Tang J, Ding SL, Wu Y, Wu YP, Yuan XB, Wu PF, Sha DS. Prognostic value of a nomogram model for pancreatic cancer incorporating the systemic immune-inflammation and prognostic nutritional indices. World J Gastrointest Surg 2026; 18(3): 115906 [DOI: 10.4240/wjgs.v18.i3.115906]
Corresponding Author of This Article
Ying Wu, Department of General Surgery, Affiliated Rugao Hospital of Xinglin College, Nantong University, The People’s Hospital of Rugao, No. 278 Ninghai Road, Rucheng Town, Rugao 226500, Jiangsu Province, China. rgrmyy1398@163.com
Research Domain of This Article
Gastroenterology & Hepatology
Article-Type of This Article
Retrospective Study
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This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Mar 27, 2026 (publication date) through Mar 30, 2026
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Journal Information of This Article
Publication Name
World Journal of Gastrointestinal Surgery
ISSN
1948-9366
Publisher of This Article
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
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Tang J, Ding SL, Wu Y, Wu YP, Yuan XB, Wu PF, Sha DS. Prognostic value of a nomogram model for pancreatic cancer incorporating the systemic immune-inflammation and prognostic nutritional indices. World J Gastrointest Surg 2026; 18(3): 115906 [DOI: 10.4240/wjgs.v18.i3.115906]
Jie Tang, Ying Wu, Ya-Ping Wu, Xiao-Bing Yuan, Peng-Fei Wu, De-Sheng Sha, Department of General Surgery, Affiliated Rugao Hospital of Xinglin College, Nantong University, The People’s Hospital of Rugao, Rugao 226500, Jiangsu Province, China
Shi-Lin Ding, Department of Clinical Laboratory, Affiliated Rugao Hospital of Xinglin College, Nantong University, The People’s Hospital of Rugao, Rugao 226500, Jiangsu Province, China
Co-first authors: Jie Tang and Shi-Lin Ding.
Author contributions: Tang J and Ding SL designed the study, collected the data, validated the data, and wrote the first draft; they contributed equally to this article, and they are the co-first authors of this manuscript; Wu Y, Wu YP, Yuan XB participated in the data collection and analysis; Wu PF and Sha DS did the statistical analysis; Tang J, Ding SL, Wu Y, Wu YP, Yuan XB, Wu PF, and Sha DS participated in the manuscript revisions and editing; All authors read and approved the final version for submission.
Supported by Science and Key Technology Research Project, Rugao City, No. SRGS[23]003.
Institutional review board statement: This study was approved by the Medical Ethics Committee of the People’s Hospital of Rugao, approval No.KY202211013.
Informed consent statement: Each participant signed a written informed consent for treatment and the use and publication of their clinical data and information.
Conflict-of-interest statement: All authors report no relevant conflicts of interest for this article.
Data sharing statement: The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
Corresponding author: Ying Wu, Department of General Surgery, Affiliated Rugao Hospital of Xinglin College, Nantong University, The People’s Hospital of Rugao, No. 278 Ninghai Road, Rucheng Town, Rugao 226500, Jiangsu Province, China. rgrmyy1398@163.com
Received: October 29, 2025 Revised: December 1, 2025 Accepted: January 14, 2026 Published online: March 27, 2026 Processing time: 150 Days and 7.4 Hours
Abstract
BACKGROUND
A nomogram model predictive of pancreatic ductal adenocarcinoma (PDAC) outcomes based on the systemic immune inflammation index (SII) and prognostic nutritional index (PNI) does not exist.
AIM
To determine the prognostic value of a nomogram model combining the SII and PNI in patients with PDAC after radical surgery.
METHODS
One hundred sixty-four patients who underwent radical surgery for PDAC between 2017 and 2023 were retrospectively enrolled. A nomogram prediction model for the survival rate after PDAC surgery was established based on the multivariable Cox regression results of the training cohort (n = 129). The model was validated in the external validation cohort (n = 35). The time-dependent receiver operating characteristic (ROC) curve, C-index, calibration curve, and decision curve were used to evaluate model efficacy, and an online prediction tool was developed.
RESULTS
An SII > 335.82, a PNI ≤ 44.45, poorly differentiated PDAC, no postoperative adjuvant chemotherapy, and a carbohydrate antigen 19-9 level > 37 U/mL were independent risk factors for poor prognosis of patients with PDAC after radical surgery. These five factors were included in the nomogram model. The internal validation C-index of the nomogram model was 0.691 (95% confidence interval: 0.626-0.755). The area under the ROC curve values for the 1-year, 2-year, and 3-year postoperative survival rates in the training cohort were 0.684, 0.762, and 0.822, respectively; the area under the ROC curve values for the external validation cohort were 0.772, 0.755, and 0.796, respectively.
CONCLUSION
The nomogram model based on the SII and PNI accurately predicted the survival risk and prognosis in patients with PDAC after surgery, providing a quantitative tool for individualized treatment decisions.
Core Tip: A nomogram prediction model that was constructed based on the systemic immune inflammation index and prognostic nutrition index accurately assessed the comprehensive preoperative inflammation-immune-nutrition status of patients with pancreatic cancer. The convenience and simplicity of the model, especially when combined with the online calculator, enhanced the predictive potential for the prognosis of patients with pancreatic cancer after surgery. This model is particularly suitable for primary hospitals with limited resources. However, the results of this study need to be verified by prospective samples from multiple centers with large samples.
