新型预后营养炎症评分系统建立以有效预测胰腺癌根治术后患者的长期预后

doi:10.3877/cma.j.issn.1674-0793.2026.02.003

中华普通外科学文献(电子版) ›› 2026, Vol. 20 ›› Issue (02) : 85 -90. doi: 10.3877/cma.j.issn.1674-0793.2026.02.003

论著

新型预后营养炎症评分系统建立以有效预测胰腺癌根治术后患者的长期预后

曹喆¹, 翁桂湖¹, 刘涛¹, 张锰钢¹, 杨刚¹, 陈浩¹, 邱江东¹, 徐建威², 张太平¹^,^†(

)

¹　100730　北京，中国医学科学院北京协和医学院　北京协和医院基本外科
²　250012　济南，山东大学齐鲁医院普外科

收稿日期:2026-02-28 出版日期:2026-04-01
通信作者: 张太平
基金资助:
国家重点研发计划资助项目(2023YFC2413400); 协和人才培育支持计划D类项目(UHB11961); 中央高水平医院临床科研业务费项目(2025-PUMCH-A-070)

Development of a novel prognostic nutrition-inflammation scoring system to predict long-term prognosis in patients with pancreatic cancer after radical surgery

Zhe Cao¹, Guihu Weng¹, Tao Liu¹, Menggang Zhang¹, Gang Yang¹, Hao Chen¹, Jiangdong Qiu¹, Jianwei Xu², Taiping Zhang¹^,^†()

¹ Department of General Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
² Department of General Surgery, Qilu Hospital of Shandong University, Jinan 250012, China

Received:2026-02-28 Published:2026-04-01
Corresponding author: Taiping Zhang

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引用本文：

曹喆, 翁桂湖, 刘涛, 张锰钢, 杨刚, 陈浩, 邱江东, 徐建威, 张太平. 新型预后营养炎症评分系统建立以有效预测胰腺癌根治术后患者的长期预后[J/OL]. 中华普通外科学文献(电子版), 2026, 20(02): 85-90.

Zhe Cao, Guihu Weng, Tao Liu, Menggang Zhang, Gang Yang, Hao Chen, Jiangdong Qiu, Jianwei Xu, Taiping Zhang. Development of a novel prognostic nutrition-inflammation scoring system to predict long-term prognosis in patients with pancreatic cancer after radical surgery[J/OL]. Chinese Archives of General Surgery(Electronic Edition), 2026, 20(02): 85-90.

目的

探究营养及炎症相关指标在胰腺癌中的预后价值，并构建个性化预测模型。

方法

回顾性分析2016年1月至2021年9月于北京协和医院和山东大学齐鲁医院接受胰腺癌根治性切除的158例胰腺癌患者的临床资料。采用Cox回归筛选与总生存期（OS）和无病生存期（DFS）相关的标志物。利用 “rms”包开发了预后营养炎症评分（PNIS）系统和PNIS-列线图，并通过时间依赖的受试者工作特征曲线、校准曲线和决策曲线分析（DCA）进行评估。

结果

基于预后营养指数、中性粒细胞-淋巴细胞比值、丙氨酸氨基转移酶和超敏C反应蛋白构建PNIS公式，将患者分层为低、高风险组，高风险组的总生存期(P<0.001)和无病生存期 (P<0.001) 更短。结合病理分级、N 分期、化疗和吸烟史构建PNIS-列线图，其对1、2、3年OS率（AUC：0.896、0.782、0.783）和DFS率（AUC：0.775、0.766、0.784）的预测性能良好，且校准曲线和DCA表现优越。

结论

PNIS-列线图作为一种可靠工具，可有效预测胰腺癌手术患者的长期预后，可为异常炎性反应及营养不良在胰腺癌中的作用提供新见解。

关键词: 胰腺肿瘤, 营养/炎症, 长期预后, 列线图

Objective

Toinvestigate the prognostic values of nutrition-and inflammation-related indicators in pancreatic cancer and construct a personalized predictive model.

Methods

Clinical data from 158 patients with pancreatic cancer who underwent radical resection in Peking Union Medical College Hospital and Qilu Hospital of Shandong University from January 2016 to September 2021 were retrospectively analyzed. Cox regression was used to identify markers associated with overall survival (OS) and disease-free survival (DFS). The prognostic nutritional inflammation score (PNIS) system and PNIS-nomogram were developed using the ‘rms’ package and evaluated via time-dependent receiver operating characteristic curves, calibration curves, and decision curve analysis (DCA).

Results

The PNIS formula, based on prognostic nutritional index, neutrophil-to-lymphocyte ratio, alanine aminotransferase, and high-sensitivity C-reactive protein, stratified patients into low- and high-risk groups, with high-risk patients showing significantly shorter OS (P<0.001) and DFS (P<0.001). The PNIS-nomogram, incorporating pathological grade, N stage, chemotherapy, and smoking history, demonstrated excellent predictive performance for 1-, 2-, and 3-year OS (AUC: 0.896, 0.782, 0.783) and DFS (AUC: 0.775, 0.766, 0.784), with favorable calibration and DCA results.

Conclusion

The PNIS-nomogram serves as a reliable tool for effectively predicting long-term postoperative outcomes in pancreatic cancer patients and may provide new insights into the role of abnormal inflammatory responses and malnutrition in pancreatic cancer.

Key words: Pancreatic neoplasms, Nutrition/inflammation, Long-term prognosis, Nomogram

图1 基于4个营养/炎症指标（PNI、NLR、ALT、hsCRP）的预后营养炎症评分（PNIS）列线图，用于预测胰腺癌患者的生存率或无病生存率　A. PNIS.OS模型用于1、2、3年OS率预测；B. PNIS.DFS模型用于1、2、3年DFS率预测；C. PNIS.OS低风险组与PNIS.OS高风险组患者的Kaplan-Meier曲线；D. PNIS.DFS低风险组与PNIS.DFS高风险组患者的Kaplan-Meier曲线；E. PNIS.OS模型的时间依赖性ROC曲线；F. PNIS.DFS模型的时间依赖性ROC曲线;总生存期（OS）；无病生存期（DFS）；外周血中性粒细胞-淋巴细胞比值（NLR）；预后营养指数（PNI）；丙氨酸氨基转移酶（ALT）；超敏C反应白蛋白（hsCRP）

图2 结合PNIS评分和其他临床病理参数构建与评估PNIS-列线图，用于OS和DFS预测（A、B）、PNIS-列线图预测OS和DFS的时间依赖性ROC曲线（C、D）；E. PNIS-列线图在预测患者1、2、3年OS率的校准曲线；F. PNIS-列线图在预测患者1、2、3年DFS率的校准曲线；总生存期（OS）；无病生存期（DFS）；预后营养炎症评分（PNIS）；受试者工作特征曲线（ROC）

图3 PNIS-列线图与TNM分期在队列中1年OS率(A)、2年OS率(C)、3年OS率(E)及1年DFS率(B)、2年DFS率(D)、3年DFS率(F)中的决策曲线分析；总生存期（OS）；无病生存期（DFS）；预后营养炎症评分（PNIS）

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