Machine Learning Predictive Model to Guide Treatment Allocation for Recurrent Hepatocellular Carcinoma After Surgery.

ABSTRACT:

Importance

Clear indications on how to select retreatments for recurrent hepatocellular carcinoma (HCC) are still lacking.

Objective

To create a machine learning predictive model of survival after HCC recurrence to allocate patients to their best potential treatment.

Design, setting, and participants

Real-life data were obtained from an Italian registry of hepatocellular carcinoma between January 2008 and December 2019 after a median (IQR) follow-up of 27 (12-51) months. External validation was made on data derived by another Italian cohort and a Japanese cohort. Patients who experienced a recurrent HCC after a first surgical approach were included. Patients were profiled, and factors predicting survival after recurrence under different treatments that acted also as t

SUBMITTER: Famularo S 

PROVIDER: S-EPMC9857766 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature