Cost-effectiveness of using artificial intelligence versus polygenic risk score to guide breast cancer screening.

ABSTRACT:

Background

Current guidelines for mammography screening for breast cancer vary across agencies, especially for women aged 40-49. Using artificial Intelligence (AI) to read mammography images has been shown to predict breast cancer risk with higher accuracy than alternative approaches including polygenic risk scores (PRS), raising the question whether AI-based screening is more cost-effective than screening based on PRS or existing guidelines. This study provides the first evidence to shed light on this important question.

Methods

This study is a model-based economic evaluation. We used a hybrid decision tree/microsimulation model to compare the cost-effectiveness of eight strategies of mammography screening for women aged 40-49 (screening beyond age 50 follows existing guide

SUBMITTER: Mital S 

PROVIDER: S-EPMC9074290 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature