Development and Validation of Nomogram for Predicting Survival of Primary Liver Cancers Using Machine Learning.

ABSTRACT:

Background and aims

Primary liver cancer (PLC) is a common malignancy with poor survival and requires long-term follow-up. Hence, nomograms need to be established to predict overall survival (OS) and cancer-specific survival (CSS) from different databases for patients with PLC.

Methods

Data of PLC patients were downloaded from Surveillance, Epidemiology, and End Results (SEER) and the Cancer Genome Atlas (TCGA) databases. The Kaplan Meier method and log-rank test were used to compare differences in OS and CSS. Independent prognostic factors for patients with PLC were determined by univariate and multivariate Cox regression analyses. Two nomograms were developed based on the result of the multivariable analysis and evaluated by calibration curves and receiver operating charac

SUBMITTER: Chen R 

PROVIDER: S-EPMC9258303 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature