Workflows to automate covariate-adaptive randomization in REDCap via data entry triggers

Le résumé fourni par la source

Objective: Covariate-adaptive randomization algorithms (CARAs) can reduce covariate imbalance in randomized controlled trials (RCTs), but a lack of integration into Research Electronic Data Capture (REDCap) has limited their use. We developed a software pipeline to seamlessly integrate CARAs into REDCap as part of the all2GETHER study, a 2-armed RCT concerning HIV prevention. Materials and Methods: Leveraging REDCap's Data Entry Trigger and a separate server, we implemented software in PHP and R to automate randomizations for all2GETHER. Randomizations were triggered by saving a specific REDCap form and were automatically communicated to unblinded study personnel. Results: = 0.003 for continuous variables and risk differences <2.4% for categorical/binary variables. Conclusions: Our pipeline proved effective at reducing covariate imbalance with minimal additional effort for study personnel. Discussion: This pipeline is reproducible and could be used by other RCTs that collect data via REDCap.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.