Detection of Pathogenic Variants With Germline Genetic Testing Using Deep Learning vs Standard Methods in Patients With Prostate Cancer and Melanoma.

ABSTRACT:

Importance

Less than 10% of patients with cancer have detectable pathogenic germline alterations, which may be partially due to incomplete pathogenic variant detection.

Objective

To evaluate if deep learning approaches identify more germline pathogenic variants in patients with cancer.

Design, setting, and participants

A cross-sectional study of a standard germline detection method and a deep learning method in 2 convenience cohorts with prostate cancer and melanoma enrolled in the US and Europe between 2010 and 2017. The final date of clinical data collection was December 2017.

Exposures

Germline variant detection using standard or deep learning methods.

Main outcomes and measures

The primary outcomes included pathogenic variant detection performance in

SUBMITTER: AlDubayan SH 

PROVIDER: S-EPMC7672519 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature