A machine learning model for colorectal liver metastasis post-hepatectomy prognostications.

ABSTRACT:

Background

Currently, surgical resection is the mainstay for colorectal liver metastases (CRLM) management and the only potentially curative treatment modality. Prognostication tools can support patient selection for surgical resection to maximize therapeutic benefit. This study aimed to develop a survival prediction model using machine learning based on a multicenter patient sample in Hong Kong.

Methods

Patients who underwent hepatectomy for CRLM between 1 January 2009 and 31 December 2018 in four hospitals in Hong Kong were included in the study. Survival analysis was performed using Cox proportional hazards (CPH). A stepwise selection on Cox multivariable models with Least Absolute Shrinkage and Selection Operator (LASSO) regression was applied to a multiply-imputed datas

SUBMITTER: Lam CSN 

PROVIDER: S-EPMC10432293 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature