Machine Learning Identifies Clinical and Genetic Factors Associated With Anthracycline Cardiotoxicity in Pediatric Cancer Survivors.

ABSTRACT:

Background

Despite known clinical risk factors, predicting anthracycline cardiotoxicity remains challenging.

Objectives

This study sought to develop a clinical and genetic risk prediction model for anthracycline cardiotoxicity in childhood cancer survivors.

Methods

We performed exome sequencing in 289 childhood cancer survivors at least 3 years from anthracycline exposure. In a nested case-control design, 183 case patients with reduced left ventricular ejection fraction despite low-dose doxorubicin (≤250 mg/m²), and 106 control patients with preserved left ventricular ejection fraction despite doxorubicin >250 mg/m² were selected as extreme phenotypes. Rare/low-frequency variants were collapsed to identify genes differentially enriched for varian

SUBMITTER: Chaix MA 

PROVIDER: S-EPMC8352204 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature