Dynamic evolution of NK cells and immune remodeling mediated by CRS+HIPEC: prognostic mechanisms and therapeutic implications for malignant peritoneal mesothelioma

Dynamic evolution of NK cells and immune remodeling mediated by CRS+HIPEC: prognostic mechanisms and therapeutic implications for malignant peritoneal mesothelioma | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Dynamic evolution of NK cells and immune remodeling mediated by CRS+HIPEC: prognostic mechanisms and therapeutic implications for malignant peritoneal mesothelioma Yi-Tong Liu, Qi-Di Zhao, Xin-Li Liang, Ru Ma, Yan-Dong Su, Rui Yang, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6288852/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 03 Nov, 2025 Read the published version in World Journal of Surgical Oncology → Version 1 posted 15 You are reading this latest preprint version Abstract Background: Malignant peritoneal mesothelioma (MPM) is a highly aggressive peritoneal malignancy with a significant recurrence rate following cytoreductive surgery (CRS) combined with hyperthermic intraperitoneal chemotherapy (HIPEC). Thus, there is an urgent need to investigate novel therapeutic strategies for MPM. Natural killer (NK) cells exhibit rapid responsiveness in anti-tumor immunity; however, NK cells' dynamic evolution and clinical significance in MPM remain unclear. Methods: This study retrospectively enrolled 80 newly diagnosed MPM patients (preoperative group) and 64 patients who underwent CRS+HIPEC (postoperative group). The frequency of NK cells (CD3 - CD56 dim CD16 + ) in peripheral blood was quantified using flow cytometry. Univariate and multivariate regression analyses were performed to evaluate the association between NK cell counts and clinicopathological characteristics, intraoperative events, and prognosis. A multivariate prediction model for NK cell recovery was established. Results: Preoperative NK cell reduction was observed in 41 patients (51.3%), and this phenomenon was significantly associated with preoperative thrombosis ( P = 0.023), a high intraoperative plasma infusion volume ( P = 0.004), prolonged hospital stay ( P = 0.023), decreased total lymphocyte count ( P = 0.011), and an elevated CD4 + /CD8 + T cell ratio ( P = 0.018). The median NK cell count increased significantly to 278 cells/μL postoperatively. Postoperative NK cell reduction occurred in 20 cases (31.3%), which was independently correlated with lower Karnofsky performance scale (KPS) scores ( P = 0.048), and higher expression levels of interleukins IL-4 ( P = 0.020), IL-5 ( P = 0.007), IL-6 ( P = 0.016), and IL-8 ( P = 0.018). Elevated levels of IL-2 ( P = 0.019) and IL-4 ( P = 0.007) were identified as independent factors contributing to NK cell depletion following surgery. Survival analysis revealed that a high perioperative stress score (PSS) ( P = 0.015), lymph node metastasis ( P = 0.015), intraoperative blood loss ( P = 0.013), low preoperative CD8⁺T cell levels ( P = 0.001), and low postoperative IL-17 expression levels ( P = 0.013) were independent adverse predictors of overall survival (OS). Patients with higher preoperative NK cell levels exhibited a tendency toward longer OS. Furthermore, the dynamic NK recovery model demonstrated that baseline NK cell levels ( P < 0.001), peritoneal cancer index (PCI) ( P < 0.001), CD8⁺T cell status ( P < 0.001), and postoperative recovery time ( P < 0.001) all influenced the immune remodeling process. Conclusions: This study represents the first systematic investigation into the spatiotemporal dynamic characteristics of NK cells in MPM patients. More than half of MPM patients experienced preoperative NK cell depletion, which CRS+HIPEC could effectively reverse. The NK cell count may serve as a dynamic biomarker for tumor burden and immunosuppressive microenvironment assessment, with its preoperative elevation potentially improving prognosis. Targeting the IL-2/IL-4 pathway alone or in combination with CD8⁺ T cells may offer a novel strategy for MPM immunotherapy. malignant peritoneal mesothelioma natural killer cells cytoreductive surgery tumor microenvironment Figures Figure 1 Figure 2 1. Background Malignant peritoneal mesothelioma (MPM) is a rare malignant tumor that originates from peritoneal mesothelial cells, with an annual incidence of approximately 1–2 cases per million (1) . It accounts for 7%-30% of all mesotheliomas( 2 , 3 ). In 2020, the prevalence of MPM in China was 2.6 cases per million, corresponding to a total of 3,737 patients( 4 ). The Peritoneal Surface Oncology Group International (PSOGI) recommends cytoreductive surgery (CRS) combined with hyperthermic intraperitoneal chemotherapy (HIPEC) as the standard treatment regimen( 5 ), which has been shown to extend survival to approximately 3 years( 6 ). However, despite complete cytoreduction, the recurrence rate remains high( 7 ). Consequently, identifying novel therapeutic strategies to improve long-term patient outcomes represents an urgent clinical challenge. Natural killer (NK) cells, as the core effector cells of the innate immune system, exhibit dual anti-tumor effects by directly lysing tumor cells and modulating adaptive immunity( 8 ). Human peripheral blood (PB) NK cells can be categorized into CD3 − CD56 dim CD16 + cells (cytotoxic subset, > 90%) and CD3 − CD56 bright CD16 − cells (immunomodulatory subset, < 10%)( 9 – 11 ). Their activation does not depend on antigen presentation but rather relies on the "missing self" recognition mechanism to rapidly respond to tumor cells( 12 , 13 ). Recent studies have demonstrated that the tumor microenvironment dynamically regulates NK cell function; high tumor burden suppresses NK cell proliferation through TGF-β secretion( 14 ), whereas immune or targeted therapies can partially restore their cytotoxicity( 15 ). Although the role of NK cells in peritoneal metastatic cancers, such as gastric cancer, has been preliminarily elucidated ( 16 ), the dynamic changes and clinical significance of NK cells in MPM remain unclear. The objective of this study is to systematically analyze the dynamic alterations of PB-NK cells of MPM patients before and after surgery, to investigate their correlation with clinicopathological characteristics, treatment response, and prognosis, and to establish a predictive model for NK cell recovery, thereby providing a theoretical foundation for MPM immunotherapy. 2. Materials and Methods 2.1 Case Screening This study received approval from the Institutional Review Board of Beijing Shijitan Hospital, Capital Medical University (Approval No.: 2015- [28]). All patients provided written informed consent before undergoing CRS + HIPEC. Patients diagnosed with MPM who were treated between May 2023 and February 2025 were retrospectively identified from the hospital database. A total of 80 patients underwent preoperative PB-NK cell testing, while 64 patients had postoperative PB-NK cell testing. All included patients met the established inclusion and exclusion criteria for CRS + HIPEC( 5 ), and possessed comprehensive clinicopathological data as well as follow-up information. Venous blood samples were collected after a fasting period of 6–8 hours. Following EDTA anticoagulation, the samples were processed and analyzed within one hour to ensure accuracy and reliability. 2.2 NK Cell Detection 2.2.1 Flow Cytometry PB-NK cell subsets (CD3 − CD56 dim CD16 + ) were analyzed by flow cytometry using a FACSCanto II instrument and standardized antibodies (CD3: BD Biosciences, catalog number 340662; CD56: BD Biosciences, USA, catalog number 340723). The detection procedure adhered to the immunological counting guidelines published by the Clinical and Laboratory Standards Institute (CLSI) in 2007( 17 ). 2.2.2 Patient Grouping Patients were categorized into three groups based on preoperative NK cell counts: ( 1 ) pre-decreased group: 550 cell/µL. The rate of change was calculated as follows: Change rate = \(\:\frac{\text{Postoperative PB-NK cell count- Preoperative PB-NK cell count}}{\text{Preoperative PB-NK cell count}}\text{×100%}\) . Based on the rate of change after surgery, patients were further divided into three groups: ( 1 ) post-decrease group: 10%. 2.3 Research indicators 2.3.1 Clinicopathological features Gender, age, body mass index (BMI), previous treatment history, prior surgery score (PSS), Karnofsky performance status (KPS), histological type (epithelioid or non-epithelioid), lymph node metastasis (yes or no), vascular invasion (yes or no), Ki-67 proliferation index was recorded. 2.3.2 CRS + HIPEC-related surgical parameters Operation duration, peritoneal cancer index (PCI), tumor cytoreduction score (CC), intraoperative blood loss, intraoperative red blood cell transfusion, intraoperative plasma transfusion, number of resected organs, number of peritoneal resection areas, number of anastomoses, intraoperative ascites, and adverse events within 30 days after surgery were recorded. 2.3.3 Parameters related to immune cells The number of total lymphocytes B, T lymphocytes, CD4 + T cells, CD8 + T cells, and CD4 + /CD8 + T cell ratio in peripheral blood. The levels of interleukin (IL)-1β, IL-2, IL-4, IL-5, IL-6, IL-8, IL-10, IL-12p70, IL-17, tumor necrosis factor (TNF)-α, interferon (IFN)-α, and IFN-γ in peripheral blood. 2.3.4 Survival data The survival status, time, and cause of death of patients were recorded through outpatient follow-up or telephone interviews. The last follow-up was on February 28, 2025. The follow-up rate was 100%. Overall survival (OS) was defined as the interval from the date of diagnosis to the end of follow-up or death due to disease. 2.4 Statistical analysis Data analysis was performed using IBM SPSS Statistics for Windows, version 27.0 (IBM Corp., Armonk, NY, USA). Continuous variables were expressed as median (range) or mean ± standard deviation (SD), and a t-test or rank sum test was used for comparison between groups. Categorical variables were expressed as frequencies (percentages), and the chi-square test or Fisher's exact test was used. The Kaplan-Meier method was used to calculate OS, and the Log-rank test was used for comparison between groups. The Cox proportional hazards model was used to analyze independent prognostic factors. P < 0.05 was considered statistically significant. Model construction was performed in the R language (v4.3.1) using the caret and lm packages; model fitting and cross-validation codes are described in the Supplementary Material. 3. Results 3.1 Main clinicopathological features and NK cell characteristics of MPM patients A total of 80 patients with MPM were enrolled in the preoperative study. Among them, 35 were male (43.7%) and 45 were female (56.3%), with a median age of 56 years (range: 14–74 years). The median preoperative BMI was 22.2 kg/m 2 (range: 13.6–29.3 kg/m 2 ), and the median KPS score was 90 (range: 80–100). Preoperative thrombosis was observed in three patients (3.7%). Histologically, 58 cases (72.5%) were classified as epithelioid type, while 22 cases (27.5%) were non-epithelioid type. Before surgery, 24 patients (30.0%) received no treatment or chemotherapy, 33 patients (41.2%) underwent targeted therapy, and 23 patients (28.8%) received immunotherapy. Surgical parameters revealed that the median duration of CRS + HIPEC was 451 minutes (range: 102–886 min). The median number of organs resected was 2 (range: 0–6), and the median number of peritoneal regions stripped was 6 (range: 0–8). The median PCI was 28 (range: 1–39), and a CC0-1 score was achieved in 57 patients (71.3%). Anastomosis was performed in 36 patients (45.0%), and lymph node metastasis occurred in 9 cases (11.3%). Serious adverse events within 30 days post-surgery were reported in 16 patients (20.0%), and the median length of hospital stay was 13 days (range: 6–75 days). Preoperatively, the median PB-NK cell count was 137 cell/µL (range: 16–778 cell/µL). Decreased NK cell counts were observed in 41 patients (51.3%), normal NK cell counts in 36 patients (45.0%), and increased NK cell counts in 3 patients (3.7%) (Table 1 ). A total of 64 patients with MPM were enrolled in the postoperative study. The statistics on the detailed clinic-pathologic information was like the preoperative cohort. (Table 1 ). Table 1 Clinicopathological characteristics of MPM patients in this study Variables Preoperative group value (n = 80) Postoperative group value (n = 64) Gender, n (%) Female 45 (56.3) 38 (59.4) Male 35 (43.7) 26 (40.6) Age (years), Median (range) 56 (14–74) 56 (14–74) BMI (kg/m 2 ), Median (range) 22.2 (13.6–29.3) 23.0 (13.6–29.3) KPS, Median (range) 90 (80–100) 90 (80–100) Preoperative thrombosis, n (%) No 77 (96.3) 62 (95.4) Yes 3 (3.7) 3 (4.6) Pathological type, n (%) Epithelioid type 58 (72.5) 44 (68.8) Non-epithelioid type 22 (37.5) 20 (21.2) Preoperative Interventions, n (%) No treatment or chemotherapy 24 (30.0) 47 (73.4) Targeted therapy 33 (41.2) 9 (14.1) Immunotherapy 23 (28.8) 8 (12.5) Lymphatic metastasis, n (%) No 71 (88.7) 60 (93.8) Yes 9 (11.3) 4 (6.2) Procedure Time (minutes), Median (range) 451 (102–886) 445 (102–886) Organ resections, Median (range) 2 (0–6) 2 (0–6) Peritoneal resections, Median (range) 6 (0–9) 6 (0–9) Anastomoses, n (%) No 44 (55.0) 38 (59.4) Yes 36 (45.0) 26 (40.6) PCI, Median (range) 28 (1–39) 28 (1–39) CC, n (%) 0 ~ 1 57 (71.3) 47 (73.4) 2 ~ 3 23 (28.7) 17 (26.6) Bleeding (mL), Median (range) 100 (20–500) 100 (20–500) RBC transfusion (U), Median (range) 0 (0–6) 0 (0–6) Plasma transfusion (mL), Median (range) 600 (0-1200) 600 (0-1200) Ascites volume (mL), Median (range) 200 (0-6000) 200 (0-6000) SAEs, n (%) 16 (20.0%) 11 (17.2) Length of stay (d), Median (range) 13 (6–75) 13 (6–31) Preoperative NK cells (cell/µL), Median (range), n (%) 137 (16–778) 278 (22-1349) < 155 41 (51.3) 20 (31.3) 155–550 36 (45.0) 31 (48.4) ≥ 550 3 (3.7) 13 (20.3) MPM: malignant peritoneal mesothelioma; BMI: body mass index; KPS: Karnofsky performance status score; PCI: peritoneal cancer index; CC: degree of tumor cell reduction score; Red blood cells; SAEs: serious adverse events; NA: not available. 3.2 Comparison of Main Clinicopathological Features Between Groups The presence or absence of preoperative thrombosis was independently associated with changes in NK cells among the preoperative PB-NK cell groups (decreased, normal, and increased) ( P = 0.023). Other factors, such as gender, age, and KPS score, did not show significant differences between the two groups ( P > 0.05) (Table 2 ). The KPS score was independently correlated with changes in NK cells among the postoperative PB-NK cell groups (decreased, stable, and increased) ( P = 0.048). Other factors, such as gender and age, were not significantly different between the two groups ( P > 0.05) (Table 2 ). Table 2 Major clinicopathological characteristics of MPM patients in this study Variables Preoperative NK cell count P value Postoperative NK cell change P value Decrease group (n = 41) Normal group (n = 36) Increase group (n = 3) Decrease group (n = 16) Stable group (n = 9) Increase group (n = 39) Gender, n (%) 0.552 0.671 Female 25 (61.0) 19 (52.8) 1 (33.3) 11 (68.8) 5 (55.6) 22 (56.4) Male 16 (39.0) 17 (47.2) 2 (66.7) 5 (31.3) 4 (44.4) 17 (43.6) Age (years), n (%) 0.430 0.863 < 60 30 (73.2) 23 (63.9) 2 (66.7) 11 (68.8) 7 (77.8) 27 (70.3) ≥ 60 11 (26.8) 13 (36.1) 1 (33.3) 5 (31.3) 2 (22.2) 12 (30.8) BMI (kg/m 2 ), n (%) 0.266 0.827 < 18.5 3 (7.3) 1 (2.8) 0 (0.0) 0 (0.0) 0 (0.0) 3 (7.7) 18.5–24.0 28 (68.3) 23 (63.9) 2 (66.7) 12 (75.0) 4 (44.4) 23 (59.0) ≥ 24.0 10 (24.4) 12 (33.3) 1 (33.3) 4 (25.0) 5 (55.6) 13 (33.3) Abdominal circumference (cm), n (%) 0.243 0.621 ≤ 85 27 (65.9) 22 (61.1) 3 (100.0) 10 (62.5) 4 (44.4) 24 (61.5) < 85 14 (34.1) 14 (38.9) 0 (0.0) 6 (37.5) 5 (55.6) 15 (38.5) Surgery history, n (%) 0.211 0.125 No 14 (34.1) 10 (27.8) 0 (0.0) 2 (12.5) 5 (55.6) 13 (33.3) Yes 27 (65.9) 25 (69.4) 3 (100.0) 14 (87.6) 4 (44.4) 26 (66.7) PSS, n (%) 0.415 0.584 0/1 27 (65.9) 20 (55.6) 1 (33.3) 8 (50.0) 6 (66.7) 25 (64.1) 2/3 14 (34.1) 16 (44.4) 2 (66.7) 8 (50.0) 3 (33.3) 14 (35.9) Preoperative IPc, n (%) 0.762 0.549 No 38 (92.7) 35 (97.2) 2 (66.7) 15 (93.8) 9 (100.0) 38 (96.9) Yes 3 (7.3) 1 (2.8) 1 (33.3) 1 (6.3) 0 (0.0) 1 (2.6) KPS, n (%) 0.099 0.048 < 90 22 (53.7) 20 (55.6) 0 (0.0) 7 (43.8) 2 (22.2) 25 (64.1) ≥ 90 19 (46.3) 16 (44.4) 3 (100.0) 9 (56.3) 7 (77.8) 14 (35.9) Thrombosis history, n (%) 0.190 0.549 No 39 (95.1) 36 (100.0) 3 (100.0) 15 (93.8) 9 (100.0) 38 (96.9) Yes 2 (4.9) 0 (0.0) 0 (0.0) 1 (6.3) 0 (0.0) 1 (2.6) Preoperative thrombosis, n (%) 0.023 0.527 No 40 (97.6) 35 (97.2) 2 (66.7) 16 (100.0) 8 (88.9) 37 (94.9) Yes 1 (2.4) 1 (2.8) 1 (33.3) 0 (0.0) 1 (11.1) 2 (5.1) Pathological types, n (%) 0.408 0.556 Epithelioid 31 (75.6) 22 (61.1) 3 (100.0) 13 (81.3) 3 (33.3) 28 (71.8) Non-epithelioid 10 (24.4) 14 (38.9) 0 (0.0) 3 (18.8) 6 (66.7) 11 (28.2) Tumor vascular emboli, n (%) 0.190 0.527 No 37 (90.2) 35 (97.2) 3 (100.0) 16 (100.0) 8 (88.9) 37 (94.9) Yes 4 (9.8) 1 (2.8) 0 (0.0) 0 (0.0) 1 (11.1) 2 (5.1) Lymphatic metastasis, n (%) 0.654 0.124 No 36 (87.8) 32 (88.9) 3 (100.0) 16 (100.0) 9 (100.0) 35 (89.7) Yes 5 (12.2) 4 (11.1) 0 (0.0) 0 (0.0) 0 (0.0) 4 (10.3) Ki-67 index, n (%) 0.920 0.671 ≤ 9% 13 (31.7) 13 (36.1) 1 (33.3) 5 (31.3) 4 (44.4) 17 (43.6) > 9% 28 (68.3) 23 (63.9) 2 (66.7) 11 (68.8) 5 (55.6) 22 (56.4) Therapeutic Interventions, n (%) 0.698 0.815 No treatment or chemotherapy 12 (29.3) 12 (33.3) 0 (0.0) 12 (75.0) 6 (66.7) 29 (74.4) Targeted therapy 18 (43.9) 13 (36.1) 2 (66.7) 3 (18.8) 1 (11.1) 5 (12.8) Immunotherapy 11 (26.8) 11 (30.6) 1 (33.3) 1 (6.3) 2 (22.2) 5 (12.8) MPM: malignant peritoneal mesothelioma; BMI: body mass index; PSS: score of previous surgery; IPc: intraperitoneal chemotherapy; KPS: Karnofsky Performance Scale. 