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中华普外科手术学杂志(电子版) ›› 2026, Vol. 20 ›› Issue (05) : 468 -473. doi: 10.3877/cma.j.issn.1674-3946.2026.05.014

论著

基于炎症与营养指标的早发型直肠癌患者预后列线图的构建与验证
夏明宇1, 刘光昊2, 孙倩男3, 刘宾3, 王道荣1,2,3,†()   
  1. 1 225001 江苏扬州,徐州医科大学扬州临床学院
    2 225001 江苏扬州,扬州大学附属苏北人民医院
    3 225001 江苏扬州,苏北人民医院
  • 收稿日期:2025-12-26 出版日期:2026-10-26
  • 通信作者: 王道荣

Construction and validation of a prognostic nomogram for early-onset rectal cancer patients based on inflammatory and nutritional indicators

Mingyu Xia1, Guanghao Liu2, Qiannan Sun3, Bin Liu3, Daorong Wang1,2,3,†()   

  1. 1 The Yangzhou Clinical Medical College of Xuzhou Medical University, Yangzhou Jiangsu Province 225001, China
    2 Northern Jiangsu People's Hospital Affiliated to Yangzhou University, Yangzhou Jiangsu Province 225001, China
    3 Northern Jiangsu People's Hospital, Yangzhou Jiangsu Province 225001, China
  • Received:2025-12-26 Published:2026-10-26
  • Corresponding author: Daorong Wang
引用本文:

夏明宇, 刘光昊, 孙倩男, 刘宾, 王道荣. 基于炎症与营养指标的早发型直肠癌患者预后列线图的构建与验证[J/OL]. 中华普外科手术学杂志(电子版), 2026, 20(05): 468-473.

Mingyu Xia, Guanghao Liu, Qiannan Sun, Bin Liu, Daorong Wang. Construction and validation of a prognostic nomogram for early-onset rectal cancer patients based on inflammatory and nutritional indicators[J/OL]. Chinese Journal of Operative Procedures of General Surgery(Electronic Edition), 2026, 20(05): 468-473.

目的

本研究旨在构建并验证一种整合术前炎症与营养指标的实用性预后列线图,用于评估早发型直肠癌(EORC)患者的生存结局。

方法

回顾性纳入326例接受根治性切除的EORC患者,随机分为训练队列和验证队列。基于常规实验室检查数据计算术前炎症及营养指标,构建炎症-营养风险评分(RS),RS由LASSO筛选的中性粒细胞/淋巴细胞比值(NLR)、系统炎症反应指数(SIRI)、系统免疫炎症指数(SII)、血小板/淋巴细胞比值(PLR)、营养免疫炎症指数(ALI)、预后营养指数(PNI)加权线性组合得到。采用多因素生存分析筛选独立预后因素,并建立预测总生存期(OS)的列线图。通过区分度、校准度及临床决策曲线分析(DCA)评估模型性能。

结果

多因素分析显示,年龄、TNM分期、血清白蛋白水平及炎症与营养风险评分为OS的独立预测因素。所构建列线图在训练队列及验证队列中对1年、3年和5年OS均表现出良好的区分度与校准度。

结论

本研究构建并验证的一种简便、具有临床实用性的炎症与营养列线图,可通过整合常规术前指标,为EORC患者的术后风险分层及个体化随访管理提供辅助决策依据。

Objective

The aim of this study was to develop and validate a practical prognostic nomogram integrating preoperative inflammatory and nutritional indicators to assess the survival outcomes of patients with early-onset rectal cancer (EORC).

Methods

A total of 326 patients with EORC who underwent radical resection were retrospectively included and randomly divided into a training cohort and a validation cohort. Preoperative inflammatory and nutritional indicators were calculated based on routine laboratory test data, and an inflammatory-nutritional risk score (RS) was constructed. The RS was obtained through a weighted linear combination of the LASSO-sellected neutrophil/lymphocyte ratio (NLR), systemic inflammatory response index (SIRI), systemic immune-inflammatory index (SII), platelet/lymphocyte ratio (PLR), nutritional immune-inflammatory index (ALI), and prognostic nutritional index (PNI). Multivariate survival analysis was used to screen independent prognostic factors, and a nomogram for predicting overall survival (OS) was established. The performance of the model was evaluated using discrimination, calibration, and clinical decision curve analysis (DCA).

Results

Multivariate analysis showed that age, TNM stage, serum albumin level, and the inflammatory-nutritional risk score were independent predictors of OS. The constructed nomogram demonstrated good discrimination and calibration for 1-year, 3-year, and 5-year OS in both the training cohort and validation cohort.

Conclusion

This study developed and validated a simple and clinically practical inflammatory-nutritional nomogram that can integrate routine preoperative indicators, providing an auxiliary decision-making basis for postoperative risk stratification and individualized follow-up management of patients with EORC.

