Systemic Immune-Inflammation Index After Neoadjuvant Therapy Predicts the Pathological Response in Patients with Resected Pancreatic Ductal Adenocarcinoma

Systemic Immune-Inflammation Index After Neoadjuvant Therapy Predicts the Pathological Response in Patients with Resected Pancreatic Ductal Adenocarcinoma | 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 Systemic Immune-Inflammation Index After Neoadjuvant Therapy Predicts the Pathological Response in Patients with Resected Pancreatic Ductal Adenocarcinoma Shuo Shen, Lingyu Zhu, Bo Li, Xiaoyi Yin, Xiaohan Shi, Suizhi Gao, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2856912/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Pancreatic ductal adenocarcinoma (PDAC) patients have improved prognosis after neoadjuvant therapy (NAT). However, there is a lack of biomarkers to predict the pathological response preoperatively. We evaluated the predictive value of multiple biomarkers, including inflammatory biomarkers, for predicting the pathological responses. Methods: We respectively reviewed the records of patients with localized PDAC who underwent NAT followed by resection between January 2017 and May 2021 at the First Affiliated Hospital of Naval Medical University. The patients were divided into the major pathological response (MPR) and non-MPR groups, according to the tumor regression grade. Univariate and multivariate predictors of MRP were explored. The predictive factors identified on multivariate analysis were used to establish a nomogram prognostic model, which was evaluated using the Decision Curve Analysis (DCA). Results: A total of 150 patients, including 21 in the MPR and 129 in the non-MPR group, were analyzed. In the multivariate analysis of the MRP group, normal CA19-9 level (<37U/ml)(odds ratio, OR = 32.014; 95% confidence interval (CI) = 3.809–269.071; p = 0.001), post-NAT SII < 530 (OR = 14.739; 95% CI = 2.811–77.265; p = 0.001), and use of Stereotactic Body Radiation Therapy (OR = 8.370; 95% CI = 2.175–32.205) predicted MPR in PDAC patients. DCA showed that the nomogram prognostic model had a higher predictive value than standard radiological assessments. Conclusions: In resected PDAC, post-NAT normal CA19-9 level, post-NAT SII, and use of Stereotactic Body Radiation Therapy predicted MPR after NAT in PDAC patients. Post-NAT SII can be used as a biomarker to determine the treatment response. Pancreatic cancer pathological response neoadjuvant therapy biomarker systemic immune-inflammation index Figures Figure 1 Figure 2 Figure 3 INTRODUCTION Despite therapeutic advances in recent years, pancreatic ductal adenocarcinoma (PDAC) remains one of the deadliest cancers worldwide, with a 5-year survival rate of < 10% 1 . Surgical resection is the only curative treatment for PDAC patients 2 . However, more than half of the patients have locally advanced disease or distant metastasis, which makes them unsuitable for radical resection. Even among patients who undergo surgery, a majority have local recurrence or metastasis within 2 years 3 . With the introduction of preoperative systemic treatment, including chemotherapy, radiotherapy, and chemoradiotherapy (also known as neoadjuvant therapy, NAT), the treatment of PDAC has been revolutionized. NAT increases the resection rate of PDAC, improves the R0 resection rate and negative lymph node rate, and leads to a better prognosis 4-6 . Therefore, NAT is being increasingly used in clinical practice. However, the assessment of therapeutic response during NAT is challenging. Pathological examination demonstrates tumor regression, which can be used as an indicator of therapeutic response. According to the College of American Pathologists (CAP), major pathological response (MPR) includes no viable cancer cells or single/rare groups of cancer cells. MPR has been proven to be independently associated with prolonged survival of PDAC patients after NAT 7-9 . However, these conclusions are based on an analysis of postoperative resected specimens. To decide regarding the choice of surgery, preoperative predictors of MPR in PDAC patients following NAT should be identified. Radiological examinations are routinely used to assess the restaging and resectability of tumors after NAT. For PDAC patients, there are only limited data that this method is associated with tumor regression 10-12 . In addition, there is a lack of studies on other biomarkers of tumor regression. Pancreatic cancer is a systematic disease and peripheral blood markers may reflect the tumor status. Inflammatory mediators play a significant role in the PDAC tumor microenvironment, which supports immunoregulatory adaptive immune responses, promotes the proliferation and growth of malignant cells, and reduces the efficacy of chemotherapy 13 . Inflammatory biomarkers obtained from the peripheral blood, such as neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII), are associated with the overall survival of PDAC patients 14-17 . Additionally, SII is associated with the prognosis of PDAC patients after NAT 18 . The influence of NAT on the inflammatory biomarkers and the predictive value of inflammatory biomarkers for the pathological response have not been explored to date. In this study, we retrospectively compared patients with MPR after NAT with those who did not achieve MPR in terms of differences in clinical characteristics, including inflammatory biomarkers. METHODS Study Patients We retrospectively reviewed our PDAC surgical database for consecutive patients with localized PDAC who underwent NAT followed by resection between January 2017 and May 2021 at the First Affiliated Hospital of Naval Medical University. Before NAT, all patients underwent endoscopic ultrasound and biopsy, which was analyzed by pathologists to confirm pancreatic cancer. The patients received at least three cycles of NAT based on gemcitabine, 5-fluorouracil, or both. After NAT, patients underwent radiological evaluation and those without disease progression underwent radical surgical resection. Those with pathologically confirmed PDAC were included in the study. We excluded patients who did not undergo radical resection or in whom postoperative pathological examination showed variant exocrine or intraductal papillary mucinous neoplasm. Pathological Evaluation Pathological evaluations were performed by independent pathologists. All patients had pathologically confirmed PDAC. The TNM stage was determined according to the 8th edition of the American Joint Committee on Cancer (AJCC) Staging System 19, 20 . TRG stage was identified on the basis of postoperative pathological sections by at least 2 independent pathologist, in accordance with the College of American Pathology (CAP) protocols 21 : complete response, score 0 (no viable cancer cells); near complete response, score 1 (single/rare groups of cancer cells); partial response, score 2 (residual cancer with regression); and poor/no response, score 3 (no tumor regression). MPR correlated with score 0 or 1. Data Collection We retrospectively collected the general patient information and laboratory and pathological examination results, including data related to demographic characteristics, treatment, tumor stage, tumor size, and tumor marker levels, from the electronic medical record system. Pre- and post-NAT imaging diagnosis and laboratory values were recorded within 15 days before NAT and 1 week before surgery. PDAC resectability was determined according to the National Comprehensive Cancer Network (NCCN) guidelines 22 . Tumor radiological response was assessed using the Response Evaluation Criteria in Solid Tumors (RECIST) version 1.120. The absolute platelet (P), neutrophil (N), and lymphocyte (L) counts were used to calculate the NLR (N/L), PLR (P/L), and SII (SII = P* [N/L]). The examination results exceeding the maximum value of the instrument range shall be calculated as the maximum value. Patients with post-NAT CA19-9 level < 37U/ml were considered CA19-9 normalized; however, five patients with CA 19-9 non-secretor (<secretion (< 2) were excluded from further CA 19-9 analyses. Statistical Analysis Categorical variables were displayed as frequencies (n) and percentages (%). Chi-square test or Fisher’s exact test was used to compare the groups. For continuous variables, normally distributed data were expressed as mean ± standard deviation. Student’s t-test was used to compare the differences between the groups. Meanwhile, non-normally distributed data are expressed as median (interquartile range [IQR]). Mann-Whitney U rank-sum test was used for the comparison between groups. The traditional receiver operating characteristic (ROC) curve was applied to determine the optimal cutoff value to predict MRP for the continuous variables. To identify predictive factors of MPR, univariate and multivariate logistic regression analyses were performed, and odds ratio (OR) and 95% CI were calculated. A two-sided p-value < 0.05 was considered statistically significant. The independent predictive factors were used to establish a nomogram prognostic model, and the performance of this model was compared to that of the standard radiological assessments using a Decision Curve Analysis (DCA). All statistical analyses were performed using SPSS software (version 25.0; IBM Corp., Armonk, NY, USA) and R software (version 4.1.0; R Foundation for Statistical Computing, Vienna, Austria). RESULTS Demographic and Perioperative Data Patient demographics and clinical characteristics are shown in Table 1. Of the 150 patients included in this study, 21 (14.0%) had MPR. No significant difference was found between the MPR and non-MPR groups in terms of age (61.0 ± 8.6 and 59.0 ± 8.6, respectively; p = 0.337), gender (male%: 52.4 and 60.5, respectively; p = 0.485), BMI (22.4 ± 2.8 and 23.2 ± 2.7, respectively; p = 0.490), tumor size (3.0 ± 1.3 and 3.6 ± 1.5, respectively; p = 0.209), and resectability (p = 0.698). However, 7 out of 21 patients (33.3%) in the MPR group had received 5FU-based regimen, which was statistically different from the non-MPR group (p = 0.010). However, there was no evidence that NAT cycles prolonged to more than four cycles could be beneficial for pathologic response (33.3% and 48.8%, respectively; p = 0.240). However, preoperative stereotactic body radiation therapy (SBRT) was associated with a better pathologic response (81.0% and 31.0%, respectively; p < 0.001). Based on the RECIST grade, none of the patients had complete response (CR) or progressive disease (PD) in the two groups. However, the MPR group had a better regression grade than the non-MPR group (p = 0.003). Pathological Characteristics The MPR group consisted of 4 TRG-0 cases and 17 TRG-1 cases. In contrast, the non-MRP group consisted of 81 TRG-2 cases and 48 TRG-3 cases. As shown in Table 2, the pathological examination showed that there was no difference in tumor position between the two groups. T staging in the MPR group was significantly lower than that in the non-MPR group (p = 0.001). A similar difference was also found in N staging (p = 0.002). Furthermore, there was a statistical difference in the lymph node positive rate between the MPR and non-MPR groups (19.0% and 55.8%, respectively; p = 0.002). The MPR group showed less perineural invasion compared to the non-MPR group (42.9% and 94.6%, respectively; p < 0.001). Clinical Predictors of MPR Pre-NAT CEA level (p = 0.008), post-NAT CA19-9 level (p < 0.001), and minimum CA19-9 value (p < 0.001) were associated with MPR. In addition, post-NAT CA19-9 normalization predicted MPR (p < 0.001). However, pre-NAT NLR, PLR, and SII did not show any statistical difference between the MPR and non-MPR groups. Nevertheless, post-NAT PLR (p = 0.021) and SII (p = 0.005) predicted MPR. Other tumor and inflammatory markers did not correlate with MPR pre- or post- NAT. The MRP group had a better radiological response compared to the non-MPR group according to the RECIST criteria (p = 0.005). According to the ROC curve, the optimal cutoff values of post-NAT PLR and post-NAT SII were 149 and 530, respectively. The corresponding areas under the curve (AUC) for post-NAT PLR and post-NAT SII were 0.658 and 0.690, respectively. The Jordon indexes for post-NAT PLR and post-NAT SII were 0.265 and 0.362, respectively. Based on the optimal cutoff value of post-NAT PLR and SII, the patients were divided into high and low groups. The ROC curves for post-NAT SII and PLR are shown in Figure 1. Univariate and Multivariate Analyses of MPR Based on the aforementioned results, univariate and multivariate logistic regression analyses of predictors of MPR were performed (Table 3). Univariate analysis showed that SBRT use (odds ratio, OR = 9.456; 95% CI = 2.990–29.904; p < 0.001) was related to MRP. Lower post-NAT CA19-9 level (OR = 1.029; 95% CI = 1.005–1.053; p = 0.018), lower minimum CA19-9 level (OR = 1.029; 95% CI = 1.004–1.055; p = 0.021), and CA19-9 normalization (OR = 25.962; 95% CI = 3.361–200.560; p = 0.002) also predicted MRP. Inflammatory markers, such as lower post-NAT SII (OR = 8.007; 95% CI = 1.791–35.801; p = 0.006), were also associated with MRP. In addition, RECIST grade (OR = 4.400; 95% CI = 1.649 = 11.738; p = 0.003) also predicted MPR in the univariate analysis. However, in the multivariate analysis of the MRP cohort, only CA19-9 normalization (OR = 32.014; 95% CI = 3.809–269.071; p = 0.001), post-NAT SII < 530 (OR = 14.739; 95% CI = 2.811–77.265; p = 0.001), and SBRT use (OR = 8.370; 95% CI = 2.175–32.205) predicted MPR in PDAC patients. Nomogram Prediction Model Based on the univariate analysis, CA19-9 normalization, post-NAT SII < 530, and SBRT use were used to establish a nomogram prediction model for MPR using the R software. DCA was used to compare the prediction value of nomogram model and the RECIST grade. The results showed that the AUC of the nomogram model, based on the three predictive factors, was significantly greater than that of the RECIST grade (Figure 2). Therefore, our nomogram model was more accurate for the prediction of MRP than the RECIST grade. DISCUSSION Several studies have demonstrated that PDAC patients may benefit from NAT compared to upfront surgery 5, 23, 24 . NAT is increasingly being used for many PDAC patients. However, one of the current problems of NAT is the lack of accurate evaluation methods that can accurately assess the treatment effect of NAT. As the direct evidence of NAT treatment effect, tumor pathological response cannot be determined preoperatively and can only be detected in resected PDAC samples. Radiological examinations are frequently used, but there is no evidence that radiological tumor regression after NAT predicts MPR. Even among patients with significant pathological response to NAT, radiological findings may not detect a significant change 25 . Our result revealed that although univariate analysis showed predictive value of RECIST grade for MPR, the multivariate analysis showed no significant difference in the RECIST grade between the MRP and non-MPR groups. We excluded patients with obvious disease progression from undergoing surgery; therefore, the study did not include PD patients. In our study, more than half of the patients presented with SD after NAT, and 33.3% of