Impact of Helicobacter pylori infection on neoadjuvant chemotherapy in locally advanced gastric cancer: a retrospective analysis

Impact of Helicobacter pylori infection on neoadjuvant chemotherapy in locally advanced gastric cancer: a retrospective analysis | 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 Impact of Helicobacter pylori infection on neoadjuvant chemotherapy in locally advanced gastric cancer: a retrospective analysis Bin Zhong, Zhizhong Xiong, Jiabo Zheng, Saddam Ahmed Mohamed, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4760812/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 27 Jan, 2025 Read the published version in BMC Cancer → Version 1 posted 13 You are reading this latest preprint version Abstract Background Helicobacter pylori ( H. pylori ) infection may affect the efficacy of immunotherapy and adjuvant chemotherapy in gastric cancer patients. However, the role of H. pylori infection in neoadjuvant chemotherapy in patients with locally advanced gastric cancer (LAGC) remains unclear. This study investigated the effect of H. pylori infection on neoadjuvant chemotherapy and prognosis of patients with LAGC. Methods This retrospective study utilized data from patients with LAGC who underwent neoadjuvant chemotherapy and surgical treatment at the Sixth Affiliated Hospital of Sun Yat-sen University from January 1, 2010, to January 31, 2021. Patients were grouped according to their H. pylori infection status. The responses of the two groups to neoadjuvant chemotherapy and oncological outcomes were then compared. Results A total of 239 patients were included in the analysis, and the baseline characteristics of the H. pylori -positive (n = 51) and H. pylori -negative (n = 188) groups were comparable. Further analysis revealed that H. pylori infection was significantly associated with the major pathological response ( P = 0.009). Multivariate analysis showed that factors related to major pathological response included; age ≤ 50 (OR: 0.423, 95% CI: 0.194–0.925), H. pylori infection (OR: 0.396, 95% CI: 0.183–0.854), pathological stage T 3/4 (OR: 0.524, 95% CI: 0.288–0.954), and CA125 > 35 U/mL (OR: 0.345, 95% CI: 0.132–0.904). Both overall survival (OS) and disease-free survival (DFS) rates were poorer in the H. pylori -positive group than in the H. pylori -negative group (OS: Log-Rank P = 0.035; DFS: Log-Rank P = 0.029). Conclusion This cohort study indicated that H. pylori infection may be associated with tumor response to neoadjuvant chemotherapy and survival outcomes in patients with LAGC. Locally advanced gastric cancer Helicobacter pylori Neoadjuvant chemotherapy effect Prognosis Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Gastric cancer (GC) is the fifth most common cancer and the fourth leading cause of cancer-related deaths globally, making it a significant health concern [ 1 ]. In China, 70%-80% of GC patients are in a locally advanced stage at the time of diagnosis, and their 5-year OS rate after radical surgery remains below 50% [ 2 , 3 ]. Since the MAGIC study [ 4 ] established the significance of neoadjuvant chemotherapy in the treatment of locally advanced gastric cancer (LAGC), with subsequent studies such as the PRODIGY [ 5 ] and RESOLVE [ 6 ] trials, it has been further demonstrated that neoadjuvant chemotherapy can increase the R0 resection rate and improve the prognosis of patients with LAGC, making neoadjuvant chemotherapy the focus of the treatment of LAGC. According to previous studies, the proportion of patients with LAGC achieving tumor regression grade (TRG) 0–1 is approximately 11%-24% [ 6 – 8 ], indicating room for significant improvement. Statistics have shown that, from 2015 to 2022, the global adult infection rate of Helicobacter pylori ( H. pylori ) was approximately 43.9%, making it the principal etiological agent for GC [ 9 ]. Previous studies have shown that H. pylori can reduce the sensitivity of GC cells to chemotherapeutic drugs by up-regulating cellular glucose metabolism through the secretion of CagA protein and by affecting the receptor tyrosine kinase process [ 10 , 11 ]. Recent retrospective studies have shown that H. pylori infection decreases the efficacy of tumor immunotherapy [ 12 ] and that H. pylori eradication after surgery improves both the efficacy and prognosis of adjuvant chemotherapy in patients with LAGC [ 13 , 14 ]. However, the effect of H. pylori infection on neoadjuvant chemotherapy in patients with LAGC remains unclear. In this study, we aimed to explore whether H. pylori infection affects the outcome of neoadjuvant chemotherapy in patients with LAGC, complementing the results of previous studies. Methods Patients We retrospectively collected medical data of patients with GC who underwent radical surgery at the Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, China, between 1, January, 2010, and 31, January, 2021. As shown in Fig. 1 , patients diagnosed with gastric adenocarcinoma or esophagogastric junction adenocarcinoma who underwent R0 resection and D2 lymphadenectomy were included in the cohort study. Patients with pathological diagnoses of stage I or IV had residual gastric cancer, did not receive 3–4 cycles of neoadjuvant chemotherapy, had incomplete clinicopathological data, missing follow-up information, had no information on H. pylori infection status, and received anti- H. pylori treatment during neoadjuvant chemotherapy was excluded. Pathological staging was evaluated according to the eighth edition of the American Joint Committee on Cancer’s Cancer Staging Manual [ 15 ], including the tumor depth of invasion and extent of resection, among other factors. Patients were categorized into H. pylori -positive and H. pylori -negative groups according to their H. pylori infection status before the time of their first neoadjuvant treatment. All patients in this retrospective cohort provided written informed consent for the anonymous collection and analysis of clinical data. This study was conducted under the Declaration of Helsinki [ 16 ] and approved by the Review Board of the Sixth Affiliated Hospital of Sun Yat-sen University. The reporting of this study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline [ 17 ]. Evaluation of H. pylori infection status The H. pylori infection status was determined using the 13C urea breath test and/or histological examination of gastric tissue (Giemsa or immunohistochemical staining) before the first regimen of neoadjuvant chemotherapy. A positive result was obtained for either test diagnosed H. pylori infection. Patients with negative test results were classified into the H. pylori -negative group, whereas the H. pylori-positive group was classified as positive. Outcome Tumor pathological response was scored according to TRG [ 18 ], where TRG 0 represents complete remission (no residual cancer cells), TRG 1indicates significant remission (residual lesions 50% residual lesions). The primary endpoint in this study was the major pathological response (MPR), defined as a TRG score of 0–1. The secondary study endpoints included pathological complete response (PCR), defined as TRG 0; OS, defined as the time from the date of surgery to the date of death from any cause; and disease-free survival (DFS), defined as the time from the date of surgery to recurrence, or death, whichever occured first. Data collection and conversion This study incorporated the following clinical and pathological indicators: age, sex, family history of cancer, body mass index (BMI), histological differentiation, TRG, Lauren classification, pathological T stage, pathological N stage, TNM staging, tumor location, neoadjuvant chemotherapy regimen, Her2 status, Mismatch Repair (MMR) status, preoperative hemoglobin, preoperative albumin, preoperative white blood cells, preoperative platelets, carcinoembryonic antigen (CEA), cancer antigen 199 (CA199), cancer antigen 125 (CA125), cancer antigen 153(CA153), and alpha-fetoprotein (AFP). TRG, histological differentiation, Lauren classification, depth of tumor invasion, lymph node metastasis, TNM stage, tumor location, Her2, and MMR were determined based on postoperative pathological results. Preoperative hematological parameters were based on blood test performed immediately before their first neoadjuvant chemotherapy. Age was categorized into three groups: early onset (≤ 50 years), average age group (51–64 years), and late-onset group (≥ 65 years); According to their calculated BMI, the patients were classified as underweight (BMI less than 18.5 kg/m 2 ), normal weight (BMI 18.5–24 kg/m 2 ), or overweight/obese (≥ 24 kg/m 2 ). Blood biochemical parameters and tumor marker levels were grouped according to abnormal values of the hospital tests. Patients were followed up every 3 months during the first 2 years, every 6 months from 2 to 5 years, and then annually. Follow-up data were retrieved from the follow-up data center of our hospital on 30 June 2022. Statistical analysis The basic characteristics of patients were compared between the H. pylori -positive and H. pylori -negative groups using either the chi-squared test or two-tailed Fisher’s exact test for categorical variables. Univariate and multivariate logistic regression analyses were used to identify the independent risk factors for determining the efficacy of neoadjuvant chemotherapy in patients with LAGC. The area under the receiver operating characteristic (ROC) curve and Wald test were used to evaluate the importance of factors affecting neoadjuvant therapy. Survival curves were calculated using the Kaplan-Meier method. The forest plots were generated according to the Cox regression analysis results, using the "survival" and "survminer" packages. The "mediation" package was utilized for analyzing mediation effects. All statistical tests were two-sided, with significance set at P < 0.05. All analyses were performed using the R software (version 4.3.1; R Foundation for Statistical Computing). Results Patient characteristics According to the inclusion and exclusion criteria, 239 patients were included in the analysis (median [IQR] age, 60 years; 178 [74.5%] male and 61 [25.5%] female). There were 51 H. pylori -positive patients and 188 H. pylori -negative patients. A summary of the patient's characteristics is presented in Table 1. Overall, the baseline patient characteristics were consistent. There were no significant differences in sex, age, BMI, TNM stage, CPR, neoadjuvant chemotherapy regimen, tumor location, histological differentiation, blood biochemical indicators and tumor marker levels between the two groups. However, compared with the H. pylori -negative group, the rate of MPR in the H. pylori -positive group was lower (74/188[39.4%] VS 10/51[19.6%]; P = 0.009), and the proportion of patients with a family history of cancer was higher (5/188[2.7%] vs 5/51[9.8%]; P = 0.024). Table 1. Patient demographic, clinical, and pathological characteristics Characteristic H. pylori -negative N=188 H. pylori -posititve N=51 p Age (years) (%) 0.510 ≤50 39 (20.7) 14 (27.5) 51-64 96 (51.1) 22 (43.1) ≥65 53 (28.2) 15 (29.4) Sex (%) 0.146 male 136 (72.3) 42(82.4) female 52 (27.7) 9 (17.6) Family history of cancer(%) 0.024 no 183 (97.3) 46 (90.2) yes 5 (2.7) 5 (9.8) BMI (kg/m 2 ) (%) 0.085 18.5-24 29 (15.4) 2 (3.9) ＜18.5 118 (62.8) 38 (74.5) ≥24 41 (21.8) 11 (21.6) TRG (%) 0.076 0 36 (19.1) 5 (9.8) 1 38 (20.2) 5 (9.8) 2 94 (50.0) 34 (66.7) 3 20 (10.6) 7 (13.7) MPR（TRG:0/1） (%) 0.009 no 114 (60.6) 41 (80.4) yes 74 (39.4) 10 (19.6) CPR（TRG:0） (%) 0.116 no 152 (80.9) 46 (90.2) yes 36 (19.1) 5 (9.8) Pathological T stage 0.942 T1/2 119 (63.3) 32 (62.7) T3/4 69 (36.7) 19 (37.3) Pathological N stage 0.398 N (−) 101 (53.7) 24 (47.1) N (+) 87 (46.3) 27 (52.9) TNM Stage (%) 0.822 II 111(59.0) 31(60.8) III 77(41.0) 20(39.2) Albumin (g/L) (%) 0.495 40-55 61 (32.4) 14 (27.5) ＜40 127 (67.6) 37 (72.5) Hemoglobin (g/L) (%) 0.657 120-160 53 (28.2) 16 (31.4) ＜120 135 (71.8) 35 (68.6) Platelet (10 9 /L) (%) 0.648 100-300 142 (75.5) 37 (72.5) ＜100 22 (11.7) 5 (9.8) ＞300 24 (12.8) 9 (17.6) Leucocyte (10 9 /L) (%) 0.303 4-10 128 (68.1) 29 (56.9) ＜4 38 (20.2) 13 (25.5) ＞10 22 (11.7) 9 (17.6) CEA (ng/L) (%) 0.256 0-5 147 (78.2) 36 (70.6) ＞5 41 (21.8) 15 (29.4) CA199 (U/mL) (%) 0.216 0-37 167 (88.8) 42 (82.4) ＞37 21 (11.2) 9 (17.6) CA125 (U/mL) (%) 0.597 0-35 163 (87.2) 43 (84.3) 35 24 (12.8) 8 (15.7) CA153 (U/mL) (%) 0.777 0-32.4 183 (97.3) 50 (98.0) ＞32.4 5 (2.7) 1 (2.0) AFP (ng/L) (%) 0.446 0-8.78 166 (88.3) 43 (84.3) ＞8.78 22 (11.7) 8 (15.7) Her2 (%) 0.328 negative 125 (66.5) 39 (76.5) positive 33 (17.6) 5 (9.8) unknow 30 (16.0) 7 (13.7) MMR (%) 0.209 pMMR 114 (60.6) 37 (72.5) dMMR 9 (4.8) 3 (5.9) unknow 65 (34.6) 11 (21.6) Chemotherapy regimen(%) 0.945 SOX 62 (33.0) 15 (29.4) DOF 58 (30.9) 17 (33.3) FLOT 30 (16.0) 7 (13.7) XELOX 13 (6.9) 3 (5.9) FOLFOX 16 (8.5) 5 (9.8) Other 9 (4.8) 4 (7.8) Lauren(%) 0.099 intestine type 65 (34.6) 26 (51.0) diffused type 76 (40.4) 16 (31.4) mixed type 47 (25.0) 9 (17.6) Tumor location (%) 0.891 esophagogastric junction 47 (25.1) 10 (19.6) upper 18 (9.6) 4 (7.8) middle 47 (25.1) 13 (25.5) lower 75 (40.1) 24 (47.1) Differentiation (%) 0.394 well differentiated 9 (4.8) 5 (9.8) moderately differentiated 100 (53.2) 25 (49.0) poorly differentiated 79 (42.0) 21 (41.2) Abbreviations: BMI, body mass index; TRG, tumor regression grade; MPR, major pathological response; CPR, pathological complete response; CEA, carcinoembryonic antigen; CA199, cancer antigen 199; CA125, cancer antigen 125; CA153, cancer antigen 153; AFP, alpha-fetoprotein; pMMR, proficient Mismatch Repair; dMMR, deficient Mismatch Repair.Abbreviations: BMI, body mass index; TRG, tumor regression grade; MPR, major pathological response; CPR, pathological complete response; CEA, carcinoembryonic antigen; CA199, cancer antigen 199; CA125, cancer antigen 125; CA153, cancer antigen 