表1 两组早发型直肠癌患者的基线特征
特征 训练队列(n=229) 验证队列(n=97) 统计值 P 值
年龄[岁,M(P25,P75)] 44.8(39.1, 50.5) 45.56(40.2, 51.0) Z=1.169 0.253
性别[例(%)]
男 116(50.7) 56(57.7) χ2=1.369 0.504
女 113(49.3) 41(42.3)
高血压[例(%)]
是 21(9.2) 14(14.4) χ2=1.969 0.374
否 208(90.8) 83(85.6)
糖尿病[例(%)]
是 5(2.2) 7(7.2) χ2=4.875 0.088
否 224(97.8) 90(92.8)
冠心病[例(%)]
是 5(2.2) 1(1.0) χ2=0.512 0.778
否 224(97.8) 96(99.0)
腹部手术史[例(%)]
是 158(69.0) 57(58.8) χ2=3.177 0.204
否 71(31.0) 40(41.2)
肿瘤最大径[例(%)]
≥5 cm 101(44.1) 36(37.1) χ2=0.283 0.505
<5 cm 128(55.9) 61(62.9)
淋巴结转移[例(%)]
是 67(29.3) 27(27.8) χ2=0.067 0.967
否 162(70.7) 70(72.2)
T分期[例(%)]
T1 23(10.0) 10(10.3) χ2=1.529 0.958
T2 37(16.2) 12(12.4)
T3 80(34.9) 40(41.2)
T4 89(38.9) 35(36.1)
N分期[例(%)]
N0 75(32.8) 32(33.0) χ2=0.111 0.996
N1 108(47.2) 46(47.4)
N2 46(20.1) 19(19.6)
M分期[例(%)]
M0 175(76.4) 68(70.1) χ2=1.432 0.489
M1 54(23.6) 29(29.9)
TNM分期[例(%)]
Ⅰ期 29(12.7) 12(12.4) χ2=1.309 0.971
Ⅱ期 52(22.7) 21(21.7)
Ⅲ期 93(40.6) 35(36.1)
Ⅳ期 55(24.0) 29(29.9)
血管侵犯[例(%)]
阴性 194(84.7) 80(82.5) χ2=0.255 0.880
阳性 35(15.3) 17(17.5)
神经侵犯[例(%)]
阴性 205(89.5) 82(84.5) χ2=1.607 0.448
阳性 24(10.5) 15(15.5)
血红蛋白[g/L,M(P25, P75)] 136.3(117.1, 155.6) 132.8(108.4, 157.3) Z=1.267 0.164
白蛋白[g/L,M(P25, P75)] 46.2(38.3, 54.1) 45.3(39.7, 51.0) Z=1.145 0.317
BMI[kg/m²,M(P25, P75)] 24.10(20.5, 27.7) 24.2(21.0, 27.4) Z=0.332 0.753
NLR[M(P25, P75)] 3.91(0.1, 7.7) 3.8(1.3, 6.2) Z=0.429 0.716
PLR[M(P25, P75)] 173.6(41.7, 305.5) 191.3(63.4, 319.2) Z=1.131 0.265
MLR[M(P25, P75)] 0.2(0.1, 0.3) 0.3(0.0, 0.6) Z=2.494 0.262
SIRI[M(P25, P75)] 1.1(0.1, 2.3) 1.5(0.6, 3.7) Z=1.770 0.329
ALI[M(P25, P75)] 409.1(148.2,670.0) 397.5(167.1, 627.9) Z=1.402 0.703
PIV[M(P25, P75)] 275.5(91.8,642.9) 362.6(162.4, 887.6) Z=1.487 0.088
PNI[M(P25, P75)] 53.9(44.2,63.7) 52.6(46.7, 58.5) Z=1.520 0.209
SII[M(P25, P75)] 918.6(198.3, 2035.5) 928.9(205.1, 1 652.7) Z=0.099 0.933
表2 术前炎症与营养指标的最佳截断值
表3 炎症与营养相关指标对总生存期的单因素COX回归分析
图1 炎症与营养风险评分(RS)的构建与验证 A、B采用LASSO Cox回归分析进行变量筛选Log(λ) 与回归系数变化曲线;C为RS在训练队列中预测总生存期(OS)的ROC曲线;D为高RS组与低RS组患者OS的Kaplan-Meier生存曲线 注:ROC为受试者工作特征
表4 总生存期相关因素的单因素及多因素COX回归分析
图2 基于RS及临床病理因素的早发型直肠癌总生存期预测列线图 注:列线图包括4个变量:年龄、TNM分期、血清白蛋白水平及RS。每个变量对应0~100分的评分刻度,总评分(0~260分)为各变量得分之和。通过自各变量取值向上作垂线至“Points”轴以获得相应得分
图3 列线图在训练队列和验证队列中对总生存期(OS)的区分度 A~C为训练队列中预测1年、3年及5年OS的ROC曲线;D~F为验证队列中预测1年、3年及5年OS的ROC曲线横坐标为 1–特异度(假阳性率),纵坐标为灵敏度(真阳性率) 注:AUC为曲线下面积;ROC为受试者工作特征
图4 列线图的校准曲线 A~C为训练队列中1年、3年及5年总生存期(OS)预测的校准曲线(n=229,事件数=115;每组70例,重抽样校正,B=500);D~F为验证队列中1年、3年及5年OS预测的校准曲线(n=97,事件数=48;每组30例,重抽样校正,B=500);横坐标表示预测生存概率,纵坐标表示实际生存概率,对角线代表理想校准状态(预测值与实际值完全一致)
图5 决策曲线分析评估列线图的临床实用价值(DCA) A~C为训练队列中预测1年、3年及5年总生存期(OS)的决策曲线;D~F为验证队列中预测1年、3年及5年OS的决策曲线;横坐标表示阈值概率,纵坐标表示净获益。“不干预” 曲线代表不对任何患者进行干预的策略,“全部干预”曲线代表对所有患者进行干预的策略,“列线图模型”曲线表示列线图模型在不同阈值概率下的净获益,反映其临床应用价值。决策曲线分析显示,在较宽的阈值概率范围内,该列线图预测总体生存的净获益优于“全部干预”和“不干预”策略
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