Comparing dynamic treatment regimes using repeated-measures outcomes: modeling considerations in SMART studies

Stat Med. 2016 May 10;35(10):1595-615. doi: 10.1002/sim.6819. Epub 2015 Dec 6.


A dynamic treatment regime (DTR) is a sequence of decision rules, each of which recommends a treatment based on a patient's past and current health status. Sequential, multiple assignment, randomized trials (SMARTs) are multi-stage trial designs that yield data specifically for building effective DTRs. Modeling the marginal mean trajectories of a repeated-measures outcome arising from a SMART presents challenges, because traditional longitudinal models used for randomized clinical trials do not take into account the unique design features of SMART. We discuss modeling considerations for various forms of SMART designs, emphasizing the importance of considering the timing of repeated measures in relation to the treatment stages in a SMART. For illustration, we use data from three SMART case studies with increasing level of complexity, in autism, child attention deficit hyperactivity disorder, and adult alcoholism. In all three SMARTs, we illustrate how to accommodate the design features along with the timing of the repeated measures when comparing DTRs based on mean trajectories of the repeated-measures outcome.

Keywords: adaptive intervention; longitudinal analysis; marginal structural model; sequential multiple assignment randomized trial.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Alcoholism / therapy
  • Attention Deficit Disorder with Hyperactivity / therapy
  • Autistic Disorder / therapy
  • Child
  • Child, Preschool
  • Humans
  • Randomized Controlled Trials as Topic*
  • Research Design*
  • Statistics as Topic*
  • Treatment Outcome

Grant support