3.3 Comparison of CRS + HIPEC-Related Parameters Between Groups Plasma transfusion volume ( P = 0.004) and length of hospital stay ( P = 0.023) were independently associated with changes in preoperative PB-NK cells. Other CRS + HIPEC-related parameters, including procedure duration, PCI, CC, and number of organ resections, did not show statistically significant differences among the three groups ( P > 0.05) (Table 3 ). No independent correlation was observed between CRS + HIPEC-related parameters and changes in PB-NK cells after surgery ( P > 0.05) (Table 3 ). Table 3 Major CRS + HIPEC related characteristics of MPM patients in this study Variables Preoperative NK cell count P value Postoperative NK cell change P value Decrease group (n = 41) Normal group (n = 36) Increase group (n = 3) Decrease group (n = 16) Stable group (n = 9) Increase group (n = 39) Procedure Time (minutes), n (%) 0.469 0.985 ≤ 451 19 (46.3) 21 (58.3) 1 (33.3) 9 (56.3) 5 (55.6) 21 (53.8) > 451 22 (53.7) 15 (41.7) 2 (66.7) 7 (43.8) 4 (44.4) 18 (46.2) PCI, n (%) 0.737 0.474 ≤ 28 20 (48.8) 20 (55.6) 2 (66.7) 10 (62.5) 6 (66.7) 19 (48.7) > 28 21 (51.2) 16 (44.4) 1 (33.3) 6 (37.5) 3 (33.3) 20 (51.3) CC, n (%) 0.643 0.615 0 ~ 1 28 (68.3) 27 (75.0) 2 (66.7) 13 (81.3) 7 (77.8) 27 (69.2) 2 ~ 3 13 (31.7) 9 (25.0) 1 (33.3) 3 (18.8) 2 (22.2) 12 (30.8) NA Bleeding (mL), n (%) 0.191 0.815 ≤ 100 18 (43.9) 23 (63.9) 2 (66.7) 10 (62.5) 6 (66.7) 22 (56.4) > 100 23 (56.1) 13 (36.1) 1 (33.3) 6 (37.5) 3 (33.3) 17 (43.6) RBC transfusion, n (%) 0.356 0.714 No 22 (53.7) 25 (69.4) 2 (66.7) 11 (68.8) 7 (77.8) 25 (64.1) Yes 19 (46.3) 11 (30.6) 1 (33.3) 5 (31.3) 2 (22.2) 14 (35.9) Plasma transfusion (mL), n (%) 0.004 0.610 ≤ 600 19 (46.3) 29 (80.6) 1 (33.3) 11 (68.8) 7 (77.8) 24 (61.5) > 600 22 (53.7) 7 (19.4) 2 (66.7) 5 (31.3) 2 (22.2) 15 (38.5) Organ resections, n (%) 0.215 0.098 ≤ 2 25 (61.0) 21 (58.3) 3 (100.0) 8 (50.0) 4 (44.4) 29 (74.4) > 2 16 (39.0) 15 (41.7) 0 (0.0) 8 (50.0) 5 (55.6) 10 (25.6) Peritoneal resections, n (%) 0.884 0.188 ≤ 6 25 (61.0) 21 (58.3) 2 (66.7) 10 (62.5) 8 (88.9) 23 (59.0) > 6 16 (39.0) 15 (41.7) 1 (33.3) 6 (37.5) 1 (11.1) 16 (41.0) Anastomose, n (%) 0.137 0.134 No 23 (56.1) 18 (50.0) 3 (100.0) 7 (43.8) 5 (55.6) 27 (69.2) Yes 18 (43.9) 18 (50.0) 0 (0.0) 9 (56.3) 4 (44.4) 12 (30.8) Ascites volume (mL), n (%) 0.394 0.388 0 13 (31.7) 11 (30.6) 3 (100.0) 7 (43.8) 3 (33.3) 12 (30.8) 0 ~ 1000 18 (43.9) 15 (41.7) 0 (0.0) 4 (25.0) 5 (55.6) 20 (51.3) > 1000 10 (24.4) 10 (27.8) 0 (0.0) 5 (31.3) 1 (11.1) 7 (17.9) Length of stay (d), n (%) 0.023 0.267 ≤ 13 19 (46.3) 25 (69.4) 8 (50.0) 5 (55.6) 28 (71.8) > 13 22 (53.7) 11 (30.6) 8 (50.0) 4 (44.4) 11 (28.2) SAEs, n (%) 0.097 0.514 No 30 (73.2) 31 (86.1) 3 (100.0) 12 (75.0) 7 (77.8) 34 (87.2) Yes 11 (26.8) 5 (13.9) 0 (0.0) 4 (25.0) 2 (22.2) 5 (12.8) MPM: malignant peritoneal mesothelioma; PCI : peritoneal cancer index; CC: degree of tumor cell reduction score; SAEs: serious adverse events. 3.4 Comparison of Immune Cell-Related Parameters Between Groups The immune cell-related parameters independently correlated with the changes in PB-NK cells before surgery included the total lymphocyte count ( P = 0.011) and the CD4 + /CD8 + T lymphocyte ratio ( P = 0.018). Other immune cell-related parameters, such as B lymphocytes and IL-2, did not show statistically significant differences between the two groups ( P > 0.05) (Table 4 ). Post-surgery, the immune cell-related parameters independently associated with changes in peripheral blood NK cells included IL-4 ( P = 0.020), IL-5 ( P = 0.007), IL-6 ( P = 0.016), and IL-8 ( P = 0.018). Other immune cell-related parameters, such as B lymphocytes and IL-1β, did not exhibit statistically significant differences between the two groups ( P > 0.05) (Table 4 ). Table 4 Major immune-related characteristics of MPM patients in this study Variables Preoperative NK cell count P value Postoperative NK cell change P value Decrease group (n = 41) Normal group (n = 36) Increase group (n = 3) Decrease group (n = 16) Stable group (n = 9) Increase group (n = 39) lymphocyte (cell/µL), n (%) 0.011 0.090 < 1100 14 (34.1) 4 (11.1) 0 (0.0) 4 (25.0) 4 (44.4) 5 (12.8) ≥ 1100 27 (65.9) 32 (88.9) 3 (100.0) 12 (75.0) 5 (55.6) 34 (87.2) B lymphocyte (cell/µL), n (%) 0.567 0.869 < 90 17 (41.5) 13 (36.1) 2 (66.7) 8 (50.0) 4 (44.4) 21 (53.8) ≥ 90 24 (58.5) 23 (63.9) 1 (33.3) 8 (50.0) 5 (55.6) 18 (46.2) T lymphocyte (cell/µL), n (%) 0.335 0.692 < 940 18 (43.9) 10 (27.8) 1 (33.3) 7 (43.8) 4 (44.4) 13 (33.3) ≥ 940 23 (56.1) 26 (72.2) 2 (66.7) 9 (56.3) 5 (55.6) 26 (66.7) CD4 + T lymphocyte (cell/µL), n (%) 0.495 0.547 < 410 10 (24.4) 5 (13.9) 1 (33.3) 5 (31.3) 4 (44.4) 10 (25.6) ≥ 410 31 (75.6) 31 (86.1) 2 (66.7) 11 (68.8) 5 (55.6) 29 (74.4) CD8 + T lymphocyte (cell/µL), n (%) 0.242 0.242 < 240 10 (24.4) 6 (16.7) 0 (0.0) 3 (18.8) 1 (11.1) 3 (7.7) ≥ 240 31 (75.6) 30 (83.3) 3 (100.0) 13 (81.3) 8 (88.9) 36 (92.3) CD4 + /CD8 + T lymphocyte, n (%) 0.018 0.882 < 0.9 6 (14.6) 3 (8.3) 2 (66.7) 4 (25.0) 3 (33.3) 6 (18.2) ≥ 0.9 35 (85.4) 33 (91.7) 1 (33.3) 12 (75.0) 6 (66.7) 27 (81.8) IL-1β (pg/ml), n (%) * * ≤ 24.13 41 (100.0) 36 (100.0) 3 (100.0) 16 (100.0) 9 (100.0) 39 (100.0) > 24.13 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) IL-2 (pg/ml), n (%) 0.883 0.052 ≤ 4.96 36 (87.8) 31 (86.1) 3 (100.0) 12 (75.0) 9 (100.0) 38 (97.4) > 4.96 5 (12.2) 5 (13.9) 0 (0.0) 4 (25.0) 0 (0.0) 1 (2.6) IL-4 (pg/ml), n (%) 0.284 0.020 ≤ 3.54 32 (78.0) 24 (66.7) 2 (66.7) 16 (100.0) 8 (88.9) 24 (72.7) > 3.54 9 (22.0) 12 (33.3) 1 (33.3) 0 (0.0) 1 (11.1) 9 (27.3) IL-5 (pg/ml), n (%) * 0.007 ≤ 7.12 41 (100.0) 36 (100.0) 3 (100.0) 12 (75.0) 9 (100.0) 39 (100.0) > 7.12 0 (0.0) 0 (0.0) 0 (0.0) 4 (25.0) 0 (0.0) 0 (0.0) IL-6 (pg/ml), n (%) 0.787 0.016 ≤ 15.02 27 (65.9) 25 (69.4) 2 (66.7) 6 (37.5) 5 (55.6) 33 (84.6) > 15.02 14 (34.1) 11 (30.6) 1 (33.3) 10 (62.5) 4 (44.4) 6 (15.4) IL-8 (pg/ml), n (%) 0.614 0.018 ≤ 53.09 38 (92.7) 34 (94.4) 3 (100.0) 13 (81.3) 6 (66.7) 39 (100.0) > 53.09 3 (7.3) 2 (5.6) 0 (0.0) 3 (18.8) 3 (33.3) 0 (0.0) IL-10 (pg/ml), n (%) 0.210 0.288 ≤ 6.23 24 (58.5) 23 (63.9) 3 (100.0) 12 (75.0) 5 (55.6) 29 (74.4) > 6.23 17 (41.5) 13 (36.1) 0 (0.0) 4 (25.0) 4 (44.4) 7 (25.6) IL-12p70 (pg/ml), n (%) 0.929 0.168 ≤ 5.32 39 (95.1) 34 (94.4) 3 (100.0) 16 (100.0) 8 (88.9) 36 (92.3) > 5.32 2 (4.9) 2 (5.6) 0 (0.0) 0 (0.0) 1 (11.1) 3 (7.7) IL-17 (pg/ml), n (%) 0.357 0.434 ≤ 28.25 40 (97.6) 36 (100.0) 3 (100.0) 16 (100.0) 8 (88.9) 38 (97.4) > 28.25 1 (2.4) 0 (0.0) 0 (0.0) 0 (0.0) 1 (11.1) 1 (2.6) TNF-α (pg/ml), n (%) 0.357 0.434 ≤ 17.11 40 (97.6) 36 (100.0) 3 (100.0) 16 (100.0) 8 (88.9) 38 (97.4) > 17.11 1 (2.4) 0 (0.0) 0 (0.0) 0 (0.0) 1 (11.1) 1 (2.6) INF-α (pg/ml), n (%) 0.190 0.434 ≤ 12.57 39 (95.1) 36 (100.0) 3 (100.0) 16 (100.0) 8 (88.9) 38 (97.4) > 12.57 2 (4.9) 0 (0.0) 0 (0.0) 0 (0.0) 1 (11.1) 1 (2.6) INF-γ (pg/ml), n (%) 0.967 0.350 ≤ 3.13 25 (61.0) 22 (61.1) 2 (66.7) 15 (93.8) 6 (66.7) 29 (74.4) > 3.13 16 (39.0) 14 (38.9) 1 (33.3) 1 (6.3) 3 (33.3) 7 (25.6) MPM: malignant peritoneal mesothelioma; IL: interleukin; TNF: tumor necrosis factor; INF: interferon-gamma; *: this variable was constant and no calculation was performed. 3.5 Multivariate Analysis Based on the results of univariate analysis, the factors with P < 0.10 in the preoperative NK cell change analysis were as follows: KPS score, length of hospital stay, preoperative thrombosis, plasma transfusion volume, postoperative adverse events, total lymphocyte count, and CD4 + /CD8 + T lymphocyte ratio. Subsequent inclusion in multiple logistic regression analysis revealed that plasma transfusion volume ( P = 0.021), postoperative IL-2 value ( P = 0.019), and postoperative IL-4 value ( P = 0.007) were independent risk factors for postoperative NK cell depletion (Table 5 ). Table 5 Multivariate analysis of MPM patients in preoperative NK cell count group Variables Wald OR 95% CI P value Preoperative PB-NK cell group Plasma transfusion (> 600 mL vs. ≤ 600 mL) 6.249 4.220 [1.365, 13.050] 0.021 Postoperative PB-NK cell group IL-2 (> 4.96 pg/ml vs. ≤ 4.96 pg/ml) 0.985 0.662 [0.012, 1.538] 0.019 IL-4 (> 3.54 pg/ml vs. ≤ 3.54 pg/ml) 0.447 0.469 [0.051, 4.317] 0.007 MPM: malignant peritoneal mesothelioma; IL: interleukin. 3.6 Survival analysis As of February 28, 2025, the median OS of 80 patients with MPM had not been reached. Among these patients, 9 (11.3%) had died, and 71 (88.7%) remained alive. No significant difference was observed in OS among the three preoperative PB-NK cell groups (decreased, normal, and increased) ( P = 0.748). Km analysis of the 80 patients revealed that clinicopathological factors independently associated with MPM prognosis included PSS, abdominal circumference, PCI score, intraoperative blood loss, ascites, vascular tumor thrombus, lymph node metastasis, preoperative CD8 + T lymphocyte count, and IL-17 value ( P < 0.05). Cox regression analysis further confirmed that the clinicopathological factors independently associated with MPM prognosis were the PSS score ( P = 0.015), lymph node metastasis ( P = 0.015), intraoperative blood loss ( P = 0.013), and CD8 + T lymphocytes ( P = 0.001) (Table 6 ). Although the number of NK cells did not demonstrate statistical significance, a negative correlation with OS was observed, suggesting that increased preoperative PB-NK cell counts may be beneficial for improved OS ( P = 0.533, HR = 0.674) (Fig. 1 ). As of February 28, 2025, the median OS of 64 MPM patients had not been reached. Among these patients, 3 (4.7%) had deceased and 61 (95.3%) remained alive. No significant difference was observed in OS among the groups with decreased, stable, and increased postoperative PB-NK cells ( P = 0.748). KM analysis of the 64 patients revealed that the clinicopathological factors independently associated with MPM prognosis were postoperative IL-17, TNF-α, and IFN-α levels ( P < 0.05). Upon incorporation into Cox regression analysis, the results indicated that the clinicopathological factor independently correlated with MPM prognosis was the postoperative IL-17 value ( P = 0.013) (Table 6 ). Notably, the change in NK cell counts did not exhibit a clear association with OS ( P = 0.472, HR = 7.728) (Fig. 2 ). Table 6 Analysis of survival factors of MPM patients in this study Variables Wald HR 95% CI P value Preoperative PB-NK cell group PSS (0/1 vs. 2/3) 5.948 0.054 [0.005, 0.564] 0.015 Lymphatic metastasis (Yes vs. No) 5.902 8.266 [1.504, 45.432] 0.015 Bleeding (> 100 mL vs. ≤ 100 mL) 6.130 0.086 [0.012, 0.600] 0.013 CD8 + T lymphocyte (≥ 240 cell/µL vs. < 240 cell/µL) 11.397 0.018 [0.002, 0.186] 0.001 Postoperative PB-NK cell group Postoperative IL-17 6.212 0.029 [0.002, 0.470] 0.013 MPM: malignant peritoneal mesothelioma; PSS: score of previous surgery; IL: interleukin. 3.7 Prediction Model for NK Cell Change 3.7.1 Statistical Analysis The levels of NK cells and immune-related parameters were measured in 64 patients at various time points post-surgery. The change in PB-NK cell levels (NK_Change) was defined as the difference between the current measurement and the previous measurement, with the timepoint spanning from the last examination to the current one (in months). A total of 120 groups of NK cell change/time data were collected. Univariate analysis identified variables significantly associated with NK cell changes ( P < 0.2), among which the statistically significant variables were as follows: preoperative NK cell count ( P = 1.77×10 − 9 ), postoperative NK cell count ( P = 4.22×10 − 4 ), postoperative total lymphocyte count ( P = 5.35×10 − 4 ), postoperative T cell count ( P = 0.037), and postoperative CD8 + T cell count ( P = 0.026). To account for heteroscedasticity, the weighted least squares (WLS) method was employed, using the inverse square of the fitted values from the ordinary least squares (OLS) model as weights. The final predictive model incorporated the following predictors: postoperative NK cell level (Post_NK), preoperative NK cell level (Pre_NK), centered peritoneal cancer index (PCI_centered, calculated as PCI - mean (PCI)), postoperative CD8 + T cell count (Post_CD8), and follow-up time (Timepoint). 3.7.2 Model Specification The regression equation is expressed as: NK_Change i = β 0 + β 1 Post_NK i + β 2 Pre_NK i + β 3 PCI_centered i + β 4 Post_CD8 i + β 5 Timepoint i + ϵ i , the weight w i =1/ \(\:y\\hat :\) i 2 is derived from the fitted value \(\:y\\hat :\) i 2 for the OLS model. 3.7.3 Regression Coefficients and Model Performance The developed model demonstrated robust explanatory power and universal applicability. All regression coefficients and statistical metrics exhibited significant statistical significance: the adjusted R² was 0.810 (indicating that 81.0% of the variance was explained); the residual standard error (RSE) was 1.440, representing a substantial improvement compared to the original model (RSE = 252.8); the F-statistic was 94.01 ( P < 0.001), confirming the global significance of the model. The root mean square error (RMSE) of cross-validation was 88.755, reflecting stable performance on unseen data (Table 7 ). 3.7.4 Model Interpretation The model revealed that an increase of one unit in the Post_NK level was associated with an increase of 0.386 units in NK_Change ( P < 0.001). A higher baseline NK level (Pre_NK) was independently associated with a decrease in NK cell change (NK_Change) (β = -0.391, P < 0.001). An increase in PCI_centered was independently associated with an increase in NK cell changes (β = -1.143, P < 0.001). For each additional follow-up month (Timepoint), NK_Change increased by 8.068 units ( P < 0.001). The level of CD8 + T cells (Post_CD8) exhibited a synergistic effect with the change in NK cells (NK_Change) (β = 0.050, P < 0.001). Significant collinearity was detected between the categorical variable of treatment (Treatment_Group) and the time variable (Timepoint) in the dataset using the generalized variance inflation factor (GVIF) and Spearman's rank correlation test. The GVIF^(1/(2Df)) values were as follows: Treatment_Group, 3.76 (GVIF = 199.05, Df = 2). Treatment_Group × Timepoint interaction term, 3.99 (GVIF = 253.18, Df = 2). GVIF^(1/(2Df)) > 2, suggesting a potential risk of multicollinearity. Spearman rank correlation coefficient: there is a strong correlation between Treatment_Group and Timepoint (ρ = 0.82, P < 0.001), indicating high synchronization between these two variables. Consequently, during model construction, the Treatment_Group variable was excluded, and only the Timepoint variable was retained to ensure model stability and interpretability. Table 7 Regression coefficients and statistical significance of the model analysis of the amount of NK cell change Variables Estimated (β) Std. error T value 95% CI P value (Intercept) -59.137 0.414 -9.220 [-71.900, -46.374] < 0.001 Post_NK 0.386 0.053 7.330 [0.282, 0.491] < 0.001 Pre_NK -0.391 0.065 -5.978 [-0.521, -0.261] < 0.001 PCI_centered -1.143 0.278 -4.107 [-1.690, -0.591] < 0.001 Post_CD8 + T 0.050 0.012 4.117 [0.026, 0.074] < 0.001 Timepoint 8.068 1.303 6.193 [5.480, 10.656] < 0.001 MPM: malignant peritoneal mesothelioma; Std. error: Post_NK: preoperative peripheral blood NK cell count; Pre_NK: postoperative peripheral blood NK cell count; PCI: peritoneal carcinomatosis index; PCI_centered: equal to the PCI raw value minus the mean PCI for all patients in the data; Post_CD8 + T: postoperative peripheral blood CD8 + T cell count; Timepoint: time span of the patient from the last examination to the present examination. 4. Discussion 80 preoperative and 64 postoperative MPM patients were included in this study. The incidence of PB-NK cell depletion (< 150 cell/µL) was 51.3% (41/80) before surgery, which significantly decreased to 31.3% (20/64) after surgery. The median number of PB-NK cells increased by a factor of 2.03 postoperatively (from 137 to 278 cell/µL), with 60.9% (39/64) of patients experiencing an increase in NK cell counts following surgery. Univariate analysis revealed that preoperative NK cell levels were independently associated with thrombosis ( P = 0.023), intraoperative plasma transfusion volume ( P = 0.004), hospitalization duration ( P = 0.023), total lymphocyte count ( P = 0.011), and the CD4 + /CD8 + T lymphocyte ratio ( P = 0.018). Postoperative dynamic changes in NK cell levels were independently correlated with KPS scores ( P = 0.048) and postoperative IL-4 ( P = 0.020), IL-5 ( P = 0.007), IL-6 ( P = 0.016), and IL-8 levels ( P = 0.018). Multivariate analysis further confirmed that an increased plasma transfusion volume ( P = 0.021) was an independent risk factor for preoperative NK cell reduction, while elevated postoperative IL-2 ( P = 0.019) and IL-4 ( P = 0.007) levels served as independent predictors of NK cell reduction. Survival analysis indicated that high PSS score ( P = 0.015), lymph node metastasis ( P = 0.015), substantial intraoperative blood loss ( P = 0.013), low preoperative CD8 + T cell levels ( P = 0.001), and low postoperative IL-17 expression ( P = 0.013) were independent factors associated with poor prognosis. Although the preoperative increase in NK cell levels did not reach statistical significance, it demonstrated a trend toward improved OS. A multivariate regression model showed that baseline NK cell levels ( P < 0.001), postoperative NK cell levels ( P < 0.001), peritoneal cancer index ( P < 0.001), CD8 + T cell counts ( P < 0.001), and postoperative recovery duration ( P < 0.001) all influenced the dynamic changes in NK cell levels. Preoperative depletion of PB-NK cells is significantly associated with an elevated risk of thrombosis and increased intraoperative plasma transfusion requirements, potentially reflecting the dual pathological effects of tumor immune escape. Thangaraj et al. demonstrated that a high tumor burden in patients with solid tumors inhibits the differentiation of bone marrow NK progenitor cells via TGF-β secretion, leading to reduced PB-NK cell counts( 14 ). This immunosuppressive condition is strongly correlated with heightened surgical risks and increased transfusion needs. Although direct experimental evidence linking NK cells to the regulation of coagulation factors (e.g., TFPI) is lacking, Correia's team revealed that NK cells suppress tumor recurrence through IFN-γ secretion( 18 ), suggesting their potential role in maintaining tumor microenvironment homeostasis via immune-coagulation interactions. The median NK cell count was significantly elevated post-CRS + HIPEC, likely due to the reversal of the immunosuppressive microenvironment induced by cytoreductive surgery. Wei et al. reported that normalization of bile acid metabolism following hepatectomy restored NK cell cytotoxicity( 19 ), further supporting the potential impact of surgery on immune remodeling. Notably, a negative correlation was observed between elevated postoperative IL-2/IL-4 levels and the number of NK cells. While IL-2 has traditionally been regarded as a critical factor for NK cell survival( 20 ), recent studies indicate that continuous low-dose IL-2 administration may enhance the anti-tumor activity of NK cells via metabolic reprogramming( 21 ). Additionally, Li et al. demonstrated that late-stage IL-4 expression in a mouse model promoted granulocytes to acquire cell surface markers characteristic of myeloid-derived suppressor cells (MDSCs), which exhibit tumor-promoting effects and indirectly inhibit NK cell function( 22 ). Notably, there was a negative correlation between elevated postoperative IL-2/IL-4 levels and NK cell numbers. Currently, no studies have identified a direct relationship between IL-4/IL-5 and the number of NK cells. However, Li et al. demonstrated that late-stage expression of IL-4 in a mouse model promotes granulocytes to exhibit cell surface markers characteristic of myeloid-derived suppressor cells (MDSCs), which possess tumor-promoting effects and indirectly inhibit NK cell function( 22 ). Additionally, Li et al. reported that calcitriol can suppress the release of IL-5 in vitro and exert an anti-senescence effect on NK cells by downregulating degranulation levels( 23 ). Multivariate Cox regression analysis revealed that high intraoperative blood loss and lymph node metastasis were independent predictors of poor prognosis. Mechanistically, tumor metastases facilitate tumor progression by establishing an immunosuppressive microenvironment via the TGF-β/IL-10 pathway( 18 ). Although the preoperative NK cell level was not significantly associated with OS improvement, the multiple regression analysis demonstrated that the dynamic change in NK cell levels was independently and positively correlated with CD8⁺ T cell levels, indicating a potential immune synergistic effect between NK cells and CD8⁺ T cells. Notably, patients in the high preoperative CD8⁺ T cell expression group were significantly associated with prolonged OS, further supporting the hypothesis that the interplay between innate and adaptive immunity may jointly influence clinical prognosis. The potential prognostic value of NK cells might be attributed to various mechanisms, such as inhibiting tumor angiogenesis via IFN-γ secretion and upregulating PD-L1 expression( 18 , 24 ). Postoperative OS was significantly prolonged in patients with high IL-17 expression. Suliman et al. demonstrated that IL-17 enhances the anti-tumor immune response by recruiting cytotoxic lymphocytes via CXCL9/10( 25 ). Multivariate regression analyses revealed that patients with high baseline NK cell levels and a high PCI index exhibited reduced potential for postoperative NK recovery. This phenomenon may indicate the "immune ceiling effect," wherein treatment-induced immune enhancement is constrained when baseline immune activity approaches its functional upper limit. Furthermore, a high tumor burden persistently suppresses NK cell production via TGF-β signaling( 18 ). The synergistic interaction between NK cells and CD8 + T cells appear to be associated with the dynamic equilibrium of IFN-γ signaling. Dubrot et al. demonstrated that IFN-γ enhances antigen presentation to CD8 + T cells by upregulating MHC-I molecules while simultaneously inhibiting NK cell activation( 26 ). Single-cell sequencing is required to elucidate the spatiotemporal-specific interaction network. Additionally, PB-NK cell counts progressively increased over time following surgery, underscoring the significance of standardized postoperative management, including antineoplastic therapy integrated with nutritional support, for promoting immune recovery. Moreover, the collinearity between treatment stage and time variables might stem from the consistency of the staged comprehensive treatment protocol for MPM patients post-surgery: within 1-month post-surgery, 92% of patients received only nutritional support; from 1 to 6 months post-surgery, 78% of patients underwent drug sensitivity-guided chemotherapy (e.g., capecitabine/oxaliplatin) combined with targeted therapy (apatinib); from 6 to 12 months post-surgery, 65% of patients received immunotherapy (PD-1/PD-L1 inhibitors) in conjunction with targeted therapy (apatinib). This study constituted a single-center retrospective analysis. The postoperative cohort had a relatively small sample size (n = 64), and there was no evaluation of NK cell function, including degranulation activity and KIR expression profiles, as well as the characteristics of the microenvironment, such as the Treg/MDSC ratio. Future research should focus on multi-center prospective studies incorporating spatial transcriptome and single cell sequencing technologies to comprehensively analyze the heterogeneity of NK subsets and their dynamic interactions with CD8 + T cells. 5. Conclusion This study elucidated the dynamic changes in PB-NK cell levels among MPM patients and their clinical significance, demonstrated that CRS + HIPEC enhanced NK cell function through immune microenvironment remodeling, and established a predictive model for postoperative NK recovery. Moving forward, it is essential to integrate multi-omics approaches with prospective cohort studies to thoroughly investigate the heterogeneity of NK cell subsets and their spatiotemporal interaction networks, thereby providing precise regulatory targets for personalized immunotherapy. Declarations Ethics approval and consent to participate The study was approved by the Medical Ethics Committee of Beijing Shijitan Hospital (2015- [28]). All procedures performed in studies involving human participants were by the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The consent to participate was waived due to the retrospective nature of this study. Consent for publication Not applicable. Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request. Competing interests The authors declare that they have no competing interests. Funding This work was supported by the Beijing Municipal Administration of Hospitals’ Ascent Plan (DFL20180701). Authors contributions Conceived and designed the analysis: Yi-Tong Liu, Yan Li. The data were collected from Yi-Tong Liu, Qi-Di Zhao, Xin-Li Liang, Yang Yu and Bing Li. Contributed data or analysis tools: Yi-Tong Liu, Ru Ma, Yan-Dong Su, Rui Yang, and Tian Wei. Performed the analysis: Yi-Tong Liu, Qi-Di Zhao, Xin-Li Liang, He-Liang Wu, Yu-Bin Fu, Yu-Run Cui, Yang Yu and Bing Li. Wrote the paper: Yi-Tong Liu and Yan Li. Acknowledgments Not applicable. Competing interests The authors have stated no conflicts of interest in this research. References Désage AL, Karpathiou G, Peoc'h M, Froudarakis ME. The Immune Microenvironment of Malignant Pleural Mesothelioma: A Literature Review. Cancers (Basel). 2021;13(13):e26218. Calthorpe L, Romero-Hernandez F, Miller P, Conroy PC, Hirose K, Kim A et al. 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Novel insights on human NK cells' immunological modalities revealed by gene expression profiling. J Immunol. 2004;173(11):6547–63. Yu J, Freud AG, Caligiuri MA. Location and cellular stages of natural killer cell development. Trends Immunol. 2013;34(12):573–82. Vivier E, Raulet DH, Moretta A, Caligiuri MA, Zitvogel L, Lanier LL, et al. Innate or adaptive immunity? The example of natural killer cells. Science. 2011;331(6013):44–9. Terrén I, Orrantia A, Vitallé J, Zenarruzabeitia O, Borrego F. NK Cell Metabolism and Tumor Microenvironment. Front Immunol. 2019;10:2278. Thangaraj JL, Coffey M, Lopez E, Kaufman DS. Disruption of TGF-β signaling pathway is required to mediate effective killing of hepatocellular carcinoma by human iPSC-derived NK cells. Cell Stem Cell. 2024;31(9):1327-43.e5. Bald T, Krummel MF, Smyth MJ, Barry KC. The NK cell-cancer cycle: advances and new challenges in NK cell-based immunotherapies. Nat Immunol. 2020;21(8):835–47. Mao D, Zhou Z, Chen H, Liu X, Li D, Chen X, et al. Pleckstrin-2 promotes tumour immune escape from NK cells by activating the MT1-MMP-MICA signalling axis in gastric cancer. Cancer Lett. 2023;572:216351. CLSI. Enumeration of Immunologically Defined Cell Populations by Flow Gvtometry; ApprovedGuideline-Second Edition. Wayne, PA: Clinical and Laboratory StandardsInstitute. 2007;27:CLSI document H42-A2. Correia AL, Guimaraes JC, Auf der Maur P, De Silva D, Trefny MP, Okamoto R, et al. Hepatic stellate cells suppress NK cell-sustained breast cancer dormancy. Nature. 2021;594(7864):566–71. Wei H, Suo C, Gu X, Shen S, Lin K, Zhu C et al. AKR1D1 suppresses liver cancer progression by promoting bile acid metabolism-mediated NK cell cytotoxicity. Cell Metab. 2025. Liao W, Lin JX, Leonard WJ. Interleukin-2 at the crossroads of effector responses, tolerance, and immunotherapy. Immunity. 2013;38(1):13–25. Terrén I, Orrantia A, Mosteiro A, Vitallé J, Zenarruzabeitia O, Borrego F. Metabolic changes of Interleukin-12/15/18-stimulated human NK cells. Sci Rep. 2021;11(1):6472. Li Z, Chen L, Qin Z. Paradoxical roles of IL-4 in tumor immunity. Cell Mol Immunol. 2009;6(6):415–22. Li W, Che X, Chen X, Zhou M, Luo X, Liu T. Study of calcitriol anti-aging effects on human natural killer cells in vitro. Bioengineered. 2021;12(1):6844–54. Lin M, Luo H, Liang S, Chen J, Liu A, Niu L, et al. Pembrolizumab plus allogeneic NK cells in advanced non-small cell lung cancer patients. J Clin Invest. 2020;130(5):2560–9. Al Omar S, Flanagan BF, Almehmadi M, Christmas SE. The effects of IL-17 upon human natural killer cells. Cytokine. 2013;62(1):123–30. Dubrot J, Du PP, Lane-Reticker SK, Kessler EA, Muscato AJ, Mehta A, et al. In vivo CRISPR screens reveal the landscape of immune evasion pathways across cancer. Nat Immunol. 2022;23(10):1495–506. Additional Declarations No competing interests reported. Supplementary Files RModelcode.docx Cite Share Download PDF Status: Published Journal Publication published 03 Nov, 2025 Read the published version in World Journal of Surgical Oncology → Version 1 posted Editorial decision: Revision requested 10 Jul, 2025 Reviews received at journal 08 Jul, 2025 Reviews received at journal 07 Jul, 2025 Reviewers agreed at journal 07 Jul, 2025 Reviewers agreed at journal 01 Jul, 2025 Reviewers agreed at journal 29 Jun, 2025 Reviews received at journal 23 Jun, 2025 Reviewers agreed at journal 17 Jun, 2025 Reviewers agreed at journal 13 Jun, 2025 Reviewers agreed at journal 26 Apr, 2025 Reviewers agreed at journal 24 Apr, 2025 Reviewers invited by journal 29 Mar, 2025 Editor assigned by journal 29 Mar, 2025 Submission checks completed at journal 23 Mar, 2025 First submitted to journal 23 Mar, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Hospital","correspondingAuthor":false,"prefix":"","firstName":"Qi-Di","middleName":"","lastName":"Zhao","suffix":""},{"id":440237826,"identity":"da55be23-c34b-4a4b-9084-faa7ad467608","order_by":2,"name":"Xin-Li Liang","email":"","orcid":"","institution":"Capital Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xin-Li","middleName":"","lastName":"Liang","suffix":""},{"id":440237827,"identity":"9263b4dc-cd35-4ee1-b878-ef9bf1c9669d","order_by":3,"name":"Ru Ma","email":"","orcid":"","institution":"Beijing Tsinghua Chang Gung Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ru","middleName":"","lastName":"Ma","suffix":""},{"id":440237828,"identity":"24c7b7f5-9514-4d0e-984f-c25de78decc2","order_by":4,"name":"Yan-Dong Su","email":"","orcid":"","institution":"Capital Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yan-Dong","middleName":"","lastName":"Su","suffix":""},{"id":440237829,"identity":"51e704da-267a-4131-b47e-4e5f203a3d7d","order_by":5,"name":"Rui Yang","email":"","orcid":"","institution":"Capital Medical University","correspondingAuthor":false,"prefix":"","firstName":"Rui","middleName":"","lastName":"Yang","suffix":""},{"id":440237830,"identity":"ca7c991b-451c-4677-90af-da491150b2ce","order_by":6,"name":"Tian Wei","email":"","orcid":"","institution":"Beijing Tsinghua Chang Gung Hospital","correspondingAuthor":false,"prefix":"","firstName":"Tian","middleName":"","lastName":"Wei","suffix":""},{"id":440237831,"identity":"90c644cb-fdc4-4f6b-83f5-d93ee2c23210","order_by":7,"name":"He-Liang Wu","email":"","orcid":"","institution":"Capital Medical University","correspondingAuthor":false,"prefix":"","firstName":"He-Liang","middleName":"","lastName":"Wu","suffix":""},{"id":440237832,"identity":"906a59ec-03f0-4fcc-9156-ffacddbc6c8b","order_by":8,"name":"Yu-Bin Fu","email":"","orcid":"","institution":"Capital Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yu-Bin","middleName":"","lastName":"Fu","suffix":""},{"id":440237833,"identity":"06802718-86ca-4719-90c3-cb5639f04f0c","order_by":9,"name":"Yu-Run Cui","email":"","orcid":"","institution":"Capital Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yu-Run","middleName":"","lastName":"Cui","suffix":""},{"id":440237834,"identity":"79ca5ef2-6932-4a26-b97b-8ced39d1139d","order_by":10,"name":"Yang Yu","email":"","orcid":"","institution":"Beijing Tsinghua Chang Gung Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yang","middleName":"","lastName":"Yu","suffix":""},{"id":440237835,"identity":"705b8f4d-cdea-4525-992c-ae4eb83c5af9","order_by":11,"name":"Bing Li","email":"","orcid":"","institution":"Beijing Tsinghua Chang Gung Hospital","correspondingAuthor":false,"prefix":"","firstName":"Bing","middleName":"","lastName":"Li","suffix":""},{"id":440237836,"identity":"2ece264b-ae10-4d4f-8ac8-0f74a9c657c6","order_by":12,"name":"Yan Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAv0lEQVRIiWNgGAWjYBACPmYwxSzHz8x8+AFRWtigWowl29nSDIjTAqGYEzec51GQIE4LO4/h54I/1oybD/MwGDDU2EQT4TAeY+mZbenMZod5DzxgOJaW20CEFgNp3obDbGaH+RIMGBsOE6XF+DfPn8M8xs08BhLEajGT5mE7LGHATLwWtjJr3rZ0A4nDwEBOIMYv/PyHN9/m+WNd399/+PCDDzU2hLUwMHAgRWACYeUgwP6AOHWjYBSMglEwcgEAFs8zaR+kmdMAAAAASUVORK5CYII=","orcid":"","institution":"Beijing Tsinghua Chang Gung Hospital","correspondingAuthor":true,"prefix":"","firstName":"Yan","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2025-03-23 14:38:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6288852/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6288852/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12957-025-04019-2","type":"published","date":"2025-11-03T15:58:08+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":81014964,"identity":"9b2b029f-e1b3-4543-90ef-aeafa0f3e835","added_by":"auto","created_at":"2025-04-21 08:46:09","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":125847,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePreoperative survival analysis\u003c/strong\u003e: (A) Overall survival analysis of 80 MPM patients before surgery; (B) NK cell decreased group, normal group and increased group.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6288852/v1/136291ef93cec7b02eed9221.png"},{"id":81014956,"identity":"7359fc46-81fe-41c7-8eca-ed1f412e844a","added_by":"auto","created_at":"2025-04-21 08:46:08","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":84592,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePostoperative survival analysis\u003c/strong\u003e: (A) Overall survival analysis of 64 MPM patients after surgery; (B) NK cells decreased, unchanged and increased.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6288852/v1/403759481560008551877395.png"},{"id":95564106,"identity":"fcf00018-5d37-4aa2-87c3-74c861f2aff6","added_by":"auto","created_at":"2025-11-10 16:07:56","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2949404,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6288852/v1/ab61ce3a-e5bd-45df-af6e-5f2cff8250c6.pdf"},{"id":81016104,"identity":"e5c3e876-3117-4505-bf4e-4821129c9ba8","added_by":"auto","created_at":"2025-04-21 08:54:08","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":15137,"visible":true,"origin":"","legend":"","description":"","filename":"RModelcode.docx","url":"https://assets-eu.researchsquare.com/files/rs-6288852/v1/88e965483cda25ec1d45570f.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Dynamic evolution of NK cells and immune remodeling mediated by CRS+HIPEC: prognostic mechanisms and therapeutic implications for malignant peritoneal mesothelioma","fulltext":[{"header":"1. Background","content":"\u003cp\u003eMalignant peritoneal mesothelioma (MPM) is a rare malignant tumor that originates from peritoneal mesothelial cells, with an annual incidence of approximately 1\u0026ndash;2 cases per million\u003csup\u003e(1)\u003c/sup\u003e. It accounts for 7%-30% of all mesotheliomas(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). In 2020, the prevalence of MPM in China was 2.6 cases per million, corresponding to a total of 3,737 patients(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). The Peritoneal Surface Oncology Group International (PSOGI) recommends cytoreductive surgery (CRS) combined with hyperthermic intraperitoneal chemotherapy (HIPEC) as the standard treatment regimen(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e), which has been shown to extend survival to approximately 3 years(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). However, despite complete cytoreduction, the recurrence rate remains high(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Consequently, identifying novel therapeutic strategies to improve long-term patient outcomes represents an urgent clinical challenge.\u003c/p\u003e \u003cp\u003eNatural killer (NK) cells, as the core effector cells of the innate immune system, exhibit dual anti-tumor effects by directly lysing tumor cells and modulating adaptive immunity(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Human peripheral blood (PB) NK cells can be categorized into CD3\u003csup\u003e\u0026minus;\u003c/sup\u003eCD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e+\u003c/sup\u003e cells (cytotoxic subset, \u0026gt; 90%) and CD3\u003csup\u003e\u0026minus;\u003c/sup\u003eCD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e\u0026minus;\u003c/sup\u003e cells (immunomodulatory subset, \u0026lt; 10%)(\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Their activation does not depend on antigen presentation but rather relies on the \"missing self\" recognition mechanism to rapidly respond to tumor cells(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Recent studies have demonstrated that the tumor microenvironment dynamically regulates NK cell function; high tumor burden suppresses NK cell proliferation through TGF-β secretion(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e), whereas immune or targeted therapies can partially restore their cytotoxicity(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAlthough the role of NK cells in peritoneal metastatic cancers, such as gastric cancer, has been preliminarily elucidated (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e), the dynamic changes and clinical significance of NK cells in MPM remain unclear. The objective of this study is to systematically analyze the dynamic alterations of PB-NK cells of MPM patients before and after surgery, to investigate their correlation with clinicopathological characteristics, treatment response, and prognosis, and to establish a predictive model for NK cell recovery, thereby providing a theoretical foundation for MPM immunotherapy.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e2.1 Case Screening\u003c/h2\u003e\n \u003cp\u003eThis study received approval from the Institutional Review Board of Beijing Shijitan Hospital, Capital Medical University (Approval No.: 2015- [28]). All patients provided written informed consent before undergoing CRS\u0026thinsp;+\u0026thinsp;HIPEC. Patients diagnosed with MPM who were treated between May 2023 and February 2025 were retrospectively identified from the hospital database. A total of 80 patients underwent preoperative PB-NK cell testing, while 64 patients had postoperative PB-NK cell testing. All included patients met the established inclusion and exclusion criteria for CRS\u0026thinsp;+\u0026thinsp;HIPEC(\u003cspan class=\"CitationRef\"\u003e5\u003c/span\u003e), and possessed comprehensive clinicopathological data as well as follow-up information. Venous blood samples were collected after a fasting period of 6\u0026ndash;8 hours. Following EDTA anticoagulation, the samples were processed and analyzed within one hour to ensure accuracy and reliability.