1. BestFIT Sequential Multiple Assignment Randomized Trial Results: A SMART Approach to Developing Individualized Weight Loss Treatment Sequences.
- Author
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Sherwood, Nancy E, Crain, A Lauren, Seburg, Elisabeth M, Butryn, Meghan L, Forman, Evan M, Crane, Melissa M, Levy, Rona L, Kunin-Batson, Alicia S, and Jeffery, Robert W
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WEIGHT loss , *RANDOMIZED controlled trials - Abstract
Background: State-of-the-art behavioral weight loss treatment (SBT) can lead to clinically meaningful weight loss, but only 30-60% achieve this goal. Developing adaptive interventions that change based on individual progress could increase the number of people who benefit.Purpose: Conduct a Sequential Multiple Assignment Randomized Trial (SMART) to determine the optimal time to identify SBT suboptimal responders and whether it is better to switch to portion-controlled meals (PCM) or acceptance-based treatment (ABT).Method: The BestFIT trial enrolled 468 adults with obesity who started SBT and were randomized to treatment response assessment at Session 3 (Early TRA) or 7 (Late TRA). Suboptimal responders were re-randomized to PCM or ABT. Responders continued SBT. Primary outcomes were weight change at 6 and 18 months.Results: PCM participants lost more weight at 6 months (-18.4 lbs, 95% CI -20.5, -16.2) than ABT participants (-15.7 lbs, 95% CI: -18.0, -13.4), but this difference was not statistically significant (-2.7 lbs, 95% CI: -5.8, 0.5, p = .09). PCM and ABT participant 18 month weight loss did not differ. Early and Late TRA participants had similar weight losses (p = .96), however, Early TRA PCM participants lost more weight than Late TRA PCM participants (p = .03).Conclusions: Results suggest adaptive intervention sequences that warrant further research (e.g., identify suboptimal responders at Session 3, use PCMs as second-stage treatment). Utilizing the SMART methodology to develop an adaptive weight loss intervention that would outperform gold standard SBT in a randomized controlled trial is an important next step, but may require additional optimization work.Clinical Trial Information: ClinicalTrials.gov identifier; NCT02368002. [ABSTRACT FROM AUTHOR]- Published
- 2022
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