  A sequential multiple assignment randomized trial (SMART) facilitates
comparison of multiple adaptive treatment strategies (ATSs) simultaneously.
Previous studies have established a framework to test the homogeneity of
multiple ATSs by a global Wald test through inverse probability weighting.
SMARTs are generally lengthier than classical clinical trials due to the
sequential nature of treatment randomization in multiple stages. Thus, it would
be beneficial to add interim analyses allowing for early stop if overwhelming
efficacy is observed. We introduce group sequential methods to SMARTs to
facilitate interim monitoring based on multivariate chi-square distribution.
Simulation study demonstrates that the proposed interim monitoring in SMART
(IM-SMART) maintains the desired type I error and power with reduced expected
sample size compared to the classical SMART. Lastly, we illustrate our method
by re-analyzing a SMART assessing the effects of cognitive behavioral and
physical therapies in patients with knee osteoarthritis and comorbid
subsyndromal depressive symptoms.