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003e2.2 NK Cell Detection\u003c/h2\u003e\n \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e\n \u003ch2\u003e2.2.1 Flow Cytometry\u003c/h2\u003e\n \u003cp\u003ePB-NK cell subsets (CD3\u003csup\u003e\u0026minus;\u003c/sup\u003eCD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e+\u003c/sup\u003e) were analyzed by flow cytometry using a FACSCanto II instrument and standardized antibodies (CD3: BD Biosciences, catalog number 340662; CD56: BD Biosciences, USA, catalog number 340723). The detection procedure adhered to the immunological counting guidelines published by the Clinical and Laboratory Standards Institute (CLSI) in 2007(\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e\n \u003ch2\u003e2.2.2 Patient Grouping\u003c/h2\u003e\n \u003cp\u003ePatients were categorized into three groups based on preoperative NK cell counts: (\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e) pre-decreased group: \u0026lt; 155 cell/\u0026micro;L; (\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e) pre-normal group: 155\u0026ndash;550 cell/\u0026micro;L; (\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e) pre-increased group: \u0026gt; 550 cell/\u0026micro;L.\u003c/p\u003e\n \u003cp\u003eThe rate of change was calculated as follows:\u003c/p\u003e\n \u003cp\u003eChange rate =\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{\\text{Postoperative PB-NK cell count- Preoperative PB-NK cell count}}{\\text{Preoperative PB-NK cell count}}\\text{\u0026times;100%}\\)\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003eBased on the rate of change after surgery, patients were further divided into three groups: (\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e) post-decrease group: \u0026lt; -10%; (\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e) post-stable group: -10\u0026ndash;10%; (\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e) post -increase group: \u0026gt; 10%.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n \u003ch2\u003e2.3 Research indicators\u003c/h2\u003e\n \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e\n \u003ch2\u003e2.3.1 Clinicopathological features\u003c/h2\u003e\n \u003cp\u003eGender, age, body mass index (BMI), previous treatment history, prior surgery score (PSS), Karnofsky performance status (KPS), histological type (epithelioid or non-epithelioid), lymph node metastasis (yes or no), vascular invasion (yes or no), Ki-67 proliferation index was recorded.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\n \u003ch2\u003e2.3.2 CRS\u0026thinsp;+\u0026thinsp;HIPEC-related surgical parameters\u003c/h2\u003e\n \u003cp\u003eOperation duration, peritoneal cancer index (PCI), tumor cytoreduction score (CC), intraoperative blood loss, intraoperative red blood cell transfusion, intraoperative plasma transfusion, number of resected organs, number of peritoneal resection areas, number of anastomoses, intraoperative ascites, and adverse events within 30 days after surgery were recorded.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e\n \u003ch2\u003e2.3.3 Parameters related to immune cells\u003c/h2\u003e\n \u003cp\u003eThe number of total lymphocytes B, T lymphocytes, CD4\u003csup\u003e+\u003c/sup\u003eT cells, CD8\u003csup\u003e+\u003c/sup\u003eT cells, and CD4\u003csup\u003e+\u003c/sup\u003e /CD8\u003csup\u003e+\u003c/sup\u003eT cell ratio in peripheral blood. The levels of interleukin (IL)-1\u0026beta;, IL-2, IL-4, IL-5, IL-6, IL-8, IL-10, IL-12p70, IL-17, tumor necrosis factor (TNF)-\u0026alpha;, interferon (IFN)-\u0026alpha;, and IFN-\u0026gamma; in peripheral blood.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e\n \u003ch2\u003e2.3.4 Survival data\u003c/h2\u003e\n \u003cp\u003eThe survival status, time, and cause of death of patients were recorded through outpatient follow-up or telephone interviews. The last follow-up was on February 28, 2025. The follow-up rate was 100%. Overall survival (OS) was defined as the interval from the date of diagnosis to the end of follow-up or death due to disease.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003e2.4 Statistical analysis\u003c/h2\u003e\n \u003cp\u003eData analysis was performed using IBM SPSS Statistics for Windows, version 27.0 (IBM Corp., Armonk, NY, USA). Continuous variables were expressed as median (range) or mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD), and a t-test or rank sum test was used for comparison between groups. Categorical variables were expressed as frequencies (percentages), and the chi-square test or Fisher\u0026apos;s exact test was used. The Kaplan-Meier method was used to calculate OS, and the Log-rank test was used for comparison between groups. The Cox proportional hazards model was used to analyze independent prognostic factors. \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. Model construction was performed in the R language (v4.3.1) using the caret and lm packages; model fitting and cross-validation codes are described in the Supplementary Material.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Main clinicopathological features and NK cell characteristics of MPM patients\u003c/h2\u003e \u003cp\u003eA total of 80 patients with MPM were enrolled in the preoperative study. Among them, 35 were male (43.7%) and 45 were female (56.3%), with a median age of 56 years (range: 14\u0026ndash;74 years). The median preoperative BMI was 22.2 kg/m\u003csup\u003e2\u003c/sup\u003e (range: 13.6\u0026ndash;29.3 kg/m\u003csup\u003e2\u003c/sup\u003e), and the median KPS score was 90 (range: 80\u0026ndash;100). Preoperative thrombosis was observed in three patients (3.7%). Histologically, 58 cases (72.5%) were classified as epithelioid type, while 22 cases (27.5%) were non-epithelioid type. Before surgery, 24 patients (30.0%) received no treatment or chemotherapy, 33 patients (41.2%) underwent targeted therapy, and 23 patients (28.8%) received immunotherapy. Surgical parameters revealed that the median duration of CRS\u0026thinsp;+\u0026thinsp;HIPEC was 451 minutes (range: 102\u0026ndash;886 min). The median number of organs resected was 2 (range: 0\u0026ndash;6), and the median number of peritoneal regions stripped was 6 (range: 0\u0026ndash;8). The median PCI was 28 (range: 1\u0026ndash;39), and a CC0-1 score was achieved in 57 patients (71.3%). Anastomosis was performed in 36 patients (45.0%), and lymph node metastasis occurred in 9 cases (11.3%). Serious adverse events within 30 days post-surgery were reported in 16 patients (20.0%), and the median length of hospital stay was 13 days (range: 6\u0026ndash;75 days). Preoperatively, the median PB-NK cell count was 137 cell/\u0026micro;L (range: 16\u0026ndash;778 cell/\u0026micro;L). Decreased NK cell counts were observed in 41 patients (51.3%), normal NK cell counts in 36 patients (45.0%), and increased NK cell counts in 3 patients (3.7%) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA total of 64 patients with MPM were enrolled in the postoperative study. The statistics on the detailed clinic-pathologic information was like the preoperative cohort. (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eClinicopathological characteristics of MPM patients in this study\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePreoperative group value (n\u0026thinsp;=\u0026thinsp;80)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePostoperative group value (n\u0026thinsp;=\u0026thinsp;64)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eGender, n (%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45 (56.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38 (59.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35 (43.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (40.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years), Median (range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56 (14\u0026ndash;74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56 (14\u0026ndash;74)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e), Median (range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.2 (13.6\u0026ndash;29.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.0 (13.6\u0026ndash;29.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKPS, Median (range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e90 (80\u0026ndash;100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90 (80\u0026ndash;100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003ePreoperative thrombosis, n (%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e77 (96.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62 (95.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (3.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (4.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003ePathological type, n (%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEpithelioid type\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58 (72.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44 (68.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-epithelioid type\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22 (37.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (21.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003ePreoperative Interventions, n (%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo treatment or chemotherapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24 (30.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47 (73.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTargeted therapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33 (41.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (14.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImmunotherapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23 (28.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (12.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eLymphatic metastasis, n (%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71 (88.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60 (93.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (11.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (6.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProcedure Time (minutes), Median (range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e451 (102\u0026ndash;886)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e445 (102\u0026ndash;886)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOrgan resections, Median (range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (0\u0026ndash;6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (0\u0026ndash;6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePeritoneal resections, Median (range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (0\u0026ndash;9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (0\u0026ndash;9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eAnastomoses, n (%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44 (55.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38 (59.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36 (45.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (40.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCI, Median (range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (1\u0026ndash;39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28 (1\u0026ndash;39)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eCC, n (%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u0026thinsp;~\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e57 (71.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47 (73.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u0026thinsp;~\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23 (28.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (26.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBleeding (mL), Median (range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100 (20\u0026ndash;500)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100 (20\u0026ndash;500)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRBC transfusion (U), Median (range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0\u0026ndash;6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0\u0026ndash;6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlasma transfusion (mL), Median (range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e600 (0-1200)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e600 (0-1200)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAscites volume (mL), Median (range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e200 (0-6000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e200 (0-6000)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSAEs, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (20.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (17.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLength of stay (d), Median (range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (6\u0026ndash;75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (6\u0026ndash;31)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePreoperative NK cells (cell/\u0026micro;L), Median (range), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e137 (16\u0026ndash;778)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e278 (22-1349)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41 (51.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (31.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e155\u0026ndash;550\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36 (45.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31 (48.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;550\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (3.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (20.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eMPM: malignant peritoneal mesothelioma; BMI: body mass index; KPS: Karnofsky performance status score; PCI: peritoneal cancer index; CC: degree of tumor cell reduction score; Red blood cells; SAEs: serious adverse events; NA: not available.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Comparison of Main Clinicopathological Features Between Groups\u003c/h2\u003e \u003cp\u003eThe presence or absence of preoperative thrombosis was independently associated with changes in NK cells among the preoperative PB-NK cell groups (decreased, normal, and increased) (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.023). Other factors, such as gender, age, and KPS score, did not show significant differences between the two groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The KPS score was independently correlated with changes in NK cells among the postoperative PB-NK cell groups (decreased, stable, and increased) (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.048). Other factors, such as gender and age, were not significantly different between the two groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMajor clinicopathological characteristics of MPM patients in this study\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003ePreoperative NK cell count\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003ePostoperative NK cell change\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDecrease\u003c/p\u003e \u003cp\u003egroup\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;41)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003cp\u003egroup\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;36)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIncrease\u003c/p\u003e \u003cp\u003egroup (n\u0026thinsp;=\u0026thinsp;3)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDecrease group\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;16)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eStable group\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;9)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eIncrease\u003c/p\u003e \u003cp\u003egroup\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;39)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eGender, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.552\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.671\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25 (61.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (52.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11 (68.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5 (55.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e22 (56.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (39.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (47.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5 (31.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4 (44.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e17 (43.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eAge (years), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.430\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.863\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30 (73.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (63.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11 (68.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7 (77.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e27 (70.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11 (26.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (36.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5 (31.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2 (22.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e12 (30.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.827\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;18.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (7.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (2.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3 (7.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18.5\u0026ndash;24.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (68.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (63.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12 (75.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4 (44.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e23 (59.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;24.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (24.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4 (25.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5 (55.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e13 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eAbdominal circumference (cm), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.243\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.621\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27 (65.