Prediction of long-term survival after gastrectomy using random survival forests.

ABSTRACT:

Background

No well validated and contemporaneous tools for personalized prognostication of gastric adenocarcinoma exist. This study aimed to derive and validate a prognostic model for overall survival after surgery for gastric adenocarcinoma using a large national dataset.

Methods

National audit data from England and Wales were used to identify patients who underwent a potentially curative gastrectomy for adenocarcinoma of the stomach. A total of 2931 patients were included and 29 clinical and pathological variables were considered for their impact on survival. A non-linear random survival forest methodology was then trained and validated internally using bootstrapping with calibration and discrimination (time-dependent area under the receiver operator curve (tAUC)) assessed

SUBMITTER: Rahman SA 

PROVIDER: S-EPMC10364915 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature