Biostatistics, Epidemiology and Research Design Pilot Award
By Kelly Hale, Communications Coordinator
May 16, 2024
Title: Exploring Bayesian Adaptive Designs in Patient Preference Randomized Trials
PI: Alexandra Brown, Ph.D., University of Kansas Medical Center
Project synopsis: Premature birth is the leading cause of infant death and yet the rate of premature births is still increasing over the last decade. Docosahexaenoic acid (DHA) is currently the most effective tool to prevent preterm birth, but critical barriers (e.g. dislike of swallowing capsules) hinder proper DHA supplementation. To break these barriers, the research team will implement a patient-preference clinical trial utilizing adaptive randomization. The innovative trial design will include randomizing a group of participants to an arm allowing them to choose how to take their DHA: chews or capsules. Two other arms will be included in randomization and participants will be given either chews or capsules. They will also utilize Bayesian methods (statistical innovations) in their trial’s adaptive design and analysis and have extensive expertise in working with pregnant women and in executing adaptive clinical trials. Altogether, the study uses innovative Bayesian trial design and patient-preference strategies to improve adherence to DHA supplementation to reduce premature birth and infant mortality rates.
This work will support a clinical trial (OPT DHA, PI: Christifano) that uses patient choice as part of the trial to improve study adherence by developing the optimal study design using several trial factors and will utilize Bayesian methods to understand ways to integrate the patient-preference arm with the other two treatment arms.
“We want to provide information to clinicians on how best to improve adherence to taking DHA,” Brown said. “We hope to determine whether providing DHA supplementation through capsules or chews provides the highest adherence resulting in higher levels of DHA at delivery.”
“When this study started, I was pregnant with my son and really enjoyed getting to be a part of it. I became invested in this study, and it really helped me move forward in completing my Ph.D. My mentors during all this have been so supportive and helped me gain experience to move into my own research. I can’t thank them enough for all the encouragement along the way. I’m also thankful to Frontiers for this funding; I’m just so appreciative.”
Brown plans to continue her research in the areas of statistical innovations in clinical trial design and execution with a focus on maternal and infant health, and rural health communities.