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (61.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10 (62.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4 (44.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e24 (61.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (34.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (38.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6 (37.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5 (55.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e15 (38.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eSurgery history, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.211\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.125\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (34.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (27.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2 (12.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5 (55.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e13 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27 (65.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (69.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14 (87.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4 (44.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e26 (66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003ePSS, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.415\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.584\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0/1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27 (65.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (55.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8 (50.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6 (66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e25 (64.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2/3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (34.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (44.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8 (50.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e14 (35.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003ePreoperative IPc, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.762\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.549\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38 (92.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35 (97.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15 (93.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e38 (96.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (7.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (2.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (6.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1 (2.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eKPS, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.099\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.048\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22 (53.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (55.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7 (43.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2 (22.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e25 (64.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (46.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (44.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9 (56.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7 (77.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e14 (35.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eThrombosis history, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.549\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39 (95.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15 (93.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e38 (96.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (4.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (6.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1 (2.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003ePreoperative thrombosis, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.023\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.527\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40 (97.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35 (97.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8 (88.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e37 (94.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (2.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2 (5.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003ePathological types, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.408\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.556\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEpithelioid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31 (75.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (61.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13 (81.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e28 (71.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-epithelioid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (24.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (38.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3 (18.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6 (66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e11 (28.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eTumor vascular emboli, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.527\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37 (90.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35 (97.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8 (88.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e37 (94.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (9.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (2.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2 (5.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eLymphatic metastasis, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.654\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.124\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36 (87.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 (88.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e35 (89.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (12.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4 (10.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eKi-67 index, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.920\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.671\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (31.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (36.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5 (31.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4 (44.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e17 (43.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (68.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (63.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11 (68.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5 (55.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e22 (56.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eTherapeutic Interventions, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.698\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.815\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo treatment or chemotherapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (29.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12 (75.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6 (66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e29 (74.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTargeted therapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (43.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (36.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3 (18.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5 (12.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImmunotherapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11 (26.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (30.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (6.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2 (22.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5 (12.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003eMPM: malignant peritoneal mesothelioma; BMI: body mass index; PSS: score of previous surgery; IPc: intraperitoneal chemotherapy; KPS: Karnofsky Performance Scale.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Comparison of CRS\u0026thinsp;+\u0026thinsp;HIPEC-Related Parameters Between Groups\u003c/h2\u003e \u003cp\u003ePlasma transfusion volume (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004) and length of hospital stay (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.023) were independently associated with changes in preoperative PB-NK cells. Other CRS\u0026thinsp;+\u0026thinsp;HIPEC-related parameters, including procedure duration, PCI, CC, and number of organ resections, did not show statistically significant differences among the three groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). No independent correlation was observed between CRS\u0026thinsp;+\u0026thinsp;HIPEC-related parameters and changes in PB-NK cells after surgery (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMajor CRS\u0026thinsp;+\u0026thinsp;HIPEC related characteristics of MPM patients in this study\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003ePreoperative NK cell count\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003ePostoperative NK cell change\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDecrease\u003c/p\u003e \u003cp\u003egroup\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;41)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003cp\u003egroup\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;36)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIncrease\u003c/p\u003e \u003cp\u003egroup (n\u0026thinsp;=\u0026thinsp;3)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDecrease group\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;16)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eStable\u003c/p\u003e \u003cp\u003egroup\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;9)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eIncrease\u003c/p\u003e \u003cp\u003egroup\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;39)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eProcedure Time (minutes), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.469\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.985\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;451\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (46.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 (58.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9 (56.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5 (55.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e21 (53.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;451\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22 (53.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (41.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7 (43.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4 (44.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e18 (46.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003ePCI, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.737\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.474\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 (48.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (55.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10 (62.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6 (66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e19 (48.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21 (51.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (44.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6 (37.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e20 (51.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eCC, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.643\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.615\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u0026thinsp;~\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (68.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27 (75.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13 (81.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7 (77.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e27 (69.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u0026thinsp;~\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (31.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (25.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3 (18.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2 (22.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e12 (30.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eBleeding (mL), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.191\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.815\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (43.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (63.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10 (62.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6 (66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e22 (56.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23 (56.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (36.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6 (37.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e17 (43.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eRBC transfusion, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.356\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.714\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22 (53.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (69.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11 (68.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7 (77.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e25 (64.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (46.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (30.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5 (31.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2 (22.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e14 (35.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003ePlasma transfusion (mL), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.610\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (46.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29 (80.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11 (68.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7 (77.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e24 (61.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22 (53.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (19.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5 (31.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2 (22.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e15 (38.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eOrgan resections, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.215\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.098\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25 (61.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 (58.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8 (50.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4 (44.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e29 (74.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (39.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (41.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8 (50.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5 (55.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10 (25.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003ePeritoneal resections, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.884\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.188\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25 (61.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 (58.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10 (62.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8 (88.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e23 (59.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (39.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (41.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6 (37.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e16 (41.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eAnastomose, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.137\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.134\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23 (56.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (50.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7 (43.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5 (55.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e27 (69.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (43.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (50.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9 (56.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4 (44.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e12 (30.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eAscites volume (mL), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.394\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.388\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (31.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (30.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7 (43.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e12 (30.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u0026thinsp;~\u0026thinsp;1000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (43.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (41.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4 (25.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5 (55.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e20 (51.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;1000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (24.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (27.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5 (31.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7 (17.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eLength of stay (d), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.023\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.267\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (46.