153; AFP, alpha-fetoprotein; pMMR, proficient Mismatch Repair; dMMR, deficient Mismatch Repair. Univariate and multivariate analyses of factors influencing neoadjuvant therapy effectiveness The results of univariate and multivariate analyses to determine the variables associated with MPR are presented in Table 2 . The univariate analysis comprised 20 variables, and the results indicated that age≤50 years (OR: 0.328, 95% CI: 0.179-0.816, P = 0.013), H. pylori positivity (OR: 0.376, 95% CI: 0.177-0.796, P = 0.011), Pathological T 3/4 (OR: 0.522, 95% CI: 0.293-0.929, P = 0.027), CA125＞35U/ml (OR: 0.387, 95% CI: 0.152-0.981, P = 0.046) were associated with MPR. Variables with P < 0.05 in the univariate analysis and factors from previous studies that may influence neoadjuvant chemotherapy were included in the multivariate analysis. The results showed that LAGC patients aged ≤50 years (OR: 0.423, 95% CI: 0.194-0.925, P = 0.031), H. pylori -positive (OR: 0.396, 95% CI: 0.183-0.854, P = 0.018), T3/4 (OR: 0.524, 95% CI: 0.288-0.954, P = 0.035) and CA125 >35U/ml (OR: 0.345, 95% CI: 0.132-0.904, P = 0.030) were less likely to achieve MPR. Table 2. Uni- and multivariate analysis of influencing factors of MPR Variables Univariate analysis Multivariate analysis OR（95% CI） P OR（95% CI） P Age (y) 51-64 ref. ref. ≤50 0.382(0.179-0.816) 0.013 0.423(0.194-0.925) 0.031 ≥ 65 0.848(0.459-1.568) 0.599 0.953(0.501-1.811) 0.883 Sex male ref. female 0.710(0.379-1.332) 0.286 Family history no ref. yes 2.904 (0.796-10.595) 0.106 H. pylori negative ref. ref. positive 0.376(0.177-0.796) 0.011 0.396(0.183-0.854) 0.018 BMI (kg/m 2 ) ≥24 ref. ＜18.5 1.558(0.609-3.985) 0.355 18.5-24 1.420(0.718-2.811) 0.314 Pathological T stage T1/2 ref. ref. T3/4 0.522(0.293-0.929) 0.027 0.524(0.288-0.954) 0.035 Pathological N stage N (−) ref. N (+) 0.859(0.504-1.463) 0.575 Differentiation well ref. poor 1.367(0.399-4.680) 0.618 moderate 1.406(0.417-4.743) 0.583 Lauren mixed type ref. intestine type 1.792(0.878-3.660) 0.109 diffused type 1.210(0.586-2.499) 0.607 Tumor location esophagogastric junction ref. lower 0.935(0.478-1.827) 0.844 middle 0.881(0.416-1.866) 0.741 upper 0.481(0.156-1.489) 0.204 Albumin (g/L) 40-55 ref. ＜40 1.031(0.581-1.829) 0.916 Hemoglobin (g/L) 120-160 ref. ＜120 0.856(0.479-1.531) 0.601 CEA (ng/L) 0-5 ref. ＞5 0.755(0.396-1.437) 0.392 CA199 (U/mL) 0-37 ref. ＞37 0.912(0.406-2.051) 0.824 CA125 (U/mL) 0-35 ref. ref. ＞35 0.387(0.152 -0.981) 0.046 0.345(0.132-0.904) 0.030 CA153 (U/mL) 0-32.4 ref. ＞32.4 0.921(0.165-5.134) 0.925 AFP (ng/L) 0-8.78 ref. ＞8.78 1.269(0.579-2.779) 0.552 Chemotherapy regimen Other ref. SOX 0.769(0.228-2.592) 0.672 DOF 1.127(0.337-3.773) 0.846 FLOT 0.677(0.181-2.537) 0.563 XELOX 0.960(0.213-4.335) 0.958 FOLFOX 0.640(0.148-2.768) 0.550 Her2 negative ref. posititve 0.590(0.288-1.210) 0.150 MMR pMMR ref. dMMR 0.673(0.203-2.227) 0.516 Abbreviations: BMI, body mass index; Hp , Helicobacter pylori ; CEA, carcinoembryonic antigen; CA199, cancer antigen 199; CA125, cancer antigen 125; CA153, cancer antigen 153; AFP, alpha-fetoprotein; pMMR, proficient Mismatch Repair; dMMR, deficient Mismatch Repair. Assessment of the importance of factors influencing neoadjuvant therapy To further explore the importance of the influencing factors of neoadjuvant chemotherapy in LAGC patients, we subjected the variables with P < 0.05 in the multivariate analysis to ROC curve analysis ( Figure 2A ) and found that H. pylori infection accounted for the highest area under the curve. We also utilized the Wald test to determine the importance of each influencing factor and found that H. pylori infection was at the top of the list of factors influencing MPR ( Figure 2B ). These findings indicate that H. pylori infection significantly influences the MPR, as indicated by both tests. Influence of Helicobacter pylori infection on prognosis We performed a survival analysis to compare the OS of the H. pylori -positive and H. pylori -negative groups ( Figure 3A ). The results showed a statistically significant difference in OS between the two groups ( P = 0.035). Subsequently, the DFS of the two groups was evaluated, and as shown in Figure 3B , there was a significant DFS advantage in the H. pylori -negative group compared to the H. pylori -positive group ( P = 0.029). Cox regression analysis In univariate analysis, TRG 0 (OS, OR: 0.242, 95% CI: 0.068-0.857, P = 0.028; DFS, OR: 0.248, 95% CI: 0.103-0.594, P = 0.002), as well as lower tumor location (OS, OR: 0.488, 95% CI: 0.248-0.960, P = 0.038; DFS, OR: 0.492, 95% CI: 0.278-0.869, P = 0.015), were protective factors for OS as well as DFS, while H. pylori -positive (OS, OR: 1.845, 95% CI: 1.033-3.293, P = 0.038; DFS, OR: 1.686, 95% CI: 1.049-2.712, P = 0.031) was a risk factor for OS as well as DFS ( Supplementary Table 1 ). In the multivariate Cox analysis, we found that TRG was an independent risk factor for OS (TRG 2, OR: 3.38, 95% CI: 1.28-8.93, P = 0.014; TRG 3, OR: 3.32, 95% CI: 0.90-12.19, P = 0.071). Lower tumor location was an independent protective factor for OS (OR: 0.48, 95% CI: 0.23-0.99, P = 0.0461) ( Figure 4 ). Similar findings were observed in the DFS analysis. However, interestingly, H. pylori was not significant in the multivariate analysis, in conjunction with the previous results, we hypothesized that H. pylori may affect the OS and DFS of patients by influencing TRG, so we further performed a mediated effect analysis regarding H. pylori and TRG, and the results showed that H. pylori could affect the prognosis of patients by influencing TRG ( Supplementary Figure 1A, B ). Discussion This study presents an exploratory analysis of the influence of H. pylori infection on the efficacy and prognosis of neoadjuvant chemotherapy in patients with LAGC. This study provides a basis for further exploration of the role of H. pylori eradication in neoadjuvant chemotherapy. Our study found that H. pylori infection was significantly associated with MPR rates and that H. pylori -positive patients had a worse prognosis among LAGC patients undergoing neoadjuvant chemotherapy. Multivariate logistic regression analysis was performed to explore the factors affecting MPR. H. pylori -positive, higher T-stage, younger age, and CA125 abnormalities were associated with non-MPR. In this study, H. pylori infection exhibited a more substantial influence than other factors. Furthermore, multivariate Cox regression and mediation effect analyses suggested that H. pylori may influence patient prognosis through its impact on TRG. The global prevalence of H. pylori infection is about 50% [19]. H. pylori infection is one of the major risk factors for gastric cancer development, increasing the risk of developing gastric cancer approximately threefold [20]. Chemotherapy plays a pivotal role in the comprehensive treatment of gastric cancer, significantly contributing to improving the prognosis and quality of life of patients with gastric cancer.. However, whether H. pylori affects the effect of chemotherapy remains unclear. It has been reported that CagA protein secreted by H. pylori is positively correlated with 5-fluorouracil resistance in gastric cancer, and that CagA protein reduces the sensitivity of gastric cancer cells to 5-fluorouracil by upregulating cellular glucose metabolism [10, 21]. Simultaneously, H. pylori can affect the receptor tyrosine kinase process in tumors, which in turn affects resistance to platinum and fluorouracil chemotherapy [11]. However, H. pylori has also been shown to increase the sensitivity of gastric cancer cells to cisplatin by downregulating miR-141 [22]. Contradictory results have been reported in clinical studies. A retrospective study by Zhao et al. [14] found that in TNM stage II/III patients receiving adjuvant chemotherapy, H. pylori eradication therapy was strongly associated with a survival benefit (OS: HR, 0.49; 95%CI: 0.24-0.99, P = 0.046), whereas in patients who did not receive adjuvant chemotherapy, anti- H. pylori therapy was not associated with survival benefit (OS: HR, 0.29; 95% CI: 0.04-2.08; P = 0.22). In a meta-analysis that included four studies, it was found that among those who received immunotherapy, those who were positive for H. pylori infection had lower OS and PFS rates than those who were H. pylori -negative, suggesting that H. pylori infection reduces the efficacy of tumor immunotherapy [12]. However, in advanced gastric cancer or metastatic gastric cancer, Choi et al. [23] found that patients with concomitant H. pylori infection responded better to chemotherapy than those without H. pylori infection. Additionally, the results of Nishizuka et al. [24] suggested that H. pylori infection is associated with a favorable prognosis in patients with advanced gastric cancer receiving S-1-adjuvant chemotherapy. An article that included patients with TNM stage III gastric cancer who received adjuvant chemotherapy after radical resection analyzed H. pylori infection and its association with clinical outcome. The results showed that H. pylori infection status did not affect either OS or DFS. However, this study had several limitations. First, only 16 H. pylori -positive patients were included. Second, information on whether neoadjuvant chemotherapy was administered is unknown and the follow-up period was not sufficiently long. To the best of our knowledge, studies exploring this topic remain relatively scarce, warranting further investigation to substantiate these findings. Our study complements this field by including patients who underwent neoadjuvant chemotherapy in TNM stage II/III, innovatively analyzing the impact of H. pylori infection on neoadjuvant treatment outcomes, and providing an in-depth analysis of the factors that contribute to neoadjuvant treatment outcomes and prognosis. Our study found that patients with H. pylori infection and abnormal CA125 levels may not benefit from neoadjuvant chemotherapy, whereas patients with low T-stage and older patients are more likely to benefit from neoadjuvant chemotherapy, which is in line with some of the results of previous studies. However, tumor site, histologic differentiation, and Lauren classification, which were mentioned in previous studies as possible influencers of neoadjuvant chemotherapy efficacy, did not consistently emerge as significantly in our study [25-27]. Meanwhile, the analysis of H. pylori infection as a variable was not addressed in previous studies. Therefore, further multicenter data are needed to verify the reliability of this conclusion. An interesting observation found in our study was that when both H. pylori and TRG were included in the Cox regression analysis, the effect of H. pylori on patient prognosis seemed to diminish. This suggests that H. pylori may affect the survival prognosis of patients through the mediating variable of TRG, and we subsequently verified this speculation by mediation effect analysis. We anticipate that as more relevant studies emerge to improve our understanding of the relationship between H. pylori infection and chemotherapy for gastric cancer, more effective treatment strategies will be available for GC patients with concomitant H. pylori infection. Our study has several limitations. First, none of the H. pylori -positive patients at our center received H. pylori eradication therapy. If additional patients who underwent H. pylori eradication during neoadjuvant chemotherapy could be included in the analysis, a more comprehensive exploration of the impact of H. pylori eradication on the outcome of neoadjuvant chemotherapy could be performed. Therefore, we plan to conduct a prospective study to explore the impact of H. pylori eradication in neoadjuvant chemotherapy on patient outcomes. Second, this was a single-center clinical retrospective study, which may be subject to selection bias. Finally, owing to the extended period of the study, variations in patients' surgical and postoperative treatments might have occurred with changes in treatment concepts. Conclusion In conclusion, our study suggests that in patients with LAGC, H. pylori infection may impede the efficacy of neoadjuvant chemotherapy, thereby affecting patient prognosis. More data are needed to support this conclusion through an in-depth validation and exploring the impact of H. pylori eradication on neoadjuvant chemotherapy is also warranted. Abbreviations AFP: Alpha-fetoprotein BMI: Body mass index CEA: Carcinoembryonic antigen CA199: Cancer antigen 199 CA125: Cancer antigen 125 CA153: Cancer antigen 153 CI: Confidence Internal DFS: Disease-free survival dMMR: deficient Mismatch Repair GC: Gastric cancer H. pylori : Helicobacter pylori LAGC: Locally advanced gastric cancer MPR: Major pathological response MMR: Mismatch repair OS: Overall survival OR: Odds Ratio pMMR: proficient Mismatch Repair PCR: Pathological complete response ROC: Receiver operating characteristics curve STROBE: Strengthening the Reporting of Observational Studies in Epidemiology TRG: Tumor regression grade Declarations Author contributions Conceptualization: LL, JP; Methodology: LL, HW; Formal analysis and investigation: ZX, JG; Writing-original draft preparation: BZ; Writing review and editing: LL, JZ, ZX, SM; Funding acquisition: LL; Resources: LL; Supervision: LL; Data curation: BZ, ZX, JS; Software: DH, BZ; Visualization: ZD, JZ, SM. Project administration: LL. Availability of data and materials The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Funding This study was supported by the National Natural Science Foundation of China (grant nos. 82070684), and the Guangdong Natural Science Fund for Outstanding Youth Scholars (grant no. 2020B151502005). Ethics approval and consent to participate This retrospective study was approved by the Medical Research Ethics Committee of the Sixth Affiliated Hospital of Sun Yat-sen University. This study was conducted in compliance with the Helsinki Declaration. All included patients aged more than 18 years and written informed consent for anonymous collection and analysis of clinical data was provided by all patients before surgery in this retrospective cohort. