Development and External Validation of Web-Based Models to Predict the Prognosis of Remnant Gastric Cancer after Surgery: A Multicenter Study.

Qi‐Yue Chen ,Qing Zhong,Ping Li,Wei Lin,Teng-Wen Li,Lisheng Cai ,Shuangming Lin ,Jia-Bin Wang,Lin Ma ,Xiantu Qiu ,Ze‐Ning Huang ,Qiu-Xian Chen,Guoqiang Su ,Qingliang He ,Zhou Jun ,Zhiyu Liu ,Ju‐Li Lin ,Kaiqing Guo ,Long‐Long Cao ,Jun Lü ,Jian‐Wei Xie ,Xueyi Dang ,Lin Ji ,Chao‐Hui Zheng ,Dongbo Xu ,Ru‐Hong Tu ,Chang‐Ming Huang

doi:10.1155/2019/6012826

Abstract

Background Remnant gastric cancer (RGC) is a rare malignant tumor with poor prognosis. There is no universally accepted prognostic model for RGC. Methods We analyzed data for 253 RGC patients who underwent radical gastrectomy from 6 centers. The prognosis prediction performances of the AJCC7th and AJCC8th TNM staging systems and the TRM staging system for RGC patients were evaluated. Web-based prediction models based on independent prognostic factors were developed to predict the survival of the RGC patients. External validation was performed using a cohort of 49 Chinese patients. Results The predictive abilities of the AJCC8th and TRM staging systems were no better than those of the AJCC7th staging system (c-index: AJCC7th vs. AJCC8th vs. TRM, 0.743 vs. 0.732 vs. 0.744; P>0.05). Within each staging system, the survival of the two adjacent stages was not well discriminated (P>0.05). Multivariate analysis showed that age, tumor size, T stage, and N stage were independent prognostic factors. Based on the above variables, we developed 3 web-based prediction models, which were superior to the AJCC7th staging system in their discriminatory ability (c-index), predictive homogeneity (likelihood ratio chi-square), predictive accuracy (AIC, BIC), and model stability (time-dependent ROC curves). External validation showed predictable accuracies of 0.780, 0.822, and 0.700, respectively, in predicting overall survival, disease-specific survival, and disease-free survival. Conclusions The AJCC TNM staging system and the TRM staging system did not enable good distinction among the RGC patients. We have developed and validated visual web-based prediction models that are superior to these staging systems.

Highlights

Remnant gastric cancer (RGC) encompasses all carcinomas arising in the remnant stomach following gastrectomy, irrespective of the histology of the primary disease or the extent of resection, the method of reconstruction, and nonrestriction of the time interval [1]
144 (56.9%) cases were located at the anastomosis site, and 109 (43.1%) cases were located at the nonanastomotic site
The staging system of primary gastric cancer (PGC) is still used for RGC in clinical practice at the present time

Summary

Introduction

Remnant gastric cancer (RGC) encompasses all carcinomas arising in the remnant stomach following gastrectomy, irrespective of the histology of the primary disease (benign or malignant) or the extent of resection, the method of reconstruction, and nonrestriction of the time interval [1]. The continuous update and improvement of the AJCC (American Joint Committee on Cancer) TNM staging are conspicuous [5, 6], as this is generally accepted as an ideal prognostic evaluation system for PGC. The rate of LN metastasis (LNR; the ratio of positive LNs to RLNs) is considered more suitable for evaluating LN status in PGC patients with fewer retrieved LNs than positive LNs. The TRM (tumorratio-metastasis) staging derived from the LNR is considered a good supplement to the TNM staging system [10,11,12]. The prognosis prediction performances of the AJCC7th and AJCC8th TNM staging systems and the TRM staging system for RGC patients were evaluated. Web-based prediction models based on independent prognostic factors were developed to predict the survival of the RGC patients. We have developed and validated visual web-based prediction models that are superior to these staging systems

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Conclusion