Jin Liang, Zou Yiping, Ruan Shiye, Han Hongwei, Zhang Yuanpeng, Chen Zhihong, Jin Haosheng, Shi Ning
Department of General Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Gland Surg. 2021 Feb;10(2):529-540. doi: 10.21037/gs-20-597.
Pancreatic adenocarcinoma (PaC) patients with positive lymph nodes (PLNs) have a dismal prognosis and lack a specific prognostic stage. This study aimed to construct a nomogram for the prediction of overall survival (OS) in these patients.
A total of 1,340 patients screened from the Surveillance, Epidemiology, and End Results database were included and randomly divided at a ratio of 7:3 into a training set (n=940) and an internal validation set (n=400). Cox regression analyses were conducted to select independent predictors in the training set, and a nomogram was constructed. The model was verified in the internal validation set and in an external validation set, which comprised 64 patients from a Chinese institute.
Six independent prognostic factors (age at diagnosis, tumor grade, lymph node ratio, T stage, radiotherapy, and chemotherapy) were identified in PaC patients with PLNs and were entered into the nomogram. The final model had a higher C-index for predicting OS than the American Joint Committee on Cancer-8th edition staging system (training set: 0.658 . 0.546; internal validation set: 0.661 . 0.546; external validation set: 0.691 . 0.581). The 1-, 2-, and 3-year area under the receiver operating characteristic curve values indicated better discrimination power for the established nomogram with respect to the prediction of OS in the training, internal validation, and external validation sets than for the American Joint Committee on Cancer-8th edition staging system. Furthermore, the nomogram performed well in both calibration and decision curve analyses (DCA) of clinical applicability. OS in PaC patients with PLNs was significantly distinguished among the three risk groups stratified according to the nomogram score (P<0.001).
The well-calibrated nomogram was determined to be extremely efficient in predicting survival, and defining a high-risk population based on the nomogram score among PaC patients with PLNs after surgery.
伴有阳性淋巴结（PLN）的胰腺腺癌（PaC）患者预后较差，且缺乏特定的预后分期。本研究旨在构建一种列线图，用于预测这些患者的总生存期（OS）。
从监测、流行病学和最终结果数据库中筛选出1340例患者，按7:3的比例随机分为训练集（n = 940）和内部验证集（n = 400）。在训练集中进行Cox回归分析以选择独立预测因素，并构建列线图。该模型在内部验证集和外部验证集（由一家中国机构的64例患者组成）中进行了验证。
在伴有PLN的PaC患者中确定了六个独立的预后因素（诊断时年龄、肿瘤分级、淋巴结比率、T分期、放疗和化疗），并将其纳入列线图。最终模型在预测OS方面的C指数高于美国癌症联合委员会第8版分期系统（训练集：0.658对0.546；内部验证集：0.661对0.546；外部验证集：0.691对0.581）。受试者工作特征曲线下1年、2年和3年的面积值表明，对于训练集、内部验证集和外部验证集中OS的预测，所建立的列线图比美国癌症联合委员会第8版分期系统具有更好的区分能力。此外，列线图在临床适用性的校准和决策曲线分析（DCA）中表现良好。根据列线图评分分层的三个风险组中，伴有PLN的PaC患者的OS有显著差异（P<0.001）。
经良好校准的列线图在预测生存方面被确定为极其有效，并且基于列线图评分在术后伴有PLN的PaC患者中定义了一个高危人群。