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. References Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021;71(3):209-49. Liu D, Lu M, Li J, Yang Z, Feng Q, Zhou M, et al. The patterns and timing of recurrence after curative resection for gastric cancer in China. World journal of surgical oncology. 2016;14(1):305. Wang H, Guo W, Hu Y, Mou T, Zhao L, Chen H, et al. Superiority of the 8th edition of the TNM staging system for predicting overall survival in gastric cancer: Comparative analysis of the 7th and 8th editions in a monoinstitutional cohort. Molecular and clinical oncology. 2018;9(4):423-31. Cunningham D, Allum WH, Stenning SP, Thompson JN, Van de Velde CJ, Nicolson M, et al. Perioperative chemotherapy versus surgery alone for resectable gastroesophageal cancer. N Engl J Med. 2006;355(1):11-20. Kang YK, Yook JH, Park YK, Lee JS, Kim YW, Kim JY, et al. PRODIGY: A Phase III Study of Neoadjuvant Docetaxel, Oxaliplatin, and S-1 Plus Surgery and Adjuvant S-1 Versus Surgery and Adjuvant S-1 for Resectable Advanced Gastric Cancer. Journal of clinical oncology : official journal of the American Society of Clinical Oncology. 2021;39(26):2903-13. Zhang X, Liang H, Li Z, Xue Y, Wang Y, Zhou Z, et al. Perioperative or postoperative adjuvant oxaliplatin with S-1 versus adjuvant oxaliplatin with capecitabine in patients with locally advanced gastric or gastro-oesophageal junction adenocarcinoma undergoing D2 gastrectomy (RESOLVE): an open-label, superiority and non-inferiority, phase 3 randomised controlled trial. The Lancet Oncology. 2021;22(8):1081-92. Jiang Z, Xie Y, Zhang W, Du C, Zhong Y, Zhu Y, et al. Perioperative chemotherapy with docetaxel plus oxaliplatin and S-1 (DOS) versus oxaliplatin plus S-1 (SOX) for the treatment of locally advanced gastric or gastro-esophageal junction adenocarcinoma (MATCH): an open-label, randomized, phase 2 clinical trial. Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association. 2024;27(3):571-9. Li S, Xu Q, Dai X, Zhang X, Huang M, Huang K, et al. Neoadjuvant Therapy with Immune Checkpoint Inhibitors in Gastric Cancer: A Systematic Review and Meta-Analysis. Annals of surgical oncology. 2023;30(6):3594-602. Chen YC, Malfertheiner P, Yu HT, Kuo CL, Chang YY, Meng FT, et al. Global Prevalence of Helicobacter pylori Infection and Incidence of Gastric Cancer Between 1980 and 2022. Gastroenterology. 2024;166(4):605-19. Gao S, Song D, Liu Y, Yan H, Chen X. Helicobacter pylori CagA Protein Attenuates 5-Fu Sensitivity of Gastric Cancer Cells Through Upregulating Cellular Glucose Metabolism. OncoTargets and therapy. 2020;13:6339-49. Chichirau BE, Diechler S, Posselt G, Wessler S. Tyrosine Kinases in Helicobacter pylori Infections and Gastric Cancer. Toxins. 2019;11(10). Gong X, Shen L, Xie J, Liu D, Xie Y, Liu D. Helicobacter pylori infection reduces the efficacy of cancer immunotherapy: A systematic review and meta-analysis. Helicobacter. 2023;28(6):e13011. Choi Y, Kim N, Yun CY, Choi YJ, Yoon H, Shin CM, et al. Effect of Helicobacter pylori eradication after subtotal gastrectomy on the survival rate of patients with gastric cancer: follow-up for up to 15 years. Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association. 2020;23(6):1051-63. Zhao Z, Zhang R, Chen G, Nie M, Zhang F, Chen X, et al. Anti-Helicobacter pylori Treatment in Patients With Gastric Cancer After Radical Gastrectomy. JAMA network open. 2024;7(3):e243812. Amin MB, Greene FL, Edge SB, Compton CC, Gershenwald JE, Brookland RK, et al. The Eighth Edition AJCC Cancer Staging Manual: Continuing to build a bridge from a population-based to a more "personalized" approach to cancer staging. CA Cancer J Clin. 2017;67(2):93-9. World Medical Association Declaration of Helsinki: ethical principles for medical research involving human subjects. Jama. 2013;310(20):2191-4. von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Lancet (London, England). 2007;370(9596):1453-7. Wong IYH, Chung JCY, Zhang RQ, Gao X, Lam KO, Kwong DLW, et al. A Novel Tumor Staging System Incorporating Tumor Regression Grade (TRG) With Lymph Node Status (ypN-Category) Results in Better Prognostication Than ypTNM Stage Groups After Neoadjuvant Therapy for Esophageal Squamous Cell Carcinoma. Ann Surg. 2022;276(5):784-91. Hooi JKY, Lai WY, Ng WK, Suen MMY, Underwood FE, Tanyingoh D, et al. Global Prevalence of Helicobacter pylori Infection: Systematic Review and Meta-Analysis. Gastroenterology. 2017;153(2):420-9. Kang SY, Han JH, Ahn MS, Lee HW, Jeong SH, Park JS, et al. Helicobacter pylori infection as an independent prognostic factor for locally advanced gastric cancer patients treated with adjuvant chemotherapy after curative resection. Int J Cancer. 2012;130(4):948-58. Lan KH, Lee WP, Wang YS, Liao SX, Lan KH. Helicobacter pylori CagA protein activates Akt and attenuates chemotherapeutics-induced apoptosis in gastric cancer cells. Oncotarget. 2017;8(69):113460-71. Zhou X, Su J, Zhu L, Zhang G. Helicobacter pylori modulates cisplatin sensitivity in gastric cancer by down-regulating miR-141 expression. Helicobacter. 2014;19(3):174-81. Choi IK, Sung HJ, Lee JH, Kim JS, Seo JH. The relationship between Helicobacter pylori infection and the effects of chemotherapy in patients with advanced or metastatic gastric cancer. Cancer chemotherapy and pharmacology. 2012;70(4):555-8. Nishizuka SS, Tamura G, Nakatochi M, Fukushima N, Ohmori Y, Sumida C, et al. Helicobacter pylori infection is associated with favorable outcome in advanced gastric cancer patients treated with S-1 adjuvant chemotherapy. Journal of surgical oncology. 2018;117(5):947-56. Piessen G, Messager M, Leteurtre E, Jean-Pierre T, Mariette C. Signet ring cell histology is an independent predictor of poor prognosis in gastric adenocarcinoma regardless of tumoral clinical presentation. Ann Surg. 2009;250(6):878-87. Heger U, Blank S, Wiecha C, Langer R, Weichert W, Lordick F, et al. Is preoperative chemotherapy followed by surgery the appropriate treatment for signet ring cell containing adenocarcinomas of the esophagogastric junction and stomach? Annals of surgical oncology. 2014;21(5):1739-48. Becker K, Langer R, Reim D, Novotny A, Meyer zum Buschenfelde C, Engel J, et al. Significance of histopathological tumor regression after neoadjuvant chemotherapy in gastric adenocarcinomas: a summary of 480 cases. Ann Surg. 2011;253(5):934-9. Additional Declarations No competing interests reported. Supplementary Files SupplementaryFigure1.tif SupplmentTable1.docx Cite Share Download PDF Status: Published Journal Publication published 27 Jan, 2025 Read the published version in BMC Cancer → Version 1 posted Editorial decision: Revision requested 27 Sep, 2024 Reviews received at journal 24 Sep, 2024 Reviewers agreed at journal 23 Sep, 2024 Reviews received at journal 08 Sep, 2024 Reviewers agreed at journal 28 Aug, 2024 Reviewers agreed at journal 28 Aug, 2024 Reviews received at journal 09 Aug, 2024 Reviewers agreed at journal 01 Aug, 2024 Reviewers invited by journal 31 Jul, 2024 Editor invited by journal 19 Jul, 2024 Editor assigned by journal 19 Jul, 2024 Submission checks completed at journal 19 Jul, 2024 First submitted to journal 18 Jul, 2024 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4760812","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":338729646,"identity":"1a724df9-4264-4a6f-a339-39ce4afa060f","order_by":0,"name":"Bin Zhong","email":"","orcid":"","institution":"Department of General Surgery (Department of Gastrointestinal Surgery), The Sixth Affiliated Hospital, Sun Yat-sen University","correspondingAuthor":false,"prefix":"","firstName":"Bin","middleName":"","lastName":"Zhong","suffix":""},{"id":338729647,"identity":"d96ea2d1-ef0f-4e2f-84de-c2c1fee97339","order_by":1,"name":"Zhizhong Xiong","email":"","orcid":"","institution":"Department of General Surgery (Department of Gastrointestinal Surgery), The Sixth Affiliated Hospital, Sun Yat-sen University","correspondingAuthor":false,"prefix":"","firstName":"Zhizhong","middleName":"","lastName":"Xiong","suffix":""},{"id":338729648,"identity":"390d0e92-c014-4ce0-a1f0-ec5c2e645288","order_by":2,"name":"Jiabo Zheng","email":"","orcid":"","institution":"Department of General Surgery (Department of Gastrointestinal Surgery), The Sixth Affiliated Hospital, Sun Yat-sen University","correspondingAuthor":false,"prefix":"","firstName":"Jiabo","middleName":"","lastName":"Zheng","suffix":""},{"id":338729649,"identity":"605a2d46-3706-4031-b547-1af73d97da05","order_by":3,"name":"Saddam Ahmed Mohamed","email":"","orcid":"","institution":"Department of General Surgery (Department of Gastrointestinal Surgery), The Sixth Affiliated Hospital, Sun Yat-sen University","correspondingAuthor":false,"prefix":"","firstName":"Saddam","middleName":"Ahmed","lastName":"Mohamed","suffix":""},{"id":338729650,"identity":"bcf94980-ed44-49ec-905f-f88903a16b9a","order_by":4,"name":"Jiachen Sun","email":"","orcid":"","institution":"Department of General Surgery (Department of Gastrointestinal Surgery), The Sixth Affiliated Hospital, Sun Yat-sen University","correspondingAuthor":false,"prefix":"","firstName":"Jiachen","middleName":"","lastName":"Sun","suffix":""},{"id":338729651,"identity":"d5bcb99c-78f4-4f6f-bbe5-491ded1985c3","order_by":5,"name":"Dayin Huang","email":"","orcid":"","institution":"Department of General Surgery (Department of Gastrointestinal Surgery), The Sixth Affiliated Hospital, Sun Yat-sen University","correspondingAuthor":false,"prefix":"","firstName":"Dayin","middleName":"","lastName":"Huang","suffix":""},{"id":338729652,"identity":"0b978c48-fa29-4f0e-ad15-0305d5991026","order_by":6,"name":"Zijian Deng","email":"","orcid":"","institution":"Department of General Surgery (Department of Gastrointestinal Surgery), The Sixth Affiliated Hospital, Sun Yat-sen University","correspondingAuthor":false,"prefix":"","firstName":"Zijian","middleName":"","lastName":"Deng","suffix":""},{"id":338729653,"identity":"e7fad4d1-0859-487f-875c-b2fc649442ec","order_by":7,"name":"Jianping Guo","email":"","orcid":"","institution":"Department of General Surgery (Department of Gastrointestinal Surgery), The Sixth Affiliated Hospital, Sun Yat-sen University","correspondingAuthor":false,"prefix":"","firstName":"Jianping","middleName":"","lastName":"Guo","suffix":""},{"id":338729654,"identity":"94cde025-5c89-4789-8516-20f637c5830a","order_by":8,"name":"Junsheng Peng","email":"","orcid":"","institution":"Department of General Surgery (Department of Gastrointestinal Surgery), The Sixth Affiliated Hospital, Sun Yat-sen University","correspondingAuthor":false,"prefix":"","firstName":"Junsheng","middleName":"","lastName":"Peng","suffix":""},{"id":338729655,"identity":"1f5ff3f4-b1cf-47fa-86ff-6d5eb2d2fb8a","order_by":9,"name":"Huashe Wang","email":"","orcid":"","institution":"Department of General Surgery (Department of Gastrointestinal Surgery), The Sixth Affiliated Hospital, Sun Yat-sen University","correspondingAuthor":false,"prefix":"","firstName":"Huashe","middleName":"","lastName":"Wang","suffix":""},{"id":338729656,"identity":"916afe42-1622-45ff-b8df-d019adaf3e18","order_by":10,"name":"Lei Lian","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABDUlEQVRIiWNgGAWjYBACPmYg8YBBQo4fSB94ABPmwaOFDaQlgUHCWLIBqCWBKC0MYC0MiRsOQBhEaGFnfvYgocKCcfO1ww+BttQlzp+RwPjgbRuDvDlOh7GZGySckWA2u51mANRyOHHDjQRmw7ltDIY7G3D6xUwisU2Czex2AkjLgcQNEgls0rxtDEAuLi3s3yQS/0nwGM9O/wBzGPtv/Fp4gLY0SEgYSOeAbGFObLiRwMZMQEuZRMIxCQOJ2zkFBxIMDhtvOPOwWXLOOQnDDTi08PMf3ybxoaauvn92+uYPHyrqZOe3Jx/88KbMRh6XLWjAgMGxgYGxAciSIEo9GNgTr3QUjIJRMApGCgAAf1ZXF2nrvwcAAAAASUVORK5CYII=","orcid":"","institution":"Department of General Surgery (Department of Gastrointestinal Surgery), The Sixth Affiliated Hospital, Sun Yat-sen University","correspondingAuthor":true,"prefix":"","firstName":"Lei","middleName":"","lastName":"Lian","suffix":""}],"badges":[],"createdAt":"2024-07-18 07:47:33","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4760812/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4760812/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12885-025-13494-5","type":"published","date":"2025-01-27T15:57:53+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":62730838,"identity":"8f4c1cd2-fc21-40b4-aa48-3964f01453d0","added_by":"auto","created_at":"2024-08-18 23:24:55","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1877263,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFlow diagram of patient inclusion and exclusion\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4760812/v1/bb2a2db4bfd724728cde164e.png"},{"id":62729883,"identity":"7cc13efa-8d32-4275-8230-1801d1b8753a","added_by":"auto","created_at":"2024-08-18 23:08:55","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":3566481,"visible":true,"origin":"","legend":"\u003cp\u003eAssessment of the importance of factors affecting neoadjuvant chemotherapy in patients with LAGC. \u003cstrong\u003eA \u003c/strong\u003eROC curves for each variable, with the area under the curve in the lower right corner. \u003cstrong\u003eB\u003c/strong\u003e Histograms of the Wald-test test for each variable, with \u003cem\u003eχ²-df\u003c/em\u003e as the horizontal coordinate, as an indicator of determining the importance of each influencing factor.\u003c/p\u003e","description":"","filename":"Figure2AB.png","url":"https://assets-eu.researchsquare.com/files/rs-4760812/v1/6b88ed33c3baed56655f1c29.png"},{"id":62730346,"identity":"af6ef400-80fa-4d97-8d8b-c2bbb3b6a952","added_by":"auto","created_at":"2024-08-18 23:16:55","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":2842669,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan–Meier curve. \u003cstrong\u003eA\u003c/strong\u003e showing overall survival in the \u003cem\u003eH. pylori\u003c/em\u003e-negative and \u003cem\u003eH. pylori\u003c/em\u003e-positive groups with number at risk table. \u003cstrong\u003eB\u003c/strong\u003e showing disease-free survival in the \u003cem\u003eH. pylori\u003c/em\u003e-negative and \u003cem\u003eH. pylori\u003c/em\u003e-positive groups with number at risk table.