MPR patients had unchanged radiological examinations. For patients with unavailable radiological response to tumor treatment, this method was not sufficient to predict the pathological response. The commonly used tumor markers, especially CA19-9, predicted the response to NAT 25 . However, 5–10% of the population does not secrete CA19-9 and it can be affected by numerous non-tumor factors. Therefore, relying on this biomarker alone is not sufficient to predict the treatment response of all patients. Thus, there is an urgent need to identify other biomarkers that can preoperatively predict the pathological response to help in selecting a treatment strategy and surgery timing for these patients. This study aimed to identify potential biomarkers of MPR in patients with PDAC who received NAT before surgical resection. Our results showed that post-NAT CA19-9 normalization also predicted MPR in PDAC patients who received NAT. The optimal post-NAT CA19-9 response was independently associated with progression-free and overall survival of PDAC patients 7, 8 . The NCCN guidelines recommend that patients with resectable/borderline resectable disease whose CA 19-9 level is stable or has decreased, and patients with locally advanced disease who have a > 50% decrease in CA19-9 level, should be considered for surgical explorations when radiographic progression has been excluded. Based on our results, CA19-9 normalization was the most significant factor. Tsai et al. reported that the normalization of CA19-9 level is the strongest prognostic marker for survival following NAT 26 . We agree with the aforementioned evidence; CA19-9 normalization is an indication of MPR, which also affects the prognosis. Thus, reducing post-NAT CA19-9 levels to the normal should be one of the main goals of NAT. However, this does not apply to patients who are CA 19-9 non-secretors or those who have normal CA 19-9 levels. SBRT use is also a predictive factor for MPR. It is unclear whether radiotherapy should to be part of neoadjuvant therapy for pancreatic cancer. In spite of differences in radiotherapy regimen and dose, most studies of NAT have showed its benefit for postoperative survival and R0 resection rate 27, 28 . Chen-Zhao et al. reported that out of 32 patients who underwent surgery following SBRT, 12 (37.5%) had complete or near complete response (TRG 0–1) 29 . Although the NCCN guidelines regarding the use of neoadjuvant radiotherapy are controversial, our results prove that SBRT use may be beneficial for pathological regression and may be used as NAT for pancreatic cancer. However, its application is limited by the tumor location, physical status, and financial situation. Currently, we are conducting a randomized controlled clinical trial of SBRT, which is yet to be published 30 . Inflammatory biomarkers, such as SII, can be calculated on the basis of counts of blood components, which can easily be obtained from blood routine examination, such as lymphocytes, neutrophils, platelets, and C-reactive protein. Among these biomarkers, NLR, PLR, and SII was associated with the prognosis of solid tumors, such as hepatocellular carcinoma, renal cell carcinoma, oral cavity squamous cell carcinoma, and laryngeal squamous cell carcinoma 31-34 . For PDAC patients, Jomrich et al. reported that SII has a greater ability to independently predict the prognosis of resectable PDAC patients compared to NLR and PLR 35 . Additionally, Murthy et al. reported that post-treatment SII may be a useful prognostic marker in PDAC patients receiving NAT 35 . In contrast to a recent study of SII in PDAC patients, our results showed that a high level of post-NAT SII (> 530), rather than pre-NAT SII, could predict MPR (OR = 5.475; 95% CI = 1.278–23.462). Therefore, it is reasonable to assume that SII is a potentially useful biomarker to predict treatment response to NAT in PDAC patients. Figure 3 shows the alterations in SII in two typical PDAC patients during NAT. PC-94 was a 54-year-old male patient with PDAC. This patient was diagnosed with borderline resectable PDAC and underwent six cycles of AG (Gemcitabine/Albumin-Paclitaxel) NAT regimen, which led to a significant decrease in the CA19-9 and SII levels. Radiological examination did not reveal significant tumor regression. This patient underwent surgery after SBRT. Postoperative pathological examination showed no viable residual tumor cells, and TRG was 0. In contrast to PC-94, PC-71 is a 68-year-old male patient with a borderline resectable tumor. The patient’s CA19-9 level was within the normal range before NAT and normalized after six cycles of AG NAT regimen. There was no significant change in the tumor size. However his SII level continued to increase during NAT. Surgery was also performed in this patient after SBRT. However, postoperative pathological examination did not reveal any obvious tumor cells with regression, with a TRG grade of 3. Based on the above two patients, we believe that SII can provide a reference for the pathological responses when tumor markers and radiological examinations are unable to fully evaluate the patient. Analyses of the cause of post-NAT SII level affects the pathologic response in PDAC. Elevated neutrophil levels are the most significant change in inflammation and promote tumor cell proliferation, whereas cancer-related neutrophils increase or suppresses host immunity by inhibiting T cell activation and recruiting regulatory T cells; neutrophils use neutrophil extracellular traps (nets) to isolate circulating cancer cells and stimulate cancer cell migration and invasion36. Platelet activation results in a hypercoagulable state; this hypercoagulable state in PDAC may form a defensive barrier around the circulating tumor cells, allowing tumor cells to escape immune surveillance and promote tumor growth and metastasis 37, 38 . Platelet activation promotes tumor growth and metastasis by binding to tumor cells and secreting angiogenic and tumor-derived growth factors 39 . Decreased lymphocyte counts indicate suppressed immune system function and provide a good microenvironment for the proliferation of circulating tumor cells. Chronic inflammation is closely related to the development of PDAC and it can promote cell proliferation, invasion, migration, metastasis, and malignant change of chronic pancreatitis or epithelial cells, which is known to be a risk factor for PDAC 40 . We hypothesized that the inflammatory biomarker SII reflects the risk of PDAC growth and metastasis. Therefore, patients with MPR have a low SII level, which may be because of low tumor burden. There were several limitations of this study. The patients were highly selected and we only included those patients who were able to undergo radical resection after NAT, failed to respond to NAT, showed diseases progression, or have unresectable tumor during surgery. The fluctuation in SII during NAT was not explored. Because of the small number of cases, different treatment regimens could not be evaluated. This was a single-center retrospective study. Therefore, further prospective multicenter studies are needed to confirm the role of SII in NAT. CONCLUSION This study suggests that post-NAT CA19-9 normalization, post-NAT SII, and RECIST grade were predictors of MPR after NAT in PDAC patients. Although it cannot replace the role of CA19-9, post-NAT SII may be used as an important biomarker to assess treatment response. Declarations Ethics approval and consent to participate ： The studies involving human participants were reviewed and approved by the Institutional Review Board of Changhai Hospital (No.CHEC-Y2020-043). All methods were carried out in accordance with declaration of Helsinki. The need for informed consent was waived by the Institutional Review Board of Changhai Hospital (No.CHEC-Y2020-043). Consent for publication: Not applicable. Availability of data and materials: The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request. Competing interests: The authors report no conflicts of interest. Funding: This work was supported by 234 Disciplines Climbing Plan (No.2019YXK033), Shanghai Science and Technology Innovation Action Plan 2020 (No.20511101200) and Shanghai Shenkang Hospital Development Center (No.SHDC2020CR2001A). Authors' contributions ： All authors made substantial contributions to the conception and design, and/or acquisition of data, analysis and interpretation of data. All authors participated in drafting the article and revising it critically for important intellectual content and gave final approval of the version to be published. Acknowledgements : Not applicable. References Siegel RL, Miller KD, Jemal A. Cancer statistics, 2020. CA: A Cancer Journal for Clinicians. 2020; 70: 7-30. Hidalgo M. Pancreatic Cancer. NEW ENGL J MED. 2010; 362: 1605-17. Cameron JL, Riall TS, Coleman J, Belcher KA. One Thousand Consecutive Pancreaticoduodenectomies. ANN SURG. 2006; 244: 10-15. Heinemann V, Haas M, Boeck S. Neoadjuvant treatment of borderline resectable and non-resectable pancreatic cancer. ANN ONCOL. 2013; 24: 2484-92. Versteijne E, Vogel JA, Besselink MG, Busch ORC, Wilmink JW, Daams JG, et al.. 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Dashevsky O, Varon D, Brill A. Platelet-derived microparticles promote invasiveness of prostate cancer cellsvia upregulation of MMP-2 production. INT J CANCER. 2009; 124: 1773-77. Zheng Z, Chen Y, Tan C, Ke N, Du B, Liu X. Risk of pancreatic cancer in patients undergoing surgery for chronic pancreatitis. BMC SURG. 2019; 19: 83. Tables Table 1 to 3 are available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Table1.xlsx Table2.xlsx Table3.xlsx Cite Share Download PDF Status: Posted Version 1 posted 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. 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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-2856912","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":197850170,"identity":"e097b5e7-83b8-489a-a69c-a802103406b4","order_by":0,"name":"Shuo Shen","email":"","orcid":"","institution":"First Affiliated Hospital of Naval Medical University (Second Military Medical University)","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Shuo","middleName":"","lastName":"Shen","suffix":""},{"id":197850171,"identity":"b4cdcf64-fc5d-4b58-97e2-61b89e488d1e","order_by":1,"name":"Lingyu Zhu","email":"","orcid":"","institution":"First Affiliated Hospital of Naval Medical University (Second Military Medical University)","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Lingyu","middleName":"","lastName":"Zhu","suffix":""},{"id":197850172,"identity":"fe01f231-9623-4188-ab16-8fb5402ba7f9","order_by":2,"name":"Bo Li","email":"","orcid":"","institution":"First Affiliated Hospital of Naval Medical University (Second Military Medical University)","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Bo","middleName":"","lastName":"Li","suffix":""},{"id":197850173,"identity":"f8077f91-47ea-4a5c-9118-e845ce7deed9","order_by":3,"name":"Xiaoyi Yin","email":"","orcid":"","institution":"First Affiliated Hospital of Naval Medical University (Second Military Medical 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Wang","email":"","orcid":"","institution":"First Affiliated Hospital of Naval Medical University (Second Military Medical University)","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Huan","middleName":"","lastName":"Wang","suffix":""},{"id":197850177,"identity":"0c038454-d3e3-473d-bb73-631a7c73c731","order_by":7,"name":"Guoxiao Zhang","email":"","orcid":"","institution":"First Affiliated Hospital of Naval Medical University (Second Military Medical University)","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Guoxiao","middleName":"","lastName":"Zhang","suffix":""},{"id":197850178,"identity":"027388e2-f59e-4224-948c-7f4e63cd10d6","order_by":8,"name":"Wei Jing","email":"","orcid":"","institution":"First Affiliated Hospital of Naval Medical University (Second Military Medical 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Guo","email":"","orcid":"","institution":"First Affiliated Hospital of Naval Medical University (Second Military Medical University)","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Shiwei","middleName":"","lastName":"Guo","suffix":""},{"id":197850182,"identity":"ca6b4dca-8af4-445a-943d-c327e44c0ca9","order_by":12,"name":"Gang Jin","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0ElEQVRIiWNgGAWjYBACxmYILQflMxOvxZh4LTCQ2EC0FuZ23sMvfu6oTZ8/7XSaBEOFdWID+9kDBBzGl2bZe+Z47obbudskGM6kJzbw5CUQ0MJjZsDbdix3gzRQC2Pb4cQGCR4DgloM/7YdS5efDdLyjzgtxo9522oSGEAOY2wg0hZm2bYDhkC/bLZIOJZu3MaTg1+LYf8Z449v2+rkgQ7beONDjbVsP/sZAloaGNgkGBgOQ3gJQMyGVz0QyAOj5gMDQx0hdaNgFIyCUTCSAQAkZUQnw/d11gAAAABJRU5ErkJggg==","orcid":"","institution":"First Affiliated Hospital of Naval Medical University (Second Military Medical University)","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Gang","middleName":"","lastName":"Jin","suffix":""}],"badges":[],"createdAt":"2023-04-25 02:14:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2856912/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2856912/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":36757190,"identity":"3337783b-35fb-4d86-ba2b-9e255ef56e4c","added_by":"auto","created_at":"2023-05-09 20:04:24","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":13917,"visible":true,"origin":"","legend":"\u003cp\u003eValue of area under the ROC curve for post-NAT SII and post-NAT PLR. The AUC of ROC curve went up to 0.690 (95% CI = 0.582–0.798, p=0.005) for post-NAT SII and 0.743 (95 % CI =\u003c/p\u003e\n\u003cp\u003e0.538–0.777, p=0.021) for post-NAT SII. The optimal cutoff value was 530 blood for post-NAT SII and 149 for post-NAT PLR.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-2856912/v1/777e9318f779ddcf21b39b71.png"},{"id":36757189,"identity":"a6d668b4-74f4-4344-b8fb-742e5687351e","added_by":"auto","created_at":"2023-05-09 20:04:24","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":40020,"visible":true,"origin":"","legend":"\u003cp\u003ethe prediction value of nomogram model (combined CA19-9 normalization, post-NAT SII \u0026lt; 530 and SBRT) and the RECIST grade by DCA. It can be seen that the AUC of the nomogram model was greater than that of the RECIST grade.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-2856912/v1/2c0fc4c670e9ea320fc05920.png"},{"id":36757977,"identity":"dc9bd6f8-6562-4fe8-b146-7ad5c5a28a3f","added_by":"auto","created_at":"2023-05-09 20:12:24","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":331666,"visible":true,"origin":"","legend":"\u003cp\u003eVariations in CA199,SII and radiological examinations during NAT in representative cases. (A) PC-94 showed a significant decrease in the CA19-9 and SII levels however radiological examination did not reveal significant tumor regression. And Postoperative pathological examination confirmed TRG was 0 which means complete response. (B) PC-71’s CA19-9 level was within the normal range, but his SII level continued to increase during NAT. Limited tumor regression was revealed in radiological examination. Eventually, postoperative pathological examination did not reveal any obvious tumor cells with regression, and no MPR achieved.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-2856912/v1/5071b091ed1a404192fb48ab.png"},{"id":67475829,"identity":"d56c9c3a-f914-4d22-9a32-cd7c25027d91","added_by":"auto","created_at":"2024-10-25 12:32:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":909264,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2856912/v1/12249f48-722c-43a3-a56b-1360fb722fd1.pdf"},{"id":36757191,"identity":"d1d7bd0e-2820-4d69-89f5-cebcf253f4f8","added_by":"auto","created_at":"2023-05-09 20:04:24","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":15213,"visible":true,"origin":"","legend":"","description":"","filename":"Table1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-2856912/v1/d32df7305e5c18c5bb73b0a5.xlsx"},{"id":36757194,"identity":"d4b8a8f5-7506-4b67-9ed5-3d5a7fcb8f1d","added_by":"auto","created_at":"2023-05-09 20:04:24","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":12131,"visible":true,"origin":"","legend":"","description":"","filename":"Table2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-2856912/v1/97df97405382ea4fd450b8e6.xlsx"},{"id":36757976,"identity":"086659f5-b941-4f26-830d-84c69c4cfc88","added_by":"auto","created_at":"2023-05-09 20:12:24","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":12093,"visible":true,"origin":"","legend":"","description":"","filename":"Table3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-2856912/v1/f48413015fea23c53ff14e62.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Systemic Immune-Inflammation Index After Neoadjuvant Therapy Predicts the Pathological Response in Patients with Resected Pancreatic Ductal Adenocarcinoma","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eDespite therapeutic advances in recent years, pancreatic ductal adenocarcinoma (PDAC) remains one of the deadliest cancers worldwide, with a 5-year survival rate of \u0026lt; 10%\u003csup\u003e1\u003c/sup\u003e. Surgical resection is the only curative treatment for PDAC patients\u003csup\u003e2\u003c/sup\u003e. However, more than half of the patients have locally advanced disease or distant metastasis, which makes them unsuitable for radical resection. Even among patients who undergo surgery, a majority have local recurrence or metastasis within 2 years\u003csup\u003e3\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eWith the introduction of preoperative systemic treatment, including chemotherapy, radiotherapy, and chemoradiotherapy (also known as neoadjuvant therapy, NAT), the treatment of PDAC has been revolutionized. NAT increases the resection rate of PDAC, improves the R0 resection rate and negative lymph node rate, and leads to a better prognosis\u003csup\u003e4-6\u003c/sup\u003e. Therefore, NAT is being increasingly used in clinical practice.\u003c/p\u003e\n\u003cp\u003eHowever, the assessment of therapeutic response during NAT is challenging. Pathological examination demonstrates tumor regression, which can be used as an indicator of therapeutic response. According to the College of American Pathologists (CAP), major pathological response (MPR) includes no viable cancer cells or single/rare groups of cancer cells. MPR has been proven to be independently associated with prolonged survival of PDAC patients after NAT\u003csup\u003e7-9\u003c/sup\u003e. However, these conclusions are based on an analysis of postoperative resected specimens. To decide regarding the choice of surgery, preoperative predictors of MPR in PDAC patients following NAT should be identified. Radiological examinations are routinely used to assess the restaging and resectability of tumors after NAT. For PDAC patients, there are only limited data that this method is associated with tumor regression\u003csup\u003e10-12\u003c/sup\u003e. In addition, there is a lack of studies on other biomarkers of tumor regression.\u003c/p\u003e\n\u003cp\u003ePancreatic cancer is a systematic disease and peripheral blood markers may reflect the tumor status. Inflammatory mediators play a significant role in the PDAC tumor microenvironment, which supports immunoregulatory adaptive immune responses, promotes the proliferation and growth of malignant cells, and reduces the efficacy of chemotherapy\u003csup\u003e13\u003c/sup\u003e. Inflammatory biomarkers obtained from the peripheral blood, such as neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII), are associated with the overall survival of PDAC patients\u003csup\u003e14-17\u003c/sup\u003e. Additionally, SII is associated with the prognosis of PDAC patients after NAT\u003csup\u003e18\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThe influence of NAT on the inflammatory biomarkers and the predictive value of inflammatory biomarkers for the pathological response have not been explored to date. In this study, we retrospectively compared patients with MPR after NAT with those who did not achieve MPR in terms of differences in clinical characteristics, including inflammatory biomarkers.\u003c/p\u003e"},{"header":"METHODS","content":"\u003ch2\u003eStudy Patients\u003c/h2\u003e\n\u003cp\u003eWe retrospectively reviewed our PDAC surgical database for consecutive patients with localized PDAC who underwent NAT followed by resection between January 2017 and May 2021 at the First Affiliated Hospital of Naval Medical University. Before NAT, all patients underwent endoscopic ultrasound and biopsy, which was analyzed by pathologists to confirm pancreatic cancer. The patients received at least three cycles of NAT based on gemcitabine, 5-fluorouracil, or both. After NAT, patients underwent radiological evaluation and those without disease progression underwent radical surgical resection. Those with pathologically confirmed PDAC were included in the study. We excluded patients who did not undergo radical resection or in whom postoperative pathological examination showed variant exocrine or intraductal papillary mucinous neoplasm.\u003c/p\u003e\n\u003ch2\u003ePathological Evaluation\u003c/h2\u003e\n\u003cp\u003ePathological evaluations were performed by independent pathologists. All patients had pathologically confirmed PDAC. The TNM stage was determined according to the 8th edition of the American Joint Committee on Cancer (AJCC) Staging System\u003csup\u003e19, 20\u003c/sup\u003e. TRG stage was identified on the basis of postoperative pathological sections by at least 2 independent pathologist, in accordance with the College of American Pathology (CAP) protocols\u003csup\u003e21\u003c/sup\u003e: complete response, score 0 (no viable cancer cells); near complete response, score 1 (single/rare groups of cancer cells); partial response, score 2 (residual cancer with regression); and poor/no response, score 3 (no tumor regression). MPR correlated with score 0 or 1.\u003c/p\u003e\n\u003ch2\u003eData Collection\u003c/h2\u003e\n\u003cp\u003eWe retrospectively collected the general patient information and laboratory and pathological examination results, including data related to demographic characteristics, treatment, tumor stage, tumor size, and tumor marker levels, from the electronic medical record system. Pre- and post-NAT imaging diagnosis and laboratory values were recorded within 15 days before NAT and 1 week before surgery. PDAC resectability was determined according to the National Comprehensive Cancer Network (NCCN) guidelines\u003csup\u003e22\u003c/sup\u003e. Tumor radiological response was assessed using the Response Evaluation Criteria in Solid Tumors (RECIST) version 1.120. The absolute platelet (P), neutrophil (N), and lymphocyte (L) counts were used to calculate the NLR (N/L), PLR (P/L), and SII (SII = P* [N/L]). The examination results exceeding the maximum value of the instrument range shall be calculated as the maximum value. Patients with post-NAT CA19-9 level \u0026lt; 37U/ml were considered CA19-9 normalized; however, five patients with CA 19-9 non-secretor (\u0026lt;secretion (\u0026lt; 2) were excluded from further CA 19-9 analyses.