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (69.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8 (50.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5 (55.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e28 (71.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22 (53.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (30.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8 (50.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4 (44.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e11 (28.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eSAEs, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.097\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.514\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30 (73.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31 (86.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12 (75.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7 (77.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e34 (87.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11 (26.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (13.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4 (25.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2 (22.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5 (12.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003eMPM: malignant peritoneal mesothelioma; PCI : peritoneal cancer index; CC: degree of tumor cell reduction score; SAEs: serious adverse events.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Comparison of Immune Cell-Related Parameters Between Groups\u003c/h2\u003e \u003cp\u003eThe immune cell-related parameters independently correlated with the changes in PB-NK cells before surgery included the total lymphocyte count (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.011) and the CD4\u003csup\u003e+\u003c/sup\u003e/CD8\u003csup\u003e+\u003c/sup\u003e T lymphocyte ratio (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.018). Other immune cell-related parameters, such as B lymphocytes and IL-2, did not show statistically significant differences between the two groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePost-surgery, the immune cell-related parameters independently associated with changes in peripheral blood NK cells included IL-4 (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.020), IL-5 (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.007), IL-6 (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.016), and IL-8 (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.018). Other immune cell-related parameters, such as B lymphocytes and IL-1β, did not exhibit statistically significant differences between the two groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMajor immune-related characteristics of MPM patients in this study\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003ePreoperative NK cell count\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003ePostoperative NK cell change\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDecrease\u003c/p\u003e \u003cp\u003egroup\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;41)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003cp\u003egroup\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;36)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIncrease\u003c/p\u003e \u003cp\u003egroup (n\u0026thinsp;=\u0026thinsp;3)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDecrease group\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;16)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eStable\u003c/p\u003e \u003cp\u003egroup\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;9)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eIncrease\u003c/p\u003e \u003cp\u003egroup\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;39)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003elymphocyte (cell/\u0026micro;L), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.011\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.090\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (34.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4 (25.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4 (44.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5 (12.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;1100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27 (65.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 (88.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12 (75.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5 (55.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e34 (87.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eB lymphocyte (cell/\u0026micro;L), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.567\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.869\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (41.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (36.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8 (50.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4 (44.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e21 (53.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24 (58.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (63.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8 (50.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5 (55.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e18 (46.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eT lymphocyte (cell/\u0026micro;L), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.335\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.692\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;940\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (43.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (27.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7 (43.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4 (44.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e13 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;940\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23 (56.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (72.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9 (56.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5 (55.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e26 (66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eCD4\u003csup\u003e+\u003c/sup\u003eT lymphocyte (cell/\u0026micro;L), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.495\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.547\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;410\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (24.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (13.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5 (31.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4 (44.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10 (25.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;410\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31 (75.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31 (86.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11 (68.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5 (55.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e29 (74.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eCD8\u003csup\u003e+\u003c/sup\u003eT lymphocyte (cell/\u0026micro;L), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.242\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;240\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (24.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (16.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3 (18.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3 (7.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;240\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31 (75.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30 (83.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13 (81.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8 (88.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e36 (92.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eCD4\u003csup\u003e+\u003c/sup\u003e/CD8\u003csup\u003e+\u003c/sup\u003eT lymphocyte, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.018\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.882\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (14.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (8.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4 (25.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6 (18.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35 (85.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33 (91.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12 (75.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6 (66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e27 (81.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eIL-1β (pg/ml), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;24.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e39 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;24.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eIL-2 (pg/ml), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.883\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.052\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;4.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36 (87.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31 (86.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12 (75.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e38 (97.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;4.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (12.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (13.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4 (25.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1 (2.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eIL-4 (pg/ml), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.284\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.020\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;3.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32 (78.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24 (66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8 (88.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e24 (72.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;3.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (22.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9 (27.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eIL-5 (pg/ml), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.007\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;7.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12 (75.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e39 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;7.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4 (25.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eIL-6 (pg/ml), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.787\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.016\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;15.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27 (65.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (69.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6 (37.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5 (55.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e33 (84.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;15.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (34.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (30.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10 (62.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4 (44.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6 (15.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eIL-8 (pg/ml), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.614\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.018\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;53.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38 (92.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34 (94.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13 (81.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6 (66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e39 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;53.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (7.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (5.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3 (18.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eIL-10 (pg/ml), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.210\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.288\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;6.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24 (58.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (63.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12 (75.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5 (55.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e29 (74.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;6.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (41.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (36.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4 (25.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4 (44.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7 (25.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eIL-12p70 (pg/ml), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.929\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.168\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;5.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39 (95.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34 (94.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8 (88.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e36 (92.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;5.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (4.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (5.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3 (7.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eIL-17 (pg/ml), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.357\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.434\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;28.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40 (97.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8 (88.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e38 (97.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;28.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1 (2.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eTNF-α (pg/ml), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.357\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.434\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;17.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40 (97.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8 (88.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e38 (97.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;17.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1 (2.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eINF-α (pg/ml), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.434\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;12.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39 (95.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8 (88.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e38 (97.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;12.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (4.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1 (2.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eINF-γ (pg/ml), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.967\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.350\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;3.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25 (61.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (61.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15 (93.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6 (66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e29 (74.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;3.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (39.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (38.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (6.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7 (25.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003eMPM: malignant peritoneal mesothelioma; IL: interleukin; TNF: tumor necrosis factor; INF: interferon-gamma; *: this variable was constant and no calculation was performed.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Multivariate Analysis\u003c/h2\u003e \u003cp\u003eBased on the results of univariate analysis, the factors with \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.10 in the preoperative NK cell change analysis were as follows: KPS score, length of hospital stay, preoperative thrombosis, plasma transfusion volume, postoperative adverse events, total lymphocyte count, and CD4\u003csup\u003e+\u003c/sup\u003e/CD8\u003csup\u003e+\u003c/sup\u003e T lymphocyte ratio. Subsequent inclusion in multiple logistic regression analysis revealed that plasma transfusion volume (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.021), postoperative IL-2 value (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.019), and postoperative IL-4 value (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.007) were independent risk factors for postoperative NK cell depletion (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultivariate analysis of MPM patients in preoperative NK cell count group\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWald\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003ePreoperative PB-NK cell group\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlasma transfusion (\u0026gt;\u0026thinsp;600 mL vs. \u0026le; 600 mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.249\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.220\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e[1.365, 13.050]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.021\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003ePostoperative PB-NK cell group\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-2 (\u0026gt;\u0026thinsp;4.96 pg/ml vs. \u0026le; 4.96 pg/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.985\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.662\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e[0.012, 1.538]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.019\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-4 (\u0026gt;\u0026thinsp;3.54 pg/ml vs. \u0026le; 3.54 pg/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.447\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.469\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e[0.051, 4.317]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.007\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eMPM: malignant peritoneal mesothelioma; IL: interleukin.