\u003c/p\u003e","description":"","filename":"Figure3AB.png","url":"https://assets-eu.researchsquare.com/files/rs-4760812/v1/b7ddcb59a8955ab31d3e1503.png"},{"id":62729882,"identity":"e573f925-af82-4ea9-8fdb-56b65fa3df5a","added_by":"auto","created_at":"2024-08-18 23:08:55","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":270175,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot. \u003cstrong\u003eA\u003c/strong\u003e Multivariate Cox regression analysis of OS. \u003cstrong\u003eB\u003c/strong\u003e Multivariate Cox regression analysis of DFS\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-4760812/v1/a5b51412e766fc165f6752d5.png"},{"id":75352050,"identity":"1d34a833-be9c-48fe-9153-cf7204527e2a","added_by":"auto","created_at":"2025-02-03 16:12:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":18883655,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4760812/v1/8dc13d7b-e9c7-43b3-8ba5-43ec4958cae5.pdf"},{"id":62729885,"identity":"be82f54f-08a6-4a1c-9d80-0960248e480f","added_by":"auto","created_at":"2024-08-18 23:08:55","extension":"tif","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":5132216,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigure1.tif","url":"https://assets-eu.researchsquare.com/files/rs-4760812/v1/604f12bc25526fd33dd0d21f.tif"},{"id":62729880,"identity":"f80ee1b1-a67d-4dd7-bf35-44cd4f85d775","added_by":"auto","created_at":"2024-08-18 23:08:55","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":25772,"visible":true,"origin":"","legend":"","description":"","filename":"SupplmentTable1.docx","url":"https://assets-eu.researchsquare.com/files/rs-4760812/v1/b3d0931944a221b365b58cda.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Impact of Helicobacter pylori infection on neoadjuvant chemotherapy in locally advanced gastric cancer: a retrospective analysis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eGastric cancer (GC) is the fifth most common cancer and the fourth leading cause of cancer-related deaths globally, making it a significant health concern [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In China, 70%-80% of GC patients are in a locally advanced stage at the time of diagnosis, and their 5-year OS rate after radical surgery remains below 50% [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSince the MAGIC study [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] established the significance of neoadjuvant chemotherapy in the treatment of locally advanced gastric cancer (LAGC), with subsequent studies such as the PRODIGY [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] and RESOLVE [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] trials, it has been further demonstrated that neoadjuvant chemotherapy can increase the R0 resection rate and improve the prognosis of patients with LAGC, making neoadjuvant chemotherapy the focus of the treatment of LAGC. According to previous studies, the proportion of patients with LAGC achieving tumor regression grade (TRG) 0\u0026ndash;1 is approximately 11%-24% [\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], indicating room for significant improvement.\u003c/p\u003e \u003cp\u003eStatistics have shown that, from 2015 to 2022, the global adult infection rate of \u003cem\u003eHelicobacter pylori\u003c/em\u003e (\u003cem\u003eH. pylori\u003c/em\u003e) was approximately 43.9%, making it the principal etiological agent for GC [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Previous studies have shown that \u003cem\u003eH. pylori\u003c/em\u003e can reduce the sensitivity of GC cells to chemotherapeutic drugs by up-regulating cellular glucose metabolism through the secretion of CagA protein and by affecting the receptor tyrosine kinase process [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Recent retrospective studies have shown that \u003cem\u003eH. pylori\u003c/em\u003e infection decreases the efficacy of tumor immunotherapy [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] and that \u003cem\u003eH. pylori\u003c/em\u003e eradication after surgery improves both the efficacy and prognosis of adjuvant chemotherapy in patients with LAGC [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHowever, the effect of \u003cem\u003eH. pylori\u003c/em\u003e infection on neoadjuvant chemotherapy in patients with LAGC remains unclear. In this study, we aimed to explore whether \u003cem\u003eH. pylori\u003c/em\u003e infection affects the outcome of neoadjuvant chemotherapy in patients with LAGC, complementing the results of previous studies.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatients\u003c/h2\u003e \u003cp\u003eWe retrospectively collected medical data of patients with GC who underwent radical surgery at the Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, China, between 1, January, 2010, and 31, January, 2021. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, patients diagnosed with gastric adenocarcinoma or esophagogastric junction adenocarcinoma who underwent R0 resection and D2 lymphadenectomy were included in the cohort study. Patients with pathological diagnoses of stage I or IV had residual gastric cancer, did not receive 3\u0026ndash;4 cycles of neoadjuvant chemotherapy, had incomplete clinicopathological data, missing follow-up information, had no information on \u003cem\u003eH. pylori\u003c/em\u003e infection status, and received anti-\u003cem\u003eH. pylori\u003c/em\u003e treatment during neoadjuvant chemotherapy was excluded. Pathological staging was evaluated according to the eighth edition of the American Joint Committee on Cancer\u0026rsquo;s Cancer Staging Manual [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], including the tumor depth of invasion and extent of resection, among other factors. Patients were categorized into \u003cem\u003eH. pylori\u003c/em\u003e-positive and \u003cem\u003eH. pylori\u003c/em\u003e-negative groups according to their \u003cem\u003eH. pylori\u003c/em\u003e infection status before the time of their first neoadjuvant treatment.\u003c/p\u003e \u003cp\u003eAll patients in this retrospective cohort provided written informed consent for the anonymous collection and analysis of clinical data. This study was conducted under the Declaration of Helsinki [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] and approved by the Review Board of the Sixth Affiliated Hospital of Sun Yat-sen University. The reporting of this study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eEvaluation of\u003c/b\u003e \u003cb\u003eH. pylori\u003c/b\u003e \u003cb\u003einfection status\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe \u003cem\u003eH. pylori\u003c/em\u003e infection status was determined using the 13C urea breath test and/or histological examination of gastric tissue (Giemsa or immunohistochemical staining) before the first regimen of neoadjuvant chemotherapy. A positive result was obtained for either test diagnosed \u003cem\u003eH. pylori\u003c/em\u003e infection. Patients with negative test results were classified into the \u003cem\u003eH. pylori\u003c/em\u003e-negative group, whereas the H. pylori-positive group was classified as positive.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eOutcome\u003c/h2\u003e \u003cp\u003eTumor pathological response was scored according to TRG [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], where TRG 0 represents complete remission (no residual cancer cells), TRG 1indicates significant remission (residual lesions\u0026thinsp;\u0026lt;\u0026thinsp;10%), TRG 2 indicates partial remission (10%-50% residual lesions), and TRG 3 meant minimal or no response (\u0026gt;\u0026thinsp;50% residual lesions). The primary endpoint in this study was the major pathological response (MPR), defined as a TRG score of 0\u0026ndash;1. The secondary study endpoints included pathological complete response (PCR), defined as TRG 0; OS, defined as the time from the date of surgery to the date of death from any cause; and disease-free survival (DFS), defined as the time from the date of surgery to recurrence, or death, whichever occured first.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eData collection and conversion\u003c/h2\u003e \u003cp\u003eThis study incorporated the following clinical and pathological indicators: age, sex, family history of cancer, body mass index (BMI), histological differentiation, TRG, Lauren classification, pathological T stage, pathological N stage, TNM staging, tumor location, neoadjuvant chemotherapy regimen, Her2 status, Mismatch Repair (MMR) status, preoperative hemoglobin, preoperative albumin, preoperative white blood cells, preoperative platelets, carcinoembryonic antigen (CEA), cancer antigen 199 (CA199), cancer antigen 125 (CA125), cancer antigen 153(CA153), and alpha-fetoprotein (AFP). TRG, histological differentiation, Lauren classification, depth of tumor invasion, lymph node metastasis, TNM stage, tumor location, Her2, and MMR were determined based on postoperative pathological results. Preoperative hematological parameters were based on blood test performed immediately before their first neoadjuvant chemotherapy.\u003c/p\u003e \u003cp\u003eAge was categorized into three groups: early onset (\u0026le;\u0026thinsp;50 years), average age group (51\u0026ndash;64 years), and late-onset group (\u0026ge;\u0026thinsp;65 years); According to their calculated BMI, the patients were classified as underweight (BMI less than 18.5 kg/m\u003csup\u003e2\u003c/sup\u003e), normal weight (BMI 18.5\u0026ndash;24 kg/m\u003csup\u003e2\u003c/sup\u003e), or overweight/obese (\u0026ge;\u0026thinsp;24 kg/m\u003csup\u003e2\u003c/sup\u003e). Blood biochemical parameters and tumor marker levels were grouped according to abnormal values of the hospital tests. Patients were followed up every 3 months during the first 2 years, every 6 months from 2 to 5 years, and then annually. Follow-up data were retrieved from the follow-up data center of our hospital on 30 June 2022.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe basic characteristics of patients were compared between the \u003cem\u003eH. pylori\u003c/em\u003e-positive and \u003cem\u003eH. pylori\u003c/em\u003e-negative groups using either the chi-squared test or two-tailed Fisher\u0026rsquo;s exact test for categorical variables. Univariate and multivariate logistic regression analyses were used to identify the independent risk factors for determining the efficacy of neoadjuvant chemotherapy in patients with LAGC. The area under the receiver operating characteristic (ROC) curve and Wald test were used to evaluate the importance of factors affecting neoadjuvant therapy. Survival curves were calculated using the Kaplan-Meier method. The forest plots were generated according to the Cox regression analysis results, using the \"survival\" and \"survminer\" packages. The \"mediation\" package was utilized for analyzing mediation effects. All statistical tests were two-sided, with significance set at \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05. All analyses were performed using the R software (version 4.3.1; R Foundation for Statistical Computing).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003ch2\u003ePatient characteristics\u003c/h2\u003e\n\u003cp\u003eAccording to the inclusion and exclusion criteria, 239 patients were included in the analysis (median [IQR] age, 60 years; 178 [74.5%] male and 61 [25.5%] female). There were 51 \u003cem\u003eH. pylori\u003c/em\u003e-positive patients and 188 \u003cem\u003eH. pylori\u003c/em\u003e-negative patients. A summary of the patient\u0026apos;s characteristics is presented in \u003cstrong\u003eTable 1.\u003c/strong\u003e Overall, the baseline patient characteristics were consistent. There were no significant differences in sex, age, BMI, TNM stage, CPR, neoadjuvant chemotherapy regimen, tumor location, histological differentiation, blood biochemical indicators and tumor marker levels between the two groups. However, compared with the \u003cem\u003eH. pylori\u003c/em\u003e-negative group, the rate of MPR in the \u003cem\u003eH. pylori\u003c/em\u003e-positive group was lower (74/188[39.4%] VS 10/51[19.6%]; \u003cem\u003eP\u003c/em\u003e = 0.009), and the proportion of patients with a family history of cancer was higher (5/188[2.7%] vs 5/51[9.8%]; \u003cem\u003eP\u003c/em\u003e = 0.024).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1. Patient demographic, clinical, and pathological characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"573\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eH. pylori\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e-negative\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN=188\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eH. pylori\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e-posititve\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN=51\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eAge (years) (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e0.510\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003e\u0026le;50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e39 (20.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e14 (27.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003e51-64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e96 (51.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e22 (43.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003e\u0026ge;65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e53 (28.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e15 (29.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eSex (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e0.146\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003emale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e136 (72.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e42(82.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003efemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e52 (27.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e9 (17.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eFamily history of cancer(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.024\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e183 (97.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e46 (90.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e5 (2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e5 (9.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e) (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e0.085\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003e18.5-24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e29 (15.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e2 (3.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003e＜18.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e118 (62.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e38 (74.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003e\u0026ge;24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e41 (21.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e11 (21.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eTRG (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e0.076\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e36 (19.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e5 (9.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e38 (20.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e5 (9.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e94 (50.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e34 (66.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e20 (10.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e7 (13.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eMPR（TRG:0/1）\u0026nbsp;(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.009\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e114 (60.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e41 (80.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e74 (39.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e10 (19.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eCPR（TRG:0）\u0026nbsp;(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e0.116\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e152 (80.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e46 (90.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e36 (19.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e5 (9.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003ePathological T stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e0.942\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eT1/2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e119 (63.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e32 (62.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eT3/4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e69 (36.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e19 (37.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003ePathological N stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e0.398\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eN (\u0026minus;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e101 (53.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e24 (47.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eN (+)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e87 (46.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e27 (52.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eTNM Stage (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e0.822\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e111(59.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e31(60.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e77(41.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e20(39.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eAlbumin (g/L) (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e0.495\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003e40-55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e61 (32.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e14 (27.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003e＜40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e127 (67.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e37 (72.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eHemoglobin (g/L) (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e0.657\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003e120-160\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e53 (28.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e16 (31.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003e＜120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e135 (71.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e35 (68.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003ePlatelet (10\u003csup\u003e9\u003c/sup\u003e/L) (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e0.648\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003e100-300\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e142 (75.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e37 (72.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003e＜100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e22 (11.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e5 (9.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003e＞300\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e24 (12.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e9 (17.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eLeucocyte (10\u003csup\u003e9\u003c/sup\u003e/L) (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e0.303\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003e4-10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e128 (68.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e29 (56.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003e＜4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e38 (20.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e13 (25.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003e＞10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e22 (11.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e9 (17.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eCEA (ng/L) (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e0.256\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003e0-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e147 (78.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e36 (70.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003e＞5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e41 (21.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e15 (29.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eCA199 (U/mL) (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e0.216\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003e0-37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e167 (88.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e42 (82.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003e＞37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e21 (11.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e9 (17.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eCA125 (U/mL) (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e0.597\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003e0-35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e163 (87.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e43 (84.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e24 (12.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e8 (15.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eCA153 (U/mL) (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e0.777\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003e0-32.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e183 (97.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e50 (98.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003e＞32.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e5 (2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e1 (2.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eAFP (ng/L) (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e0.446\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003e0-8.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e166 (88.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e43 (84.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003e＞8.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e22 (11.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e8 (15.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eHer2 (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e0.328\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003enegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e125 (66.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e39 (76.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003epositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e33 (17.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e5 (9.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eunknow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e30 (16.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e7 (13.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eMMR (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e0.209\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003epMMR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e114 (60.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e37 (72.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003edMMR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e9 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e3 (5.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eunknow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e65 (34.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e11 (21.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eChemotherapy regimen(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e0.945\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eSOX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e62 (33.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e15 (29.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eDOF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e58 (30.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e17 (33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eFLOT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e30 (16.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e7 (13.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eXELOX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e13 (6.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e3 (5.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eFOLFOX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e16 (8.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e5 (9.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e9 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e4 (7.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eLauren(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e0.099\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eintestine type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e65 (34.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e26 (51.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003ediffused type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e76 (40.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e16 (31.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003emixed type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e47 (25.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e9 (17.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eTumor location (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e0.891\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eesophagogastric junction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e47 (25.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e10 (19.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eupper\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e18 (9.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e4 (7.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003emiddle\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e47 (25.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e13 (25.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003elower\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e75 (40.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e24 (47.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003eDifferentiation (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e0.394\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003ewell\u0026nbsp;differentiated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e9 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e5 (9.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003emoderately\u0026nbsp;differentiated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e100 (53.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e25 (49.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.86713286713287%\"\u003e\n \u003cp\u003epoorly differentiated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.902097902097903%\"\u003e\n \u003cp\u003e79 (42.