Assessment of performance of the Gail model for predicting breast cancer risk: a systematic review and meta-analysis with trial sequential analysis.

ABSTRACT:

Background

The Gail model has been widely used and validated with conflicting results. The current study aims to evaluate the performance of different versions of the Gail model by means of systematic review and meta-analysis with trial sequential analysis (TSA).

Methods

Three systematic review and meta-analyses were conducted. Pooled expected-to-observed (E/O) ratio and pooled area under the curve (AUC) were calculated using the DerSimonian and Laird random-effects model. Pooled sensitivity, specificity and diagnostic odds ratio were evaluated by bivariate mixed-effects model. TSA was also conducted to determine whether the evidence was sufficient and conclusive.

Results

Gail model 1 accurately predicted breast cancer risk in American women (pooled E/O = 1.03; 95% CI

SUBMITTER: Wang X 

PROVIDER: S-EPMC5850919 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature