创新性病理 N 分级系统革新 T3-4N0-2M0 胃癌分期。

Revolutionizing T3-4N0-2M0 gastric cancer staging with an innovative pathologic N classification system.

机构信息

Postgraduate Training Base Alliance of Wenzhou Medical University (Zhejiang Cancer Hospital), Hangzhou, China; Department of Gastric surgery, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, China; Zhejiang Provincial Research Center for Upper Gastrointestinal Tract Cancer, Zhejiang Cancer Hospital, Hangzhou, China; Zhejiang Key Lab of Prevention, Diagnosis and Therapy of Upper Gastrointestinal Cancer, Zhejiang Cancer Hospital, Hangzhou, China.

Department of Medical Oncology, Sir Run Shaw Hospital, College of Medicine, Zhejiang University, Hangzhou, China.

出版信息

J Gastrointest Surg. 2024 Aug;28(8):1283-1293. doi: 10.1016/j.gassur.2024.05.031. Epub 2024 May 29.

DOI:10.1016/j.gassur.2024.05.031

PMID:38821213

Abstract

BACKGROUND

The current pathologic N (pN) classification exhibits limitations in the prognostic stratification of patients with pT3-4N0-2M0 gastric cancer (GC). Therefore, this study aimed to develop and validate a new lymph nodal staging method based on the number of examined lymph nodes (ELNs) and lymph node ratio (LNR).

METHODS

Data from 7883 patients with pT3-4N0-2M0 GC were collected from the Surveillance, Epidemiology, and End Results (SEER) database and Zhejiang Cancer Provincial Hospital. Optimal cutoff values for ELNs and LNR were determined using X-tile software. Kaplan-Meier methods, Log-rank tests, and Cox regression analyses were employed in this study. Patients were categorized into 3 new pN stages: new pN0 (pN0 with ELNs of >16), new pN1 (pN0 with ELNs of ≤16 or pN1-2 with LNR of ≤0.15), and new pN2 (pN1-2 with LNR of >0.15). The prognostic predictive power of both current and new pN staging was evaluated using the Akaike information criterion (AIC), Bayesian information criterion, concordance index (C-index), and receiver operating characteristic curve.

RESULTS

The new pN classification exhibited excellent performance in Kaplan-Meier survival analysis. After adjusting for confounding factors, the new pN staging emerged as an independent prognostic indicator in patients with GC. In the SEER cohort, the new pN staging demonstrated enhanced prognostic prediction accuracy over the American Joint Committee on Cancer pN staging (AIC: 75578.85 vs 75755.06; C-index: 0.642 vs 0.630; P < .001). Similar findings were validated in the Chinese cohort.

CONCLUSION

This study developed and validated an improved pN classification for patients with pT3-4N0-2M0 GC. Surgeons should consider ELNs and LNR when assessing postoperative prognosis in patients with GC.

摘要

背景

目前的病理 N（pN）分类在预测 pT3-4N0-2M0 胃癌（GC）患者的预后方面存在局限性。因此，本研究旨在开发和验证一种基于检查淋巴结数量（ELNs）和淋巴结比（LNR）的新的淋巴结分期方法。

方法

从监测、流行病学和最终结果（SEER）数据库和浙江省肿瘤医院收集了 7883 例 pT3-4N0-2M0 GC 患者的数据。使用 X-tile 软件确定 ELNs 和 LNR 的最佳截断值。本研究采用 Kaplan-Meier 方法、Log-rank 检验和 Cox 回归分析。将患者分为 3 个新的 pN 分期：新 pN0（ELNs >16 的 pN0）、新 pN1（ELNs ≤16 或 pN1-2 的 LNR ≤0.15 的 pN0）和新 pN2（pN1-2 的 LNR >0.15）。使用 Akaike 信息准则（AIC）、贝叶斯信息准则、一致性指数（C-index）和接收者操作特征曲线评估当前和新 pN 分期的预后预测能力。

结果

新的 pN 分类在 Kaplan-Meier 生存分析中表现出色。在调整混杂因素后，新的 pN 分期成为 GC 患者的独立预后指标。在 SEER 队列中，新的 pN 分期在预测预后方面优于美国癌症联合委员会 pN 分期（AIC：75578.85 比 75755.06；C-index：0.642 比 0.630；P<0.001）。在中国队列中也得到了验证。