\u003c/p\u003e\n\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\n\u003cp\u003eCategorical variables were displayed as frequencies (n) and percentages (%). Chi-square test or Fisher\u0026rsquo;s exact test was used to compare the groups. For continuous variables, normally distributed data were expressed as mean \u0026plusmn; standard deviation. Student\u0026rsquo;s t-test was used to compare the differences between the groups. Meanwhile, non-normally distributed data are expressed as median (interquartile range [IQR]). Mann-Whitney U rank-sum test was used for the comparison between groups. The traditional receiver operating characteristic (ROC) curve was applied to determine the optimal cutoff value to predict MRP for the continuous variables. To identify predictive factors of MPR, univariate and multivariate logistic regression analyses were performed, and odds ratio (OR) and 95% CI were calculated. A two-sided p-value \u0026lt; 0.05 was considered statistically significant. The independent predictive factors were used to establish a nomogram prognostic model, and the performance of this model was compared to that of the standard radiological assessments using a Decision Curve Analysis (DCA). All statistical analyses were performed using SPSS software (version 25.0; IBM Corp., Armonk, NY, USA) and R software (version 4.1.0; R Foundation for Statistical Computing, Vienna, Austria).\u003c/p\u003e"},{"header":"RESULTS","content":"\u003ch2\u003eDemographic and Perioperative Data\u003c/h2\u003e\n\u003cp\u003ePatient demographics and clinical characteristics are shown in Table 1. Of the 150 patients included in this study, 21 (14.0%) had MPR. No significant difference was found between the MPR and non-MPR groups in terms of age (61.0 \u0026plusmn; 8.6 and 59.0 \u0026plusmn; 8.6, respectively; p = 0.337), gender (male%: 52.4 and 60.5, respectively; p = 0.485), BMI (22.4 \u0026plusmn; 2.8 and 23.2 \u0026plusmn; 2.7, respectively; p = 0.490), tumor size (3.0 \u0026plusmn; 1.3 and 3.6 \u0026plusmn; 1.5, respectively; p = 0.209), and resectability (p = 0.698). However, 7 out of 21 patients (33.3%) in the MPR group had received 5FU-based regimen, which was statistically different from the non-MPR group (p = 0.010). However, there was no evidence that NAT cycles prolonged to more than four cycles could be beneficial for pathologic response (33.3% and 48.8%, respectively; p = 0.240). However, preoperative stereotactic body radiation therapy (SBRT) was associated with a better pathologic response (81.0% and 31.0%, respectively; p \u0026lt; 0.001). Based on the RECIST grade, none of the patients had complete response (CR) or progressive disease (PD) in the two groups. However, the MPR group had a better regression grade than the non-MPR group (p = 0.003).\u003c/p\u003e\n\u003ch2\u003ePathological Characteristics\u003c/h2\u003e\n\u003cp\u003eThe MPR group consisted of 4 TRG-0 cases and 17 TRG-1 cases. In contrast, the non-MRP group consisted of 81 TRG-2 cases and 48 TRG-3 cases. As shown in Table 2, the pathological examination showed that there was no difference in tumor position between the two groups. T staging in the MPR group was significantly lower than that in the non-MPR group (p = 0.001). A similar difference was also found in N staging (p = 0.002). Furthermore, there was a statistical difference in the lymph node positive rate between the MPR and non-MPR groups (19.0% and 55.8%, respectively; p = 0.002). The MPR group showed less perineural invasion compared to the non-MPR group (42.9% and 94.6%, respectively; p \u0026lt; 0.001).\u003c/p\u003e\n\u003ch2\u003eClinical Predictors of MPR\u003c/h2\u003e\n\u003cp\u003ePre-NAT CEA level (p = 0.008), post-NAT CA19-9 level (p \u0026lt; 0.001), and minimum CA19-9 value (p \u0026lt; 0.001) were associated with MPR. In addition, post-NAT CA19-9 normalization predicted MPR (p \u0026lt; 0.001). However, pre-NAT NLR, PLR, and SII did not show any statistical difference between the MPR and non-MPR groups. Nevertheless, post-NAT PLR (p = 0.021) and SII (p = 0.005) predicted MPR. Other tumor and inflammatory markers did not correlate with MPR pre- or post- NAT. The MRP group had a better radiological response compared to the non-MPR group according to the RECIST criteria (p = 0.005). According to the ROC curve, the optimal cutoff values of post-NAT PLR and post-NAT SII were 149 and 530, respectively. The corresponding areas under the curve (AUC) for post-NAT PLR and post-NAT SII were 0.658 and 0.690, respectively. The Jordon indexes for post-NAT PLR and post-NAT SII were 0.265 and 0.362, respectively. Based on the optimal cutoff value of post-NAT PLR and SII, the patients were divided into high and low groups. The ROC curves for post-NAT SII and PLR are shown in Figure 1.\u003c/p\u003e\n\u003ch2\u003eUnivariate and Multivariate Analyses of MPR\u003c/h2\u003e\n\u003cp\u003eBased on the aforementioned results, univariate and multivariate logistic regression analyses of predictors of MPR were performed (Table 3). Univariate analysis showed that SBRT use (odds ratio, OR = 9.456; 95% CI = 2.990\u0026ndash;29.904; p \u0026lt; 0.001) was related to MRP. Lower post-NAT CA19-9 level (OR = 1.029; 95% CI = 1.005\u0026ndash;1.053; p = 0.018), lower minimum CA19-9 level (OR = 1.029; 95% CI = 1.004\u0026ndash;1.055; p = 0.021), and CA19-9 normalization (OR = 25.962; 95% CI = 3.361\u0026ndash;200.560; p = 0.002) also predicted MRP. Inflammatory markers, such as lower post-NAT SII (OR = 8.007; 95% CI = 1.791\u0026ndash;35.801; p = 0.006), were also associated with MRP. In addition, RECIST grade (OR = 4.400; 95% CI = 1.649 = 11.738; p = 0.003) also predicted MPR in the univariate analysis. However, in the multivariate analysis of the MRP cohort, only CA19-9 normalization (OR = 32.014; 95% CI = 3.809\u0026ndash;269.071; p = 0.001), post-NAT SII \u0026lt; 530 (OR = 14.739; 95% CI = 2.811\u0026ndash;77.265; p = 0.001), and SBRT use (OR = 8.370; 95% CI = 2.175\u0026ndash;32.205) predicted MPR in PDAC patients.\u003c/p\u003e\n\u003ch2\u003eNomogram Prediction Model\u003c/h2\u003e\n\u003cp\u003eBased on the univariate analysis, CA19-9 normalization, post-NAT SII \u0026lt; 530, and SBRT use were used to establish a nomogram prediction model for MPR using the R software. DCA was used to compare the prediction value of nomogram model and the RECIST grade. The results showed that the AUC of the nomogram model, based on the three predictive factors, was significantly greater than that of the RECIST grade (Figure 2). Therefore, our nomogram model was more accurate for the prediction of MRP than the RECIST grade.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eSeveral studies have demonstrated that PDAC patients may benefit from NAT compared to upfront surgery\u003csup\u003e5, 23, 24\u003c/sup\u003e. NAT is increasingly being used for many PDAC patients. However, one of the current problems of NAT is the lack of accurate evaluation methods that can accurately assess the treatment effect of NAT. As the direct evidence of NAT treatment effect, tumor pathological response cannot be determined preoperatively and can only be detected in resected PDAC samples.