Grant: Expanding the Methodological Toolbox for Sequential, Multiple Assignment, Randomized Trials (SMARTs)

smartWORDLESSOctober 31, 2016:

Over the course of treatment, a clinician often alters treatment based on patient characteristics or response to earlier treatment. Sequential, multiple assignment, randomized trial (SMART) designs provide the data needed to construct high-quality adaptive interventions. Interventions that adapt at the right times (e.g., intensifying for people who do not respond to the initial treatment) can improve participant outcomes while decreasing the cost and burden of the intervention (e.g., stepping down treatment for responsive participants). SMART designs are currently being used around the world in dozens of trials to build adaptive interventions for drug use, HIV, ADHD, autism, obesity, and more.

Last year, a team of Methodology Center researchers was awarded a grant from the National Institute on Drug Abuse (R01 DA039901) to expand the methodological toolbox available for intervention designers seeking to analyze data and plan future SMART studies.

This research will develop multilevel models to allow intervention scientists to answer new questions using longitudinal data from a SMART—for example, to compare the effect of two adaptive interventions on changes in craving or substance use over time. The research will also develop sample size calculators to facilitate the planning of SMARTs studies with longitudinal outcomes. Co-principal investigators Inbal (Billie) Nahum Shani and Daniel Almirall are excited about the potential of this research to further expand the usefulness of SMART designs. Billie said, “Right now, the methods that we have for analyzing and planning sample size for SMART studies are relatively limited.  For example, they allow us to compare adaptive interventions only in terms of end-of-study outcome. However, many scientists are interested in taking advantage of longitudinal data they often collect in the course of a SMART study, and using it to compare adaptive interventions in terms of trajectories of change. For example, scientists may want to study change in HIV-risk behavior during the course of the intervention program. This is because modeling change, rather than end-of-study outcome, provides greater statistical power and a more nuanced picture of how the adaptive intervention works. In this project we will develop the tools to allow intervention designers conduct these analyses and plan future SMARTs with longitudinal outcomes.”

Other researchers on the team that include Linda Collins, John Dziak, and Susan Murphy. Billie, Danny, and Susan are based at University of Michigan, and Linda and John are at Penn State. This grant will add five more years of methodological research to the development of SMART, allowing this valuable method to be applied even more broadly.

Read more about SMART 

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