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.853146853146853%\"\u003e\n \u003cp\u003e21 (41.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.377622377622377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: BMI, body mass index; TRG, tumor regression grade; MPR, major pathological response; CPR, pathological complete response; CEA, carcinoembryonic antigen; CA199, cancer antigen 199; CA125, cancer antigen 125; CA153, cancer antigen 153; AFP, alpha-fetoprotein; pMMR, proficient Mismatch Repair; dMMR, deficient Mismatch Repair.Abbreviations: BMI, body mass index; TRG, tumor regression grade; MPR, major pathological response; CPR, pathological complete response; CEA, carcinoembryonic antigen; CA199, cancer antigen 199; CA125, cancer antigen 125; CA153, cancer antigen 153; AFP, alpha-fetoprotein; pMMR, proficient Mismatch Repair; dMMR, deficient Mismatch Repair.\u003c/p\u003e\n\u003ch2\u003eUnivariate and multivariate analyses of factors influencing neoadjuvant therapy effectiveness\u003c/h2\u003e\n\u003cp\u003eThe results of univariate and multivariate analyses to determine the variables associated with MPR are presented in \u003cstrong\u003eTable 2\u003c/strong\u003e. The univariate analysis comprised 20 variables, \u0026nbsp; and the results indicated that age\u0026le;50 years (OR: 0.328, 95% CI: 0.179-0.816, \u003cem\u003eP\u003c/em\u003e = 0.013), \u003cem\u003eH. pylori\u003c/em\u003e positivity (OR: 0.376, 95% CI: 0.177-0.796, \u003cem\u003eP\u003c/em\u003e = 0.011), Pathological T 3/4 (OR: 0.522, 95% CI: 0.293-0.929, \u003cem\u003eP\u003c/em\u003e = 0.027), CA125＞35U/ml (OR: 0.387, 95% CI: 0.152-0.981, \u003cem\u003eP\u003c/em\u003e = 0.046) were associated with MPR. Variables with \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05 in the univariate analysis and factors from previous studies that may influence neoadjuvant chemotherapy were included in the multivariate analysis. The results showed that LAGC patients aged \u0026le;50 years (OR: 0.423, 95% CI: 0.194-0.925, \u003cem\u003eP\u003c/em\u003e = 0.031), \u003cem\u003eH. pylori\u003c/em\u003e-positive (OR: 0.396, 95% CI: 0.183-0.854, \u003cem\u003eP\u0026nbsp;\u003c/em\u003e= 0.018), T3/4 (OR: 0.524, 95% CI: 0.288-0.954, \u003cem\u003eP\u003c/em\u003e = 0.035) and CA125 \u0026gt;35U/ml (OR: 0.345, 95% CI: 0.132-0.904, \u003cem\u003eP\u003c/em\u003e = 0.030) were less likely to achieve MPR.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Uni- and multivariate analysis of influencing factors of MPR\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"718\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.86908077994429%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eUnivariate analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.969359331476323%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eMultivariate analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.009009009009006%\" valign=\"top\"\u003e\n \u003cp\u003eOR（95% CI）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.144144144144143%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.72972972972973%\" valign=\"top\"\u003e\n \u003cp\u003eOR（95% CI）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.6036036036036037%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.513513513513514%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003eAge (y)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e51-64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003eref.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003eref.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026le;50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e0.382(0.179-0.816)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.013\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e0.423(0.194-0.925)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.031\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026ge; 65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e0.848(0.459-1.568)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e0.599\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e0.953(0.501-1.811)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0.883\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003eSex\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003emale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003eref.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003efemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e0.710(0.379-1.332)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e0.286\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003eFamily history\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003eref.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e2.904 (0.796-10.595)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e0.106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eH. pylori\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003enegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003eref.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003eref.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003epositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e0.376(0.177-0.796)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.011\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e0.396(0.183-0.854)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.018\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\"\u003e\n \u003cp\u003e\u0026ge;24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003eref.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\"\u003e\n \u003cp\u003e＜18.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e1.558(0.609-3.985)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e0.355\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\"\u003e\n \u003cp\u003e18.5-24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e1.420(0.718-2.811)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e0.314\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003ePathological T stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\"\u003e\n \u003cp\u003eT1/2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003eref.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003eref.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\"\u003e\n \u003cp\u003eT3/4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e0.522(0.293-0.929)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.027\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e0.524(0.288-0.954)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.035\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003ePathological N stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\"\u003e\n \u003cp\u003eN (\u0026minus;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003eref.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\"\u003e\n \u003cp\u003eN (+)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e0.859(0.504-1.463)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e0.575\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003eDifferentiation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\"\u003e\n \u003cp\u003ewell\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003eref.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\"\u003e\n \u003cp\u003epoor\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e1.367(0.399-4.680)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e0.618\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\"\u003e\n \u003cp\u003emoderate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e1.406(0.417-4.743)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e0.583\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003eLauren\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\"\u003e\n \u003cp\u003emixed type\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003eref.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\"\u003e\n \u003cp\u003eintestine type\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e1.792(0.878-3.660)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e0.109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\"\u003e\n \u003cp\u003ediffused type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e1.210(0.586-2.499)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e0.607\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003eTumor location\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\"\u003e\n \u003cp\u003eesophagogastric junction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003eref.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\"\u003e\n \u003cp\u003elower\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e0.935(0.478-1.827)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e0.844\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\"\u003e\n \u003cp\u003emiddle\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e0.881(0.416-1.866)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e0.741\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\"\u003e\n \u003cp\u003eupper\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e0.481(0.156-1.489)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e0.204\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003eAlbumin (g/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\"\u003e\n \u003cp\u003e40-55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003eref.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\"\u003e\n \u003cp\u003e＜40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e1.031(0.581-1.829)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e0.916\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003eHemoglobin (g/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\"\u003e\n \u003cp\u003e120-160\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003eref.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\"\u003e\n \u003cp\u003e＜120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e0.856(0.479-1.531)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e0.601\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003eCEA (ng/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\"\u003e\n \u003cp\u003e0-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003eref.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\"\u003e\n \u003cp\u003e＞5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e0.755(0.396-1.437)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e0.392\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003eCA199 (U/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\"\u003e\n \u003cp\u003e0-37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003eref.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\"\u003e\n \u003cp\u003e＞37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e0.912(0.406-2.051)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e0.824\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003eCA125 (U/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\"\u003e\n \u003cp\u003e0-35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003eref.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003eref.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\"\u003e\n \u003cp\u003e＞35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e0.387(0.152 -0.981)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.046\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e0.345(0.132-0.904)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.030\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003eCA153 (U/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\"\u003e\n \u003cp\u003e0-32.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003eref.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\"\u003e\n \u003cp\u003e＞32.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e0.921(0.165-5.134)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e0.925\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003eAFP (ng/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\"\u003e\n \u003cp\u003e0-8.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003eref.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\"\u003e\n \u003cp\u003e＞8.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e1.269(0.579-2.779)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e0.552\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eChemotherapy regimen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003eref.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003eSOX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e0.769(0.228-2.592)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e0.672\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003eDOF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e1.127(0.337-3.773)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e0.846\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003eFLOT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e0.677(0.181-2.537)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e0.563\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003eXELOX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e0.960(0.213-4.335)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e0.958\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003eFOLFOX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e0.640(0.148-2.768)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e0.550\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003eHer2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\"\u003e\n \u003cp\u003enegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003eref.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\"\u003e\n \u003cp\u003eposititve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e0.590(0.288-1.210)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e0.150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003eMMR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\"\u003e\n \u003cp\u003epMMR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003eref.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.77715877437326%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\"\u003e\n \u003cp\u003edMMR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.030640668523677%\" valign=\"top\"\u003e\n \u003cp\u003e0.673(0.203-2.227)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.838440111420613%\" valign=\"top\"\u003e\n \u003cp\u003e0.516\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.384401114206128%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.584958217270195%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: BMI, body mass index; \u003cem\u003eHp\u003c/em\u003e, \u003cem\u003eHelicobacter pylori\u003c/em\u003e; CEA, carcinoembryonic antigen; CA199, cancer antigen 199; CA125, cancer antigen 125; CA153, cancer antigen 153; AFP, alpha-fetoprotein; pMMR, proficient Mismatch Repair; dMMR, deficient Mismatch Repair.\u003c/p\u003e\n\u003ch2\u003eAssessment of the importance of factors influencing neoadjuvant therapy\u003c/h2\u003e\n\u003cp\u003eTo further explore the importance of the influencing factors of neoadjuvant chemotherapy in LAGC patients, we subjected the variables with \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05 in the multivariate analysis to ROC curve analysis (\u003cstrong\u003eFigure 2A\u003c/strong\u003e) and found that \u003cem\u003eH. pylori\u003c/em\u003e infection accounted for the highest area under the curve. We also utilized the Wald test to determine the importance of each influencing factor and found that \u003cem\u003eH. pylori\u003c/em\u003e infection was at the top of the list of factors influencing MPR (\u003cstrong\u003eFigure 2B\u003c/strong\u003e). These findings indicate that \u003cem\u003eH. pylori\u003c/em\u003e infection significantly influences the MPR, as indicated by both tests.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eInfluence of Helicobacter pylori infection on prognosis\u003c/h2\u003e\n\u003cp\u003eWe performed a survival analysis to compare the OS of the \u003cem\u003eH. pylori\u003c/em\u003e-positive and \u003cem\u003eH. pylori\u003c/em\u003e-negative groups (\u003cstrong\u003eFigure 3A\u003c/strong\u003e). The results showed a statistically significant difference in OS between the two groups (\u003cem\u003eP\u0026nbsp;\u003c/em\u003e= 0.035). Subsequently, the DFS of the two groups was evaluated, and as shown in \u003cstrong\u003eFigure 3B\u003c/strong\u003e, there was a significant DFS advantage in the \u003cem\u003eH. pylori\u003c/em\u003e-negative group compared to the \u003cem\u003eH. pylori\u003c/em\u003e-positive group (\u003cem\u003eP\u0026nbsp;\u003c/em\u003e= 0.029).\u003c/p\u003e\n\u003ch2\u003eCox regression analysis\u003c/h2\u003e\n\u003cp\u003eIn univariate analysis, TRG 0 (OS, OR: 0.242, 95% CI: 0.068-0.857, \u003cem\u003eP\u003c/em\u003e = 0.028; DFS, OR: 0.248, 95% CI: 0.103-0.594, \u003cem\u003eP\u003c/em\u003e = 0.002), as well as lower tumor location (OS, OR: 0.488, 95% CI: 0.248-0.960, P = 0.038; DFS, OR: 0.492, 95% CI: 0.278-0.869, P = 0.015), were protective factors for OS as well as DFS, while \u003cem\u003eH. pylori\u003c/em\u003e-positive (OS, OR: 1.845, 95% CI: 1.033-3.293, \u003cem\u003eP\u003c/em\u003e = 0.038; DFS, OR: 1.686, 95% CI: 1.049-2.712, \u003cem\u003eP\u003c/em\u003e = 0.031) was a risk factor for OS as well as DFS (\u003cstrong\u003eSupplementary Table 1\u003c/strong\u003e). In the multivariate Cox analysis, we found that TRG was an independent risk factor for OS (TRG 2, OR: 3.38, 95% CI: 1.28-8.93, \u003cem\u003eP\u003c/em\u003e = 0.014; TRG 3, OR: 3.32, 95% CI: 0.90-12.19, \u003cem\u003eP\u003c/em\u003e = 0.071). Lower tumor location was an independent protective factor for OS (OR: 0.48, 95% CI: 0.23-0.99, \u003cem\u003eP\u003c/em\u003e = 0.0461) (\u003cstrong\u003eFigure 4\u003c/strong\u003e). Similar findings were observed in the DFS analysis. However, interestingly, \u003cem\u003eH. pylori\u003c/em\u003e was not significant in the multivariate analysis, in conjunction with the previous results, we hypothesized that \u003cem\u003eH. pylori\u003c/em\u003e may affect the OS and DFS of patients by influencing TRG, so we further performed a mediated effect analysis regarding \u003cem\u003eH. pylori\u003c/em\u003e and TRG, and the results showed that \u003cem\u003eH. pylori\u003c/em\u003e could affect the prognosis of patients by influencing TRG (\u003cstrong\u003eSupplementary Figure 1A, B\u003c/strong\u003e).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study presents an exploratory analysis of the influence of \u003cem\u003eH. pylori\u003c/em\u003e infection on the efficacy and prognosis of neoadjuvant chemotherapy in patients with LAGC. This study provides a basis for further exploration of the role of \u003cem\u003eH. pylori\u0026nbsp;\u003c/em\u003eeradication in neoadjuvant chemotherapy. Our study found that \u003cem\u003eH. pylori\u003c/em\u003e infection was significantly associated with MPR rates and that \u003cem\u003eH. pylori\u003c/em\u003e-positive patients had a worse prognosis among LAGC patients undergoing neoadjuvant chemotherapy. Multivariate logistic regression analysis was performed to explore the factors affecting MPR. \u003cem\u003eH. pylori\u003c/em\u003e-positive, higher T-stage, younger age, and CA125 abnormalities were associated with non-MPR. In this study, \u003cem\u003eH. pylori\u003c/em\u003e infection exhibited a more substantial influence than other factors. Furthermore, multivariate Cox regression and mediation effect analyses suggested that \u003cem\u003eH. pylori\u003c/em\u003e may influence patient prognosis through its impact on TRG.\u003c/p\u003e\n\u003cp\u003eThe global prevalence of \u003cem\u003eH. pylori\u003c/em\u003e infection is about 50% [19]. \u003cem\u003eH. pylori\u003c/em\u003e infection is one of the major risk factors for gastric cancer development, increasing the risk of developing gastric cancer approximately threefold [20]. Chemotherapy plays a pivotal role in the comprehensive treatment of gastric cancer, significantly contributing to improving the prognosis and quality of life of patients with gastric cancer.. However, whether \u003cem\u003eH. pylori\u003c/em\u003e affects the effect of chemotherapy remains unclear. It has been reported that CagA protein secreted by \u003cem\u003eH. pylori\u003c/em\u003e is positively correlated with 5-fluorouracil resistance in gastric cancer, and that CagA protein reduces the sensitivity of gastric cancer cells to 5-fluorouracil by upregulating cellular glucose metabolism [10, 21]. Simultaneously, \u003cem\u003eH. pylori\u003c/em\u003e can affect the receptor tyrosine kinase process in tumors, which in turn affects resistance to platinum and fluorouracil chemotherapy [11]. However, \u003cem\u003eH. pylori\u003c/em\u003e has also been shown to increase the sensitivity of gastric cancer cells to cisplatin by downregulating miR-141 [22].\u003c/p\u003e\n\u003cp\u003eContradictory results have been reported in clinical studies. A retrospective study by Zhao et al. [14] found that in TNM stage II/III patients receiving adjuvant chemotherapy, \u003cem\u003eH. pylori\u003c/em\u003e eradication therapy was strongly associated with a survival benefit (OS: HR, 0.49; 95%CI: 0.24-0.99, \u003cem\u003eP\u0026nbsp;\u003c/em\u003e= 0.046), whereas in patients who did not receive adjuvant chemotherapy, anti-\u003cem\u003e\u0026nbsp;H. pylori\u003c/em\u003e therapy was not associated with survival benefit (OS: HR, 0.29; 95% CI: 0.04-2.08; \u003cem\u003eP\u003c/em\u003e = 0.22). In a meta-analysis that included four studies, it was found that among those who received immunotherapy, those who were positive for \u003cem\u003eH. pylori\u003c/em\u003e infection had lower OS and PFS rates than those who were \u003cem\u003eH. pylori\u003c/em\u003e-negative, suggesting that \u003cem\u003eH. pylori\u003c/em\u003e infection reduces the efficacy of tumor immunotherapy [12]. However, in advanced gastric cancer or metastatic gastric cancer, Choi et al. [23]\u003csup\u003e\u0026nbsp;\u003c/sup\u003efound that patients with concomitant \u003cem\u003eH. pylori\u003c/em\u003e infection responded better to chemotherapy than those without \u003cem\u003eH. pylori\u003c/em\u003e infection. Additionally, the results of Nishizuka et al. [24] suggested that \u003cem\u003eH. pylori\u003c/em\u003e infection is associated with a favorable prognosis in patients with advanced gastric cancer receiving S-1-adjuvant chemotherapy. An article that included patients with TNM stage III gastric cancer who received adjuvant chemotherapy after radical resection analyzed \u003cem\u003eH. pylori\u003c/em\u003e infection and its association with clinical outcome. The results showed that \u003cem\u003eH. pylori\u003c/em\u003e infection status did not affect either OS or DFS. However, this study had several limitations. First, only 16 \u003cem\u003eH. pylori\u003c/em\u003e-positive patients were included. Second, information on whether neoadjuvant chemotherapy was administered is unknown and the follow-up period was not sufficiently long.\u003c/p\u003e\n\u003cp\u003eTo the best of our knowledge, studies exploring this topic remain relatively scarce, warranting further investigation to substantiate these findings. Our study complements this field by including patients who underwent neoadjuvant chemotherapy in TNM stage II/III, innovatively analyzing the impact of \u003cem\u003eH. pylori\u003c/em\u003e infection on neoadjuvant treatment outcomes, and providing an in-depth analysis of the factors that contribute to neoadjuvant treatment outcomes and prognosis. Our study found that patients with\u003cem\u003e\u0026nbsp;H. pylori\u003c/em\u003e infection and abnormal CA125 levels may not benefit from neoadjuvant chemotherapy, whereas patients with low T-stage and older patients are more likely to benefit from neoadjuvant chemotherapy, which is in line with some of the results of previous studies. However, tumor site, histologic differentiation, and Lauren classification, which were mentioned in previous studies as possible influencers of neoadjuvant chemotherapy efficacy, did not consistently emerge as significantly in our study [25-27]. Meanwhile, the analysis of \u003cem\u003eH. pylori\u003c/em\u003e infection as a variable was not addressed in previous studies. Therefore, further multicenter data are needed to verify the reliability of this conclusion. An interesting observation found in our study was that when both \u003cem\u003eH. pylori\u003c/em\u003e and TRG were included in the Cox regression analysis, the effect of \u003cem\u003eH. pylori\u003c/em\u003e on patient prognosis seemed to diminish. This suggests that \u003cem\u003eH. pylori\u003c/em\u003e may affect the survival prognosis of patients through the mediating variable of TRG, and we subsequently verified this speculation by mediation effect analysis. We anticipate that as more relevant studies emerge to improve our understanding of the relationship between \u003cem\u003eH. pylori\u003c/em\u003e infection and chemotherapy for gastric cancer, more effective treatment strategies will be available for GC patients with concomitant \u003cem\u003eH. pylori\u003c/em\u003e infection.\u003c/p\u003e\n\u003cp\u003eOur study has several limitations. First, none of the \u003cem\u003eH. pylori\u003c/em\u003e-positive patients at our center received \u003cem\u003eH. pylori\u003c/em\u003e eradication therapy. If additional patients who underwent \u003cem\u003eH. pylori\u003c/em\u003e eradication during neoadjuvant chemotherapy could be included in the analysis, a more comprehensive exploration of the impact of \u003cem\u003eH. pylori\u003c/em\u003e eradication on the outcome of neoadjuvant chemotherapy could be performed. Therefore, we plan to conduct a prospective study to explore the impact of \u003cem\u003eH. pylori\u003c/em\u003e eradication in neoadjuvant chemotherapy on patient outcomes. Second, this was a single-center clinical retrospective study, which may be subject to selection bias. Finally, owing to the extended period of the study, variations in patients\u0026apos; surgical and postoperative treatments might have occurred with changes in treatment concepts.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, our study suggests that in patients with LAGC, \u003cem\u003eH. pylori\u003c/em\u003e infection may impede the efficacy of neoadjuvant chemotherapy, thereby affecting patient prognosis. More data are needed to support this conclusion through an in-depth validation and exploring the impact of \u003cem\u003eH. pylori\u003c/em\u003e eradication on neoadjuvant chemotherapy is also warranted.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAFP: Alpha-fetoprotein\u003c/p\u003e\n\u003cp\u003eBMI: Body mass index\u003c/p\u003e\n\u003cp\u003eCEA: Carcinoembryonic antigen\u003c/p\u003e\n\u003cp\u003eCA199: Cancer antigen 199\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCA125: Cancer antigen 125\u003c/p\u003e\n\u003cp\u003eCA153: Cancer antigen 153\u003c/p\u003e\n\u003cp\u003eCI: Confidence Internal\u003c/p\u003e\n\u003cp\u003eDFS: Disease-free survival\u003c/p\u003e\n\u003cp\u003edMMR: deficient Mismatch Repair\u003c/p\u003e\n\u003cp\u003eGC: Gastric cancer\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eH. pylori\u003c/em\u003e: \u003cem\u003eHelicobacter pylori\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eLAGC: Locally advanced gastric cancer\u003c/p\u003e\n\u003cp\u003eMPR:\u0026nbsp;Major pathological response\u003c/p\u003e\n\u003cp\u003eMMR: Mismatch repair\u003c/p\u003e\n\u003cp\u003eOS: Overall survival\u003c/p\u003e\n\u003cp\u003eOR: Odds Ratio\u003c/p\u003e\n\u003cp\u003epMMR: proficient Mismatch Repair\u003c/p\u003e\n\u003cp\u003ePCR: Pathological complete response\u003c/p\u003e\n\u003cp\u003eROC: Receiver operating characteristics curve\u003c/p\u003e\n\u003cp\u003eSTROBE: Strengthening the Reporting of Observational Studies in Epidemiology\u003c/p\u003e\n\u003cp\u003eTRG: Tumor regression grade\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor contributions\u003c/h2\u003e\n\u003cp\u003eConceptualization: LL, JP; Methodology: LL, HW; Formal analysis and investigation: ZX, JG; Writing-original draft preparation: BZ; Writing review and editing: LL, JZ, ZX, SM; Funding acquisition: LL; Resources: LL; Supervision: LL; Data curation: BZ, ZX, JS; Software: DH, BZ; Visualization: ZD, JZ, SM. Project administration: LL.\u003c/p\u003e\n\u003ch2\u003eAvailability of data and materials\u003c/h2\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis study was supported by the National Natural Science Foundation of China (grant nos. 82070684), and the Guangdong Natural Science Fund for Outstanding Youth Scholars (grant no. 2020B151502005).\u003c/p\u003e\n\u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e\n\u003cp\u003eThis retrospective study was approved by the Medical Research Ethics Committee of the Sixth Affiliated Hospital of Sun Yat-sen University. This study was conducted in compliance with the Helsinki Declaration. All included patients aged more than 18 years and written informed consent for anonymous collection and analysis of clinical data was provided by all patients before surgery in this retrospective cohort.\u003c/p\u003e\n\u003ch2\u003eConsent for publication\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021;71(3):209-49.\u003c/li\u003e\n\u003cli\u003eLiu D, Lu M, Li J, Yang Z, Feng Q, Zhou M, et al. The patterns and timing of recurrence after curative resection for gastric cancer in China. World journal of surgical oncology. 2016;14(1):305.\u003c/li\u003e\n\u003cli\u003eWang H, Guo W, Hu Y, Mou T, Zhao L, Chen H, et al. Superiority of the 8th edition of the TNM staging system for predicting overall survival in gastric cancer: Comparative analysis of the 7th and 8th editions in a monoinstitutional cohort. Molecular and clinical oncology. 2018;9(4):423-31.\u003c/li\u003e\n\u003cli\u003eCunningham D, Allum WH, Stenning SP, Thompson JN, Van de Velde CJ, Nicolson M, et al. Perioperative chemotherapy versus surgery alone for resectable gastroesophageal cancer. N Engl J Med. 2006;355(1):11-20.\u003c/li\u003e\n\u003cli\u003eKang YK, Yook JH, Park YK, Lee JS, Kim YW, Kim JY, et al. PRODIGY: A Phase III Study of Neoadjuvant Docetaxel, Oxaliplatin, and S-1 Plus Surgery and Adjuvant S-1 Versus Surgery and Adjuvant S-1 for Resectable Advanced Gastric Cancer. Journal of clinical oncology : official journal of the American Society of Clinical Oncology. 2021;39(26):2903-13.\u003c/li\u003e\n\u003cli\u003eZhang X, Liang H, Li Z, Xue Y, Wang Y, Zhou Z, et al. Perioperative or postoperative adjuvant oxaliplatin with S-1 versus adjuvant oxaliplatin with capecitabine in patients with locally advanced gastric or gastro-oesophageal junction adenocarcinoma undergoing D2 gastrectomy (RESOLVE): an open-label, superiority and non-inferiority, phase 3 randomised controlled trial. The Lancet Oncology. 2021;22(8):1081-92.\u003c/li\u003e\n\u003cli\u003eJiang Z, Xie Y, Zhang W, Du C, Zhong Y, Zhu Y, et al. Perioperative chemotherapy with docetaxel plus oxaliplatin and S-1 (DOS) versus oxaliplatin plus S-1 (SOX) for the treatment of locally advanced gastric or gastro-esophageal junction adenocarcinoma (MATCH): an open-label, randomized, phase 2 clinical trial. Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association. 2024;27(3):571-9.\u003c/li\u003e\n\u003cli\u003eLi S, Xu Q, Dai X, Zhang X, Huang M, Huang K, et al. Neoadjuvant Therapy with Immune Checkpoint Inhibitors in Gastric Cancer: A Systematic Review and Meta-Analysis. Annals of surgical oncology. 2023;30(6):3594-602.\u003c/li\u003e\n\u003cli\u003eChen YC, Malfertheiner P, Yu HT, Kuo CL, Chang YY, Meng FT, et al. Global Prevalence of Helicobacter pylori Infection and Incidence of Gastric Cancer Between 1980 and 2022. Gastroenterology. 2024;166(4):605-19.\u003c/li\u003e\n\u003cli\u003eGao S, Song D, Liu Y, Yan H, Chen X. Helicobacter pylori CagA Protein Attenuates 5-Fu Sensitivity of Gastric Cancer Cells Through Upregulating Cellular Glucose Metabolism. OncoTargets and therapy. 2020;13:6339-49.\u003c/li\u003e\n\u003cli\u003eChichirau BE, Diechler S, Posselt G, Wessler S. Tyrosine Kinases in Helicobacter pylori Infections and Gastric Cancer. Toxins. 2019;11(10).\u003c/li\u003e\n\u003cli\u003eGong X, Shen L, Xie J, Liu D, Xie Y, Liu D. Helicobacter pylori infection reduces the efficacy of cancer immunotherapy: A systematic review and meta-analysis. Helicobacter. 2023;28(6):e13011.\u003c/li\u003e\n\u003cli\u003eChoi Y, Kim N, Yun CY, Choi YJ, Yoon H, Shin CM, et al. Effect of Helicobacter pylori eradication after subtotal gastrectomy on the survival rate of patients with gastric cancer: follow-up for up to 15 years. Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association. 2020;23(6):1051-63.\u003c/li\u003e\n\u003cli\u003eZhao Z, Zhang R, Chen G, Nie M, Zhang F, Chen X, et al. Anti-Helicobacter pylori Treatment in Patients With Gastric Cancer After Radical Gastrectomy. JAMA network open. 2024;7(3):e243812.\u003c/li\u003e\n\u003cli\u003eAmin MB, Greene FL, Edge SB, Compton CC, Gershenwald JE, Brookland RK, et al. The Eighth Edition AJCC Cancer Staging Manual: Continuing to build a bridge from a population-based to a more \u0026quot;personalized\u0026quot; approach to cancer staging. CA Cancer J Clin. 2017;67(2):93-9.\u003c/li\u003e\n\u003cli\u003eWorld Medical Association Declaration of Helsinki: ethical principles for medical research involving human subjects. Jama. 2013;310(20):2191-4.\u003c/li\u003e\n\u003cli\u003evon Elm E, Altman DG, Egger M, Pocock SJ, G\u0026oslash;tzsche PC, Vandenbroucke JP. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Lancet (London, England). 2007;370(9596):1453-7.\u003c/li\u003e\n\u003cli\u003eWong IYH, Chung JCY, Zhang RQ, Gao X, Lam KO, Kwong DLW, et al. A Novel Tumor Staging System Incorporating Tumor Regression Grade (TRG) With Lymph Node Status (ypN-Category) Results in Better Prognostication Than ypTNM Stage Groups After Neoadjuvant Therapy for Esophageal Squamous Cell Carcinoma. Ann Surg. 2022;276(5):784-91.\u003c/li\u003e\n\u003cli\u003eHooi JKY, Lai WY, Ng WK, Suen MMY, Underwood FE, Tanyingoh D, et al. Global Prevalence of Helicobacter pylori Infection: Systematic Review and Meta-Analysis. Gastroenterology. 2017;153(2):420-9.\u003c/li\u003e\n\u003cli\u003eKang SY, Han JH, Ahn MS, Lee HW, Jeong SH, Park JS, et al. Helicobacter pylori infection as an independent prognostic factor for locally advanced gastric cancer patients treated with adjuvant chemotherapy after curative resection. Int J Cancer. 2012;130(4):948-58.\u003c/li\u003e\n\u003cli\u003eLan KH, Lee WP, Wang YS, Liao SX, Lan KH. Helicobacter pylori CagA protein activates Akt and attenuates chemotherapeutics-induced apoptosis in gastric cancer cells. Oncotarget. 2017;8(69):113460-71.\u003c/li\u003e\n\u003cli\u003eZhou X, Su J, Zhu L, Zhang G. Helicobacter pylori modulates cisplatin sensitivity in gastric cancer by down-regulating miR-141 expression. Helicobacter. 2014;19(3):174-81.\u003c/li\u003e\n\u003cli\u003eChoi IK, Sung HJ, Lee JH, Kim JS, Seo JH. The relationship between Helicobacter pylori infection and the effects of chemotherapy in patients with advanced or metastatic gastric cancer. Cancer chemotherapy and pharmacology. 2012;70(4):555-8.\u003c/li\u003e\n\u003cli\u003eNishizuka SS, Tamura G, Nakatochi M, Fukushima N, Ohmori Y, Sumida C, et al. Helicobacter pylori infection is associated with favorable outcome in advanced gastric cancer patients treated with S-1 adjuvant chemotherapy. Journal of surgical oncology. 2018;117(5):947-56.\u003c/li\u003e\n\u003cli\u003ePiessen G, Messager M, Leteurtre E, Jean-Pierre T, Mariette C. Signet ring cell histology is an independent predictor of poor prognosis in gastric adenocarcinoma regardless of tumoral clinical presentation. Ann Surg. 2009;250(6):878-87.\u003c/li\u003e\n\u003cli\u003eHeger U, Blank S, Wiecha C, Langer R, Weichert W, Lordick F, et al. Is preoperative chemotherapy followed by surgery the appropriate treatment for signet ring cell containing adenocarcinomas of the esophagogastric junction and stomach? Annals of surgical oncology. 2014;21(5):1739-48.\u003c/li\u003e\n\u003cli\u003eBecker K, Langer R, Reim D, Novotny A, Meyer zum Buschenfelde C, Engel J, et al. Significance of histopathological tumor regression after neoadjuvant chemotherapy in gastric adenocarcinomas: a summary of 480 cases. Ann Surg. 2011;253(5):934-9.\u003c/li\u003e\n\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":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Locally advanced gastric cancer, Helicobacter pylori, Neoadjuvant chemotherapy effect, Prognosis","lastPublishedDoi":"10.21203/rs.3.rs-4760812/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4760812/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003e\u003cem\u003eHelicobacter pylori\u003c/em\u003e (\u003cem\u003eH. pylori\u003c/em\u003e) infection may affect the efficacy of immunotherapy and adjuvant chemotherapy in gastric cancer patients. However, the role of \u003cem\u003eH. pylori\u003c/em\u003e infection in neoadjuvant chemotherapy in patients with locally advanced gastric cancer (LAGC) remains unclear. This study investigated the effect of \u003cem\u003eH. pylori\u003c/em\u003e infection on neoadjuvant chemotherapy and prognosis of patients with LAGC.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis retrospective study utilized data from patients with LAGC who underwent neoadjuvant chemotherapy and surgical treatment at the Sixth Affiliated Hospital of Sun Yat-sen University from January 1, 2010, to January 31, 2021. Patients were grouped according to their \u003cem\u003eH. pylori\u003c/em\u003e infection status. The responses of the two groups to neoadjuvant chemotherapy and oncological outcomes were then compared.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 239 patients were included in the analysis, and the baseline characteristics of the \u003cem\u003eH. pylori\u003c/em\u003e-positive (n\u0026thinsp;=\u0026thinsp;51) and \u003cem\u003eH. pylori\u003c/em\u003e-negative (n\u0026thinsp;=\u0026thinsp;188) groups were comparable. Further analysis revealed that \u003cem\u003eH. pylori\u003c/em\u003e infection was significantly associated with the major pathological response (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.009). Multivariate analysis showed that factors related to major pathological response included; age\u0026thinsp;\u0026le;\u0026thinsp;50 (OR: 0.423, 95% CI: 0.194\u0026ndash;0.925), \u003cem\u003eH. pylori\u003c/em\u003e infection (OR: 0.396, 95% CI: 0.183\u0026ndash;0.854), pathological stage T 3/4 (OR: 0.524, 95% CI: 0.288\u0026ndash;0.954), and CA125\u0026thinsp;\u0026gt;\u0026thinsp;35 U/mL (OR: 0.345, 95% CI: 0.132\u0026ndash;0.904). Both overall survival (OS) and disease-free survival (DFS) rates were poorer in the \u003cem\u003eH. pylori\u003c/em\u003e-positive group than in the \u003cem\u003eH. pylori\u003c/em\u003e-negative group (OS: Log-Rank \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.035; DFS: Log-Rank \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.029).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThis cohort study indicated that H. pylori infection may be associated with tumor response to neoadjuvant chemotherapy and survival outcomes in patients with LAGC.\u003c/p\u003e","manuscriptTitle":"Impact of Helicobacter pylori infection on neoadjuvant chemotherapy in locally advanced gastric cancer: a retrospective analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-18 23:08:50","doi":"10.21203/rs.3.rs-4760812/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-09-27T09:37:04+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-24T14:14:34+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"36677557512514674251691644079313013525","date":"2024-09-23T13:51:39+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-08T20:29:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"160469072482772411499215801286386827785","date":"2024-08-28T11:08:46+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"121026488952720080092879423423496132405","date":"2024-08-28T05:46:54+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-09T13:12:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"33837073207958249571398785998573913609","date":"2024-08-01T21:37:44+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-07-31T17:45:49+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-07-19T18:13:20+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-07-19T06:43:47+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-07-19T06:41:28+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cancer","date":"2024-07-18T07:46:10+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c625cdf6-5b99-4f42-98b1-bb328a5aa78a","owner":[],"postedDate":"August 18th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-02-03T16:08:50+00:00","versionOfRecord":{"articleIdentity":"rs-4760812","link":"https://doi.org/10.1186/s12885-025-13494-5","journal":{"identity":"bmc-cancer","isVorOnly":false,"title":"BMC Cancer"},"publishedOn":"2025-01-27 15:57:53","publishedOnDateReadable":"January 27th, 2025"},"versionCreatedAt":"2024-08-18 23:08:50","video":"","vorDoi":"10.1186/s12885-025-13494-5","vorDoiUrl":"https://doi.org/10.1186/s12885-025-13494-5","workflowStages":[]},"version":"v1","identity":"rs-4760812","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4760812","identity":"rs-4760812","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}