\u003c/p\u003e\n\n\u003cp\u003eRadiological examinations are frequently used, but there is no evidence that radiological tumor regression after NAT predicts MPR. Even among patients with significant pathological response to NAT, radiological findings may not detect a significant change\u003csup\u003e25\u003c/sup\u003e. Our result revealed that although univariate analysis showed predictive value of RECIST grade for MPR, the multivariate analysis showed no significant difference in the RECIST grade between the MRP and non-MPR groups. We excluded patients with obvious disease progression from undergoing surgery; therefore, the study did not include PD patients. In our study, more than half of the patients presented with SD after NAT, and 33.3% of MPR patients had unchanged radiological examinations. For patients with unavailable radiological response to tumor treatment, this method was not sufficient to predict the pathological response.\u003c/p\u003e\n\n\u003cp\u003eThe commonly used tumor markers, especially CA19-9, predicted the response to NAT\u003csup\u003e25\u003c/sup\u003e. However, 5\u0026ndash;10% of the population does not secrete CA19-9 and it can be affected by numerous non-tumor factors. Therefore, relying on this biomarker alone is not sufficient to predict the treatment response of all patients. Thus, there is an urgent need to identify other biomarkers that can preoperatively predict the pathological response to help in selecting a treatment strategy and surgery timing for these patients. This study aimed to identify potential biomarkers of MPR in patients with PDAC who received NAT before surgical resection.\u003c/p\u003e\n\n\u003cp\u003eOur results showed that post-NAT CA19-9 normalization also predicted MPR in PDAC patients who received NAT. The optimal post-NAT CA19-9 response was independently associated with progression-free and overall survival of PDAC patients\u003csup\u003e7, 8\u003c/sup\u003e. The NCCN guidelines recommend that patients with resectable/borderline resectable disease whose CA 19-9 level is stable or has decreased, and patients with locally advanced disease who have a \u0026gt; 50% decrease in CA19-9 level, should be considered for surgical explorations when radiographic progression has been excluded. Based on our results, CA19-9 normalization was the most significant factor. Tsai et al. reported that the normalization of CA19-9 level is the strongest prognostic marker for survival following NAT\u003csup\u003e26\u003c/sup\u003e. We agree with the aforementioned evidence; CA19-9 normalization is an indication of MPR, which also affects the prognosis. Thus, reducing post-NAT CA19-9 levels to the normal should be one of the main goals of NAT. However, this does not apply to patients who are CA 19-9 non-secretors or those who have normal CA 19-9 levels.\u003c/p\u003e\n\n\u003cp\u003eSBRT use is also a predictive factor for MPR. It is unclear whether radiotherapy should to be part of neoadjuvant therapy for pancreatic cancer. In spite of differences in radiotherapy regimen and dose, most studies of NAT have showed its benefit for postoperative survival and R0 resection rate\u003csup\u003e27, 28\u003c/sup\u003e. Chen-Zhao et al. reported that out of 32 patients who underwent surgery following SBRT, 12 (37.5%) had complete or near complete response (TRG 0\u0026ndash;1)\u003csup\u003e29\u003c/sup\u003e. Although the NCCN guidelines regarding the use of neoadjuvant radiotherapy are controversial, our results prove that SBRT use may be beneficial for pathological regression and may be used as NAT for pancreatic cancer. However, its application is limited by the tumor location, physical status, and financial situation. Currently, we are conducting a randomized controlled clinical trial of SBRT, which is yet to be published\u003csup\u003e30\u003c/sup\u003e.\u003c/p\u003e\n\n\u003cp\u003eInflammatory biomarkers, such as SII, can be calculated on the basis of counts of blood components, which can easily be obtained from blood routine examination, such as lymphocytes, neutrophils, platelets, and C-reactive protein. Among these biomarkers, NLR, PLR, and SII was associated with the prognosis of solid tumors, such as hepatocellular carcinoma, renal cell carcinoma, oral cavity squamous cell carcinoma, and laryngeal squamous cell carcinoma\u003csup\u003e31-34\u003c/sup\u003e. For PDAC patients, Jomrich et al. reported that SII has a greater ability to independently predict the prognosis of resectable PDAC patients compared to NLR and PLR\u003csup\u003e35\u003c/sup\u003e. Additionally, Murthy et al. reported that post-treatment SII may be a useful prognostic marker in PDAC patients receiving NAT\u003csup\u003e35\u003c/sup\u003e.\u003c/p\u003e\n\n\u003cp\u003eIn contrast to a recent study of SII in PDAC patients, our results showed that a high level of post-NAT SII (\u0026gt; 530), rather than pre-NAT SII, could predict MPR (OR = 5.475; 95% CI = 1.278\u0026ndash;23.462). Therefore, it is reasonable to assume that SII is a potentially useful biomarker to predict treatment response to NAT in PDAC patients. Figure 3 shows the alterations in SII in two typical PDAC patients during NAT. PC-94 was a 54-year-old male patient with PDAC. This patient was diagnosed with borderline resectable PDAC and underwent six cycles of AG (Gemcitabine/Albumin-Paclitaxel) NAT regimen, which led to a significant decrease in the CA19-9 and SII levels. Radiological examination did not reveal significant tumor regression. This patient underwent surgery after SBRT. Postoperative pathological examination showed no viable residual tumor cells, and TRG was 0. In contrast to PC-94, PC-71 is a 68-year-old male patient with a borderline resectable tumor. The patient\u0026rsquo;s CA19-9 level was within the normal range before NAT and normalized after six cycles of AG NAT regimen. There was no significant change in the tumor size. However his SII level continued to increase during NAT. Surgery was also performed in this patient after SBRT. However, postoperative pathological examination did not reveal any obvious tumor cells with regression, with a TRG grade of 3. Based on the above two patients, we believe that SII can provide a reference for the pathological responses when tumor markers and radiological examinations are unable to fully evaluate the patient.\u003c/p\u003e\n\n\u003cp\u003eAnalyses of the cause of post-NAT SII level affects the pathologic response in PDAC. Elevated neutrophil levels are the most significant change in inflammation and promote tumor cell proliferation, whereas cancer-related neutrophils increase or suppresses host immunity by inhibiting T cell activation and recruiting regulatory T cells; neutrophils use neutrophil extracellular traps (nets) to isolate circulating cancer cells and stimulate cancer cell migration and invasion36. Platelet activation results in a hypercoagulable state; this hypercoagulable state in PDAC may form a defensive barrier around the circulating tumor cells, allowing tumor cells to escape immune surveillance and promote tumor growth and metastasis\u003csup\u003e37, 38\u003c/sup\u003e. Platelet activation promotes tumor growth and metastasis by binding to tumor cells and secreting angiogenic and tumor-derived growth factors\u003csup\u003e39\u003c/sup\u003e. Decreased lymphocyte counts indicate suppressed immune system function and provide a good microenvironment for the proliferation of circulating tumor cells. Chronic inflammation is closely related to the development of PDAC and it can promote cell proliferation, invasion, migration, metastasis, and malignant change of chronic pancreatitis or epithelial cells, which is known to be a risk factor for PDAC\u003csup\u003e40\u003c/sup\u003e. We hypothesized that the inflammatory biomarker SII reflects the risk of PDAC growth and metastasis. Therefore, patients with MPR have a low SII level, which may be because of low tumor burden.