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e3.6 Survival analysis\u003c/h2\u003e \u003cp\u003eAs of February 28, 2025, the median OS of 80 patients with MPM had not been reached. Among these patients, 9 (11.3%) had died, and 71 (88.7%) remained alive. No significant difference was observed in OS among the three preoperative PB-NK cell groups (decreased, normal, and increased) (\u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.748). Km analysis of the 80 patients revealed that clinicopathological factors independently associated with MPM prognosis included PSS, abdominal circumference, PCI score, intraoperative blood loss, ascites, vascular tumor thrombus, lymph node metastasis, preoperative CD8\u003csup\u003e+\u003c/sup\u003e T lymphocyte count, and IL-17 value (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Cox regression analysis further confirmed that the clinicopathological factors independently associated with MPM prognosis were the PSS score (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.015), lymph node metastasis (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.015), intraoperative blood loss (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.013), and CD8\u003csup\u003e+\u003c/sup\u003e T lymphocytes (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Although the number of NK cells did not demonstrate statistical significance, a negative correlation with OS was observed, suggesting that increased preoperative PB-NK cell counts may be beneficial for improved OS (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.533, HR\u0026thinsp;=\u0026thinsp;0.674) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAs of February 28, 2025, the median OS of 64 MPM patients had not been reached. Among these patients, 3 (4.7%) had deceased and 61 (95.3%) remained alive. No significant difference was observed in OS among the groups with decreased, stable, and increased postoperative PB-NK cells (\u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.748). KM analysis of the 64 patients revealed that the clinicopathological factors independently associated with MPM prognosis were postoperative IL-17, TNF-α, and IFN-α levels (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Upon incorporation into Cox regression analysis, the results indicated that the clinicopathological factor independently correlated with MPM prognosis was the postoperative IL-17 value (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.013) (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Notably, the change in NK cell counts did not exhibit a clear association with OS (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.472, HR\u0026thinsp;=\u0026thinsp;7.728) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAnalysis of survival factors of MPM patients in this study\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWald\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003ePreoperative PB-NK cell group\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePSS (0/1 \u003cem\u003evs.\u003c/em\u003e 2/3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.948\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e[0.005, 0.564]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.015\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphatic metastasis (Yes \u003cem\u003evs.\u003c/em\u003e No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.902\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e[1.504, 45.432]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.015\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBleeding (\u0026gt;\u0026thinsp;100 mL \u003cem\u003evs.\u003c/em\u003e \u0026le; 100 mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.086\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e[0.012, 0.600]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.013\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD8\u003csup\u003e+\u003c/sup\u003eT lymphocyte (\u0026ge;\u0026thinsp;240 cell/\u0026micro;L \u003cem\u003evs.\u003c/em\u003e \u0026lt; 240 cell/\u0026micro;L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.397\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e[0.002, 0.186]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003ePostoperative PB-NK cell group\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostoperative IL-17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e[0.002, 0.470]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.013\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eMPM: malignant peritoneal mesothelioma; PSS: score of previous surgery; IL: interleukin.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e3.7 Prediction Model for NK Cell Change\u003c/h2\u003e \u003cdiv id=\"Sec21\" class=\"Section3\"\u003e \u003ch2\u003e3.7.1 Statistical Analysis\u003c/h2\u003e \u003cp\u003eThe levels of NK cells and immune-related parameters were measured in 64 patients at various time points post-surgery. The change in PB-NK cell levels (NK_Change) was defined as the difference between the current measurement and the previous measurement, with the timepoint spanning from the last examination to the current one (in months). A total of 120 groups of NK cell change/time data were collected. Univariate analysis identified variables significantly associated with NK cell changes (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.2), among which the statistically significant variables were as follows: preoperative NK cell count (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.77\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;9\u003c/sup\u003e), postoperative NK cell count (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;4.22\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e), postoperative total lymphocyte count (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5.35\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e), postoperative T cell count (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.037), and postoperative CD8\u003csup\u003e+\u003c/sup\u003eT cell count (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.026). To account for heteroscedasticity, the weighted least squares (WLS) method was employed, using the inverse square of the fitted values from the ordinary least squares (OLS) model as weights. The final predictive model incorporated the following predictors: postoperative NK cell level (Post_NK), preoperative NK cell level (Pre_NK), centered peritoneal cancer index (PCI_centered, calculated as PCI - mean (PCI)), postoperative CD8\u003csup\u003e+\u003c/sup\u003eT cell count (Post_CD8), and follow-up time (Timepoint).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section3\"\u003e \u003ch2\u003e3.7.2 Model Specification\u003c/h2\u003e \u003cp\u003eThe regression equation is expressed as:\u003c/p\u003e \u003cp\u003eNK_Change\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;\u003cem\u003eβ\u003c/em\u003e\u003csub\u003e0\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;\u003cem\u003eβ\u003c/em\u003e\u003csub\u003e1\u003c/sub\u003ePost_NK\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;\u003cem\u003eβ\u003c/em\u003e\u003csub\u003e2\u003c/sub\u003ePre_NK\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;\u003cem\u003eβ\u003c/em\u003e\u003csub\u003e3\u003c/sub\u003ePCI_centered\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;\u003cem\u003eβ\u003c/em\u003e\u003csub\u003e4\u003c/sub\u003ePost_CD8\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;\u003cem\u003eβ\u003c/em\u003e\u003csub\u003e5\u003c/sub\u003eTimepoint\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e+\u003cem\u003eϵ\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e, the weight \u003cem\u003ew\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e=1/\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:y\\\\hat :\\)\u003c/span\u003e\u003c/span\u003e\u003csub\u003ei\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e is derived from the fitted value \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:y\\\\hat :\\)\u003c/span\u003e\u003c/span\u003e\u003csub\u003ei\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e for the OLS model.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003e3.7.3 Regression Coefficients and Model Performance\u003c/h2\u003e \u003cp\u003eThe developed model demonstrated robust explanatory power and universal applicability. All regression coefficients and statistical metrics exhibited significant statistical significance: the adjusted R\u0026sup2; was 0.810 (indicating that 81.0% of the variance was explained); the residual standard error (RSE) was 1.440, representing a substantial improvement compared to the original model (RSE\u0026thinsp;=\u0026thinsp;252.8); the F-statistic was 94.01 (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), confirming the global significance of the model. The root mean square error (RMSE) of cross-validation was 88.755, reflecting stable performance on unseen data (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section3\"\u003e \u003ch2\u003e3.7.4 Model Interpretation\u003c/h2\u003e \u003cp\u003eThe model revealed that an increase of one unit in the Post_NK level was associated with an increase of 0.386 units in NK_Change (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). A higher baseline NK level (Pre_NK) was independently associated with a decrease in NK cell change (NK_Change) (β = -0.391, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). An increase in PCI_centered was independently associated with an increase in NK cell changes (β = -1.143, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). For each additional follow-up month (Timepoint), NK_Change increased by 8.068 units (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The level of CD8\u0026thinsp;+\u0026thinsp;T cells (Post_CD8) exhibited a synergistic effect with the change in NK cells (NK_Change) (β\u0026thinsp;=\u0026thinsp;0.050, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003eSignificant collinearity was detected between the categorical variable of treatment (Treatment_Group) and the time variable (Timepoint) in the dataset using the generalized variance inflation factor (GVIF) and Spearman's rank correlation test.\u003c/p\u003e \u003cp\u003eThe GVIF^(1/(2Df)) values were as follows:\u003c/p\u003e \u003cp\u003eTreatment_Group, 3.76 (GVIF\u0026thinsp;=\u0026thinsp;199.05, Df\u0026thinsp;=\u0026thinsp;2).\u003c/p\u003e \u003cp\u003eTreatment_Group \u0026times; Timepoint interaction term, 3.99 (GVIF\u0026thinsp;=\u0026thinsp;253.18, Df\u0026thinsp;=\u0026thinsp;2).\u003c/p\u003e \u003cp\u003eGVIF^(1/(2Df))\u0026thinsp;\u0026gt;\u0026thinsp;2, suggesting a potential risk of multicollinearity.\u003c/p\u003e \u003cp\u003eSpearman rank correlation coefficient: there is a strong correlation between Treatment_Group and Timepoint (ρ\u0026thinsp;=\u0026thinsp;0.82, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), indicating high synchronization between these two variables. Consequently, during model construction, the Treatment_Group variable was excluded, and only the Timepoint variable was retained to ensure model stability and interpretability.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRegression coefficients and statistical significance of the model analysis of the amount of NK cell change\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEstimated (β)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStd. error\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eT\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Intercept)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-59.137\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.414\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-9.220\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[-71.900, -46.374]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePost_NK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.386\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.053\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.330\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[0.282, 0.491]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePre_NK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.391\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-5.978\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[-0.521, -0.261]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCI_centered\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1.143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.278\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-4.107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[-1.690, -0.591]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePost_CD8\u003csup\u003e+\u003c/sup\u003eT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[0.026, 0.074]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTimepoint\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.303\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.193\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[5.480, 10.656]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eMPM: malignant peritoneal mesothelioma; Std. error: Post_NK: preoperative peripheral blood NK cell count; Pre_NK: postoperative peripheral blood NK cell count; PCI: peritoneal carcinomatosis index; PCI_centered: equal to the PCI raw value minus the mean PCI for all patients in the data; Post_CD8\u003csup\u003e+\u003c/sup\u003eT: postoperative peripheral blood CD8\u003csup\u003e+\u003c/sup\u003eT cell count; Timepoint: time span of the patient from the last examination to the present examination.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003e80 preoperative and 64 postoperative MPM patients were included in this study. The incidence of PB-NK cell depletion (\u0026lt;\u0026thinsp;150 cell/\u0026micro;L) was 51.3% (41/80) before surgery, which significantly decreased to 31.3% (20/64) after surgery. The median number of PB-NK cells increased by a factor of 2.03 postoperatively (from 137 to 278 cell/\u0026micro;L), with 60.9% (39/64) of patients experiencing an increase in NK cell counts following surgery. Univariate analysis revealed that preoperative NK cell levels were independently associated with thrombosis (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.023), intraoperative plasma transfusion volume (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004), hospitalization duration (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.023), total lymphocyte count (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.011), and the CD4\u003csup\u003e+\u003c/sup\u003e/CD8\u003csup\u003e+\u003c/sup\u003eT lymphocyte ratio (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.018). Postoperative dynamic changes in NK cell levels were independently correlated with KPS scores (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.048) and postoperative IL-4 (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.020), IL-5 (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.007), IL-6 (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.016), and IL-8 levels (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.018). Multivariate analysis further confirmed that an increased plasma transfusion volume (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.021) was an independent risk factor for preoperative NK cell reduction, while elevated postoperative IL-2 (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.019) and IL-4 (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.007) levels served as independent predictors of NK cell reduction. Survival analysis indicated that high PSS score (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.015), lymph node metastasis (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.015), substantial intraoperative blood loss (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.013), low preoperative CD8\u003csup\u003e+\u003c/sup\u003e T cell levels (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001), and low postoperative IL-17 expression (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.013) were independent factors associated with poor prognosis. Although the preoperative increase in NK cell levels did not reach statistical significance, it demonstrated a trend toward improved OS. A multivariate regression model showed that baseline NK cell levels (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), postoperative NK cell levels (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), peritoneal cancer index (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), CD8\u003csup\u003e+\u003c/sup\u003e T cell counts (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and postoperative recovery duration (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) all influenced the dynamic changes in NK cell levels.\u003c/p\u003e \u003cp\u003ePreoperative depletion of PB-NK cells is significantly associated with an elevated risk of thrombosis and increased intraoperative plasma transfusion requirements, potentially reflecting the dual pathological effects of tumor immune escape. Thangaraj et al. demonstrated that a high tumor burden in patients with solid tumors inhibits the differentiation of bone marrow NK progenitor cells via TGF-β secretion, leading to reduced PB-NK cell counts(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). This immunosuppressive condition is strongly correlated with heightened surgical risks and increased transfusion needs. Although direct experimental evidence linking NK cells to the regulation of coagulation factors (e.g., TFPI) is lacking, Correia's team revealed that NK cells suppress tumor recurrence through IFN-γ secretion(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e), suggesting their potential role in maintaining tumor microenvironment homeostasis via immune-coagulation interactions.