Quantifying Sex Bias in Clinical Studies at Scale With Automated Data Extraction.

ABSTRACT: Importance:Analyses of female representation in clinical studies have been limited in scope and scale. Objective:To perform a large-scale analysis of global enrollment sex bias in clinical studies. Design, Setting, and Participants:In this cross-sectional study, clinical studies from published articles from PubMed from 1966 to 2018 and records from Aggregate Analysis of ClinicalTrials.gov from 1999 to 2018 were identified. Global disease prevalence was determined for male and female patients in 11 disease categories from the Global Burden of Disease database: cardiovascular, diabetes, digestive, hepatitis (types A, B, C, and E), HIV/AIDS, kidney (chronic), mental, musculoskeletal, neoplasms, neurological, and respiratory (chronic). Machine reading algorithms were developed that extracted s

SUBMITTER: Feldman S 

PROVIDER: S-EPMC6613296 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature