Enhancing DHA supplementation adherence: A Bayesian approach with finite mixture models and irregular interim schedules in adaptive trial designs.

ABSTRACT: Docosahexaenoic acid (DHA) supplementation has proven beneficial in reducing preterm births. However, the challenge lies in addressing nonadherence to prescribed supplementation regimens-a hurdle that significantly impacts clinical trial outcomes. Conventional methods of adherence estimation, such as pill counts and questionnaires, usually fall short when estimating adherence within a specific dosage group. Thus, we propose a Bayesian finite mixture model to estimate adherence among women with low baseline red blood cell phospholipid DHA levels (<6%) receiving higher DHA doses. In our model, adherence is defined as the proportion of participants classified into one of the two distinct components in a normal mixture distribution. Subsequently, based on the estimands from the adherence model

SUBMITTER: Dutta S 

PROVIDER: S-EPMC11576245 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature