Design and analysis considerations for comparing dynamic treatment regimens with binary outcomes from sequential multiple assignment randomized trials

ABSTRACT

In behavioral, educational and medical practice, interventions are often personalized over time using strategies that are based on individual behaviors and characteristics and changes in symptoms, severity, or adherence that are a result of one's treatment. Such strategies that more closely mimic real practice, are known as dynamic treatment regimens (DTRs). A sequential multiple assignment randomized trial (SMART) is a multi-stage trial design that can be used to construct effective DTRs. This article reviews a simple to use ‘weighted and replicated’ estimation technique for comparing DTRs embedded in a SMART design using logistic regression for a binary, end-of-study outcome variable. Based on a Wald test that compares two embedded DTRs of interest from the ‘weighted and replicated’ regression model, a sample size calculation is presented with a corresponding user-friendly applet to aid in the process of designing a SMART. The analytic models and sample size calculations are presented for three of the more commonly used two-stage SMART designs. Simulations for the sample size calculation show the empirical power reaches expected levels. A data analysis example with corresponding code is presented in the appendix using data from a SMART developing an effective DTR in autism.

KEYWORDS:

• Adaptive interventions
• dynamic treatment regimes
• sequential multiple assignment randomized trial
• inverse-probability-of-treatment weighting
• sample size

Acknowledgments

All statements in this presentation, including its findings and conclusions are solely those of the authors and do not necessarily represent the views of the PCORI, its Board of Governors, or Methodology Committee.

Disclosure statement

The authors do not have any conflicts of interest to disclose.

Additional information

Funding

The development of this article was funded by the following grants: ME-1507-31108, P50DA039838, R01DA039901, R01HD073975, R03MH09795401, and 5T32CA083654-12.