\u003c/p\u003e\n\n\u003cp\u003eThere were several limitations of this study. The patients were highly selected and we only included those patients who were able to undergo radical resection after NAT, failed to respond to NAT, showed diseases progression, or have unresectable tumor during surgery. The fluctuation in SII during NAT was not explored. Because of the small number of cases, different treatment regimens could not be evaluated. This was a single-center retrospective study. Therefore, further prospective multicenter studies are needed to confirm the role of SII in NAT.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThis study suggests that post-NAT CA19-9 normalization, post-NAT SII, and RECIST grade were predictors of MPR after NAT in PDAC patients. Although it cannot replace the role of CA19-9, post-NAT SII may be used as an important biomarker to assess treatment response.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003cstrong\u003e：\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe studies involving human participants were reviewed and approved by the Institutional Review Board of Changhai Hospital (No.CHEC-Y2020-043). All methods were carried out in accordance with declaration of Helsinki. The need for informed consent was waived by the Institutional Review Board of Changhai Hospital (No.CHEC-Y2020-043).\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors report no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by 234 Disciplines Climbing Plan (No.2019YXK033), Shanghai Science and Technology Innovation Action Plan 2020 (No.20511101200) and Shanghai Shenkang Hospital Development Center (No.SHDC2020CR2001A).\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003cstrong\u003e：\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors made substantial contributions to the conception and design, and/or acquisition of data, analysis and interpretation of data. All authors participated in drafting the article and revising it critically for important intellectual content and gave final approval of the version to be published. \u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e: Not applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSiegel RL, Miller KD, Jemal A. Cancer statistics, 2020. CA: A Cancer Journal for Clinicians. 2020; 70: 7-30.\u003c/li\u003e\n\u003cli\u003eHidalgo M. Pancreatic Cancer. NEW ENGL J MED. 2010; 362: 1605-17.\u003c/li\u003e\n\u003cli\u003eCameron JL, Riall TS, Coleman J, Belcher KA. One Thousand Consecutive Pancreaticoduodenectomies. ANN SURG. 2006; 244: 10-15.\u003c/li\u003e\n\u003cli\u003eHeinemann V, Haas M, Boeck S. Neoadjuvant treatment of borderline resectable and non-resectable pancreatic cancer. ANN ONCOL. 2013; 24: 2484-92.\u003c/li\u003e\n\u003cli\u003eVersteijne E, Vogel JA, Besselink MG, Busch ORC, Wilmink JW, Daams JG, et al.. 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CANCER MED-US. 2020; Publish Ahead of Print.\u003c/li\u003e\n\u003cli\u003eLi Z, Qu Y, Yang Y, An W, Li S, Wang B, et al.. Prognostic value of the neutrophil‐to‐lymphocyte ratio, platelet‐to‐lymphocyte ratio and systemic immune‐inflammation index in patients with laryngeal squamous cell carcinoma. CLIN OTOLARYNGOL. 2020; Publish Ahead of Print.\u003c/li\u003e\n\u003cli\u003eJomrich G, Gruber ES, Winkler D, Hollenstein M, Gnant M, Sahora K, et al.. Systemic Immune-Inflammation Index (SII) Predicts Poor Survival in Pancreatic Cancer Patients Undergoing Resection. J GASTROINTEST SURG. 2020; 24: 610-18.\u003c/li\u003e\n\u003cli\u003eCoffelt SB, Wellenstein MD, de Visser KE. Neutrophils in cancer: neutral no more. NAT REV CANCER. 2016; 16: 431-46.\u003c/li\u003e\n\u003cli\u003eMeikle CKS, Kelly CA, Priyanka G, Wuescher LM, Ali RA, Worth RG. Cancer and Thrombosis: The Platelet Perspective. Frontiers in Cell \u0026amp; Developmental Biology. 2016; 4: 147.\u003c/li\u003e\n\u003cli\u003eBoone BA, Zenati MS, Rieser C, Hamad A, Al-abbas A, Zureikat AH, et al.. Risk of Venous Thromboembolism for Patients with Pancreatic Ductal Adenocarcinoma Undergoing Preoperative Chemotherapy Followed by Surgical Resection. ANN SURG ONCOL. 2019; 26: 1503-11.\u003c/li\u003e\n\u003cli\u003eDashevsky O, Varon D, Brill A. Platelet-derived microparticles promote invasiveness of prostate cancer cellsvia upregulation of MMP-2 production. INT J CANCER. 2009; 124: 1773-77.\u003c/li\u003e\n\u003cli\u003eZheng Z, Chen Y, Tan C, Ke N, Du B, Liu X. Risk of pancreatic cancer in patients undergoing surgery for chronic pancreatitis. BMC SURG. 2019; 19: 83.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 to 3 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Pancreatic cancer, pathological response, neoadjuvant therapy, biomarker, systemic immune-inflammation index","lastPublishedDoi":"10.21203/rs.3.rs-2856912/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2856912/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBackground: Pancreatic ductal adenocarcinoma (PDAC) patients have improved prognosis after neoadjuvant therapy (NAT). However, there is a lack of biomarkers to predict the pathological response preoperatively. We evaluated the predictive value of multiple biomarkers, including inflammatory biomarkers, for predicting the pathological responses.\u003c/p\u003e\n\u003cp\u003eMethods: We respectively reviewed the records of patients with localized PDAC who underwent NAT followed by resection between January 2017 and May 2021 at the First Affiliated Hospital of Naval Medical University. The patients were divided into the major pathological response (MPR) and non-MPR groups, according to the tumor regression grade. Univariate and multivariate predictors of MRP were explored. The predictive factors identified on multivariate analysis were used to establish a nomogram prognostic model, which was evaluated using the Decision Curve Analysis (DCA).\u003c/p\u003e\n\u003cp\u003eResults: A total of 150 patients, including 21 in the MPR and 129 in the non-MPR group, were analyzed. In the multivariate analysis of the MRP group, normal CA19-9 level (\u0026lt;37U/ml)(odds ratio, OR = 32.014; 95% confidence interval (CI) = 3.809–269.071; p = 0.001), post-NAT SII \u0026lt; 530 (OR = 14.739; 95% CI = 2.811–77.265; p = 0.001), and use of Stereotactic Body Radiation Therapy (OR = 8.370; 95% CI = 2.175–32.205) predicted MPR in PDAC patients. DCA showed that the nomogram prognostic model had a higher predictive value than standard radiological assessments.\u003c/p\u003e\n\u003cp\u003eConclusions: In resected PDAC, post-NAT normal CA19-9 level, post-NAT SII, and use of Stereotactic Body Radiation Therapy predicted MPR after NAT in PDAC patients. Post-NAT SII can be used as a biomarker to determine the treatment response.\u003c/p\u003e","manuscriptTitle":"Systemic Immune-Inflammation Index After Neoadjuvant Therapy Predicts the Pathological Response in Patients with Resected Pancreatic Ductal Adenocarcinoma","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-05-09 20:04:20","doi":"10.21203/rs.3.rs-2856912/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3cef849d-87bf-400c-8396-5c9f55cd0053","owner":[],"postedDate":"May 9th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-10-25T12:23:44+00:00","versionOfRecord":[],"versionCreatedAt":"2023-05-09 20:04:20","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-2856912","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2856912","identity":"rs-2856912","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}