\u003c/p\u003e \u003cp\u003eThe median NK cell count was significantly elevated post-CRS\u0026thinsp;+\u0026thinsp;HIPEC, likely due to the reversal of the immunosuppressive microenvironment induced by cytoreductive surgery. Wei et al. reported that normalization of bile acid metabolism following hepatectomy restored NK cell cytotoxicity(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e), further supporting the potential impact of surgery on immune remodeling. Notably, a negative correlation was observed between elevated postoperative IL-2/IL-4 levels and the number of NK cells. While IL-2 has traditionally been regarded as a critical factor for NK cell survival(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e), recent studies indicate that continuous low-dose IL-2 administration may enhance the anti-tumor activity of NK cells via metabolic reprogramming(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Additionally, Li et al. demonstrated that late-stage IL-4 expression in a mouse model promoted granulocytes to acquire cell surface markers characteristic of myeloid-derived suppressor cells (MDSCs), which exhibit tumor-promoting effects and indirectly inhibit NK cell function(\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eNotably, there was a negative correlation between elevated postoperative IL-2/IL-4 levels and NK cell numbers. Currently, no studies have identified a direct relationship between IL-4/IL-5 and the number of NK cells. However, Li et al. demonstrated that late-stage expression of IL-4 in a mouse model promotes granulocytes to exhibit cell surface markers characteristic of myeloid-derived suppressor cells (MDSCs), which possess tumor-promoting effects and indirectly inhibit NK cell function(\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Additionally, Li et al. reported that calcitriol can suppress the release of IL-5 in vitro and exert an anti-senescence effect on NK cells by downregulating degranulation levels(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMultivariate Cox regression analysis revealed that high intraoperative blood loss and lymph node metastasis were independent predictors of poor prognosis. Mechanistically, tumor metastases facilitate tumor progression by establishing an immunosuppressive microenvironment via the TGF-β/IL-10 pathway(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Although the preoperative NK cell level was not significantly associated with OS improvement, the multiple regression analysis demonstrated that the dynamic change in NK cell levels was independently and positively correlated with CD8⁺ T cell levels, indicating a potential immune synergistic effect between NK cells and CD8⁺ T cells. Notably, patients in the high preoperative CD8⁺ T cell expression group were significantly associated with prolonged OS, further supporting the hypothesis that the interplay between innate and adaptive immunity may jointly influence clinical prognosis. The potential prognostic value of NK cells might be attributed to various mechanisms, such as inhibiting tumor angiogenesis via IFN-γ secretion and upregulating PD-L1 expression(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Postoperative OS was significantly prolonged in patients with high IL-17 expression. Suliman et al. demonstrated that IL-17 enhances the anti-tumor immune response by recruiting cytotoxic lymphocytes via CXCL9/10(\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMultivariate regression analyses revealed that patients with high baseline NK cell levels and a high PCI index exhibited reduced potential for postoperative NK recovery. This phenomenon may indicate the \"immune ceiling effect,\" wherein treatment-induced immune enhancement is constrained when baseline immune activity approaches its functional upper limit. Furthermore, a high tumor burden persistently suppresses NK cell production via TGF-β signaling(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). The synergistic interaction between NK cells and CD8\u003csup\u003e+\u003c/sup\u003e T cells appear to be associated with the dynamic equilibrium of IFN-γ signaling. Dubrot et al. demonstrated that IFN-γ enhances antigen presentation to CD8\u003csup\u003e+\u003c/sup\u003e T cells by upregulating MHC-I molecules while simultaneously inhibiting NK cell activation(\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Single-cell sequencing is required to elucidate the spatiotemporal-specific interaction network. Additionally, PB-NK cell counts progressively increased over time following surgery, underscoring the significance of standardized postoperative management, including antineoplastic therapy integrated with nutritional support, for promoting immune recovery. Moreover, the collinearity between treatment stage and time variables might stem from the consistency of the staged comprehensive treatment protocol for MPM patients post-surgery: within 1-month post-surgery, 92% of patients received only nutritional support; from 1 to 6 months post-surgery, 78% of patients underwent drug sensitivity-guided chemotherapy (e.g., capecitabine/oxaliplatin) combined with targeted therapy (apatinib); from 6 to 12 months post-surgery, 65% of patients received immunotherapy (PD-1/PD-L1 inhibitors) in conjunction with targeted therapy (apatinib).\u003c/p\u003e \u003cp\u003eThis study constituted a single-center retrospective analysis. The postoperative cohort had a relatively small sample size (n\u0026thinsp;=\u0026thinsp;64), and there was no evaluation of NK cell function, including degranulation activity and KIR expression profiles, as well as the characteristics of the microenvironment, such as the Treg/MDSC ratio. Future research should focus on multi-center prospective studies incorporating spatial transcriptome and single cell sequencing technologies to comprehensively analyze the heterogeneity of NK subsets and their dynamic interactions with CD8\u003csup\u003e+\u003c/sup\u003e T cells.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis study elucidated the dynamic changes in PB-NK cell levels among MPM patients and their clinical significance, demonstrated that CRS\u0026thinsp;+\u0026thinsp;HIPEC enhanced NK cell function through immune microenvironment remodeling, and established a predictive model for postoperative NK recovery. Moving forward, it is essential to integrate multi-omics approaches with prospective cohort studies to thoroughly investigate the heterogeneity of NK cell subsets and their spatiotemporal interaction networks, thereby providing precise regulatory targets for personalized immunotherapy.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Medical Ethics Committee of Beijing Shijitan Hospital (2015- [28]). All procedures performed in studies involving human participants were by the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The consent to participate was waived due to the retrospective nature of this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Beijing Municipal Administration of Hospitals’ Ascent Plan (DFL20180701).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceived and designed the analysis: Yi-Tong Liu, Yan Li.\u003c/p\u003e\n\u003cp\u003eThe data were collected from Yi-Tong Liu, Qi-Di Zhao, Xin-Li Liang, Yang Yu and Bing Li.\u003c/p\u003e\n\u003cp\u003eContributed data or analysis tools: Yi-Tong Liu, Ru Ma, Yan-Dong Su, Rui Yang, and Tian Wei.\u003c/p\u003e\n\u003cp\u003ePerformed the analysis: Yi-Tong Liu, Qi-Di Zhao, Xin-Li Liang,\u0026nbsp;He-Liang Wu, Yu-Bin Fu, Yu-Run Cui, Yang Yu and Bing Li.\u003c/p\u003e\n\u003cp\u003eWrote the paper: Yi-Tong Liu and Yan Li.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have stated no conflicts of interest in this research.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eD\u0026eacute;sage AL, Karpathiou G, Peoc'h M, Froudarakis ME. 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Eur J Surg Oncol. 2023;49(1):173\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePeritoneal Tumor Committee of Chinese anti-Cancer Association THCoCa-CA, Tumor Hyperthermia Committee of Beijing Cancer Prevention and Control Society. Chinese expert consensus on diagnosis and treatment of diffuse malignant peritoneal mesothelioma. Natl Med J China. 2021;101(36):2839\u0026ndash;49.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSu YD, Yang ZR, Li XB, Yu Y, Du XM, Li Y. Key factors for successful cytoreductive surgery plus hyperthermic intraperitoneal chemotherapy to treat diffuse malignant peritoneal mesothelioma: results from specialized peritoneal cancer center in China. Int J Hyperth. 2022;39(1):706\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiang XL, Su YD, Li XB, Fu YB, Ma R, Yang R, et al. 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Disruption of TGF-β signaling pathway is required to mediate effective killing of hepatocellular carcinoma by human iPSC-derived NK cells. Cell Stem Cell. 2024;31(9):1327-43.e5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBald T, Krummel MF, Smyth MJ, Barry KC. The NK cell-cancer cycle: advances and new challenges in NK cell-based immunotherapies. Nat Immunol. 2020;21(8):835\u0026ndash;47.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMao D, Zhou Z, Chen H, Liu X, Li D, Chen X, et al. Pleckstrin-2 promotes tumour immune escape from NK cells by activating the MT1-MMP-MICA signalling axis in gastric cancer. Cancer Lett. 2023;572:216351.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCLSI. Enumeration of Immunologically Defined Cell Populations by Flow Gvtometry; ApprovedGuideline-Second Edition. Wayne, PA: Clinical and Laboratory StandardsInstitute. 2007;27:CLSI document H42-A2.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCorreia AL, Guimaraes JC, Auf der Maur P, De Silva D, Trefny MP, Okamoto R, et al. Hepatic stellate cells suppress NK cell-sustained breast cancer dormancy. Nature. 2021;594(7864):566\u0026ndash;71.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWei H, Suo C, Gu X, Shen S, Lin K, Zhu C et al. AKR1D1 suppresses liver cancer progression by promoting bile acid metabolism-mediated NK cell cytotoxicity. Cell Metab. 2025.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiao W, Lin JX, Leonard WJ. Interleukin-2 at the crossroads of effector responses, tolerance, and immunotherapy. Immunity. 2013;38(1):13\u0026ndash;25.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTerr\u0026eacute;n I, Orrantia A, Mosteiro A, Vitall\u0026eacute; J, Zenarruzabeitia O, Borrego F. Metabolic changes of Interleukin-12/15/18-stimulated human NK cells. Sci Rep. 2021;11(1):6472.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi Z, Chen L, Qin Z. Paradoxical roles of IL-4 in tumor immunity. Cell Mol Immunol. 2009;6(6):415\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi W, Che X, Chen X, Zhou M, Luo X, Liu T. Study of calcitriol anti-aging effects on human natural killer cells in vitro. Bioengineered. 2021;12(1):6844\u0026ndash;54.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLin M, Luo H, Liang S, Chen J, Liu A, Niu L, et al. Pembrolizumab plus allogeneic NK cells in advanced non-small cell lung cancer patients. J Clin Invest. 2020;130(5):2560\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAl Omar S, Flanagan BF, Almehmadi M, Christmas SE. The effects of IL-17 upon human natural killer cells. Cytokine. 2013;62(1):123\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDubrot J, Du PP, Lane-Reticker SK, Kessler EA, Muscato AJ, Mehta A, et al. In vivo CRISPR screens reveal the landscape of immune evasion pathways across cancer. Nat Immunol. 2022;23(10):1495\u0026ndash;506.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"world-journal-of-surgical-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"wjso","sideBox":"Learn more about [World Journal of Surgical Oncology](http://wjso.biomedcentral.com)","snPcode":"12957","submissionUrl":"https://submission.nature.com/new-submission/12957/3","title":"World Journal of Surgical Oncology","twitterHandle":"@OncoBioMed","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"malignant peritoneal mesothelioma, natural killer cells, cytoreductive surgery, tumor microenvironment","lastPublishedDoi":"10.21203/rs.3.rs-6288852/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6288852/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eMalignant peritoneal mesothelioma (MPM) is a highly aggressive peritoneal malignancy with a significant recurrence rate following cytoreductive surgery (CRS) combined with hyperthermic intraperitoneal chemotherapy (HIPEC). Thus, there is an urgent need to investigate novel therapeutic strategies for MPM. Natural killer (NK) cells exhibit rapid responsiveness in anti-tumor immunity; however, NK cells' dynamic evolution and clinical significance in MPM remain unclear.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eThis study retrospectively enrolled 80 newly diagnosed MPM patients (preoperative group) and 64 patients who underwent CRS+HIPEC (postoperative group). The frequency of NK cells (CD3\u003csup\u003e-\u003c/sup\u003eCD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e+\u003c/sup\u003e) in peripheral blood was quantified using flow cytometry. Univariate and multivariate regression analyses were performed to evaluate the association between NK cell counts and clinicopathological characteristics, intraoperative events, and prognosis. A multivariate prediction model for NK cell recovery was established.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Preoperative NK cell reduction was observed in 41 patients (51.3%), and this phenomenon was significantly associated with preoperative thrombosis (\u003cem\u003eP\u003c/em\u003e = 0.023), a high intraoperative plasma infusion volume (\u003cem\u003eP\u003c/em\u003e = 0.004), prolonged hospital stay (\u003cem\u003eP\u003c/em\u003e = 0.023), decreased total lymphocyte count (\u003cem\u003eP\u003c/em\u003e = 0.011), and an elevated CD4\u003csup\u003e+\u003c/sup\u003e/CD8\u003csup\u003e+\u003c/sup\u003eT cell ratio (\u003cem\u003eP\u003c/em\u003e = 0.018). The median NK cell count increased significantly to 278 cells/μL postoperatively. Postoperative NK cell reduction occurred in 20 cases (31.3%), which was independently correlated with lower Karnofsky performance scale (KPS) scores (\u003cem\u003eP\u003c/em\u003e = 0.048), and higher expression levels of interleukins IL-4 (\u003cem\u003eP\u003c/em\u003e = 0.020), IL-5 (\u003cem\u003eP\u003c/em\u003e = 0.007), IL-6 (\u003cem\u003eP\u003c/em\u003e = 0.016), and IL-8 (\u003cem\u003eP\u003c/em\u003e = 0.018). Elevated levels of IL-2 (\u003cem\u003eP\u003c/em\u003e = 0.019) and IL-4 (\u003cem\u003eP\u003c/em\u003e = 0.007) were identified as independent factors contributing to NK cell depletion following surgery. Survival analysis revealed that a high perioperative stress score (PSS) (\u003cem\u003eP\u003c/em\u003e = 0.015), lymph node metastasis (\u003cem\u003eP\u003c/em\u003e = 0.015), intraoperative blood loss (\u003cem\u003eP\u003c/em\u003e = 0.013), low preoperative CD8⁺T cell levels (\u003cem\u003eP\u003c/em\u003e = 0.001), and low postoperative IL-17 expression levels (\u003cem\u003eP\u003c/em\u003e = 0.013) were independent adverse predictors of overall survival (OS). Patients with higher preoperative NK cell levels exhibited a tendency toward longer OS. Furthermore, the dynamic NK recovery model demonstrated that baseline NK cell levels (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), peritoneal cancer index (PCI) (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), CD8⁺T cell status (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), and postoperative recovery time (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001) all influenced the immune remodeling process.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eThis study represents the first systematic investigation into the spatiotemporal dynamic characteristics of NK cells in MPM patients. More than half of MPM patients experienced preoperative NK cell depletion, which CRS+HIPEC could effectively reverse. The NK cell count may serve as a dynamic biomarker for tumor burden and immunosuppressive microenvironment assessment, with its preoperative elevation potentially improving prognosis. Targeting the IL-2/IL-4 pathway alone or in combination with CD8⁺ T cells may offer a novel strategy for MPM immunotherapy.\u003c/p\u003e","manuscriptTitle":"Dynamic evolution of NK cells and immune remodeling mediated by CRS+HIPEC: prognostic mechanisms and therapeutic implications for malignant peritoneal mesothelioma","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-21 08:46:04","doi":"10.21203/rs.3.rs-6288852/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-07-10T15:23:40+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-08T19:40:25+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-07T13:22:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"133354909726124280945059234075520346933","date":"2025-07-07T11:08:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"50089856214707255490501354963185961976","date":"2025-07-01T09:25:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"267572422741794340612628823581314562357","date":"2025-06-30T02:31:56+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-23T13:09:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"336274696786060616336878152998630472189","date":"2025-06-17T11:58:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"4361582701453954064766695730299782382","date":"2025-06-13T16:18:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"5852607903420442301464164689442745989","date":"2025-04-26T18:23:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"299999599991993037235171193627228893777","date":"2025-04-24T16:18:19+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-03-29T17:12:11+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-03-29T04:50:14+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-24T01:32:22+00:00","index":"","fulltext":""},{"type":"submitted","content":"World Journal of Surgical Oncology","date":"2025-03-23T14:29:19+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"world-journal-of-surgical-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"wjso","sideBox":"Learn more about [World Journal of Surgical Oncology](http://wjso.biomedcentral.com)","snPcode":"12957","submissionUrl":"https://submission.nature.com/new-submission/12957/3","title":"World Journal of Surgical Oncology","twitterHandle":"@OncoBioMed","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5e48b04a-3602-47cb-b0ea-90f55a28e65f","owner":[],"postedDate":"April 21st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-11-10T16:03:30+00:00","versionOfRecord":{"articleIdentity":"rs-6288852","link":"https://doi.org/10.1186/s12957-025-04019-2","journal":{"identity":"world-journal-of-surgical-oncology","isVorOnly":false,"title":"World Journal of Surgical Oncology"},"publishedOn":"2025-11-03 15:58:08","publishedOnDateReadable":"November 3rd, 2025"},"versionCreatedAt":"2025-04-21 08:46:04","video":"","vorDoi":"10.1186/s12957-025-04019-2","vorDoiUrl":"https://doi.org/10.1186/s12957-025-04019-2","workflowStages":[]},"version":"v1","identity":"rs-6288852","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6288852","identity":"rs-6288852","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}