Designing a Pilot Sequential Multiple Assignment Randomized Trial for Developing an Adaptive Treatment Strategy

By D. Almirall, Scott N. Compton, Meredith Gunlicks-Stoessel, N. Duan, Susan A. Murphy. 2012

219 citations recorded by the source corpus.

There is growing interest in how best to adapt and readapt treatments to individuals to maximize clinical benefit. In response, adaptive treatment strategies (ATS), which operationalize adaptive, sequential clinical decision making, have been developed. From a patient's perspective an ATS is a sequence of treatments, each individualized to the patient's evolving health status. From a clinician's perspective, an ATS is a sequence of decision rules that input the patient's current health status and output the next recommended treatment. Sequential multiple assignment randomized trials (SMART) have been developed to address the sequencing questions that arise in the development of ATSs, but SMARTs are relatively new in clinical research. This article provides an introduction to ATSs and SMART designs. This article also discusses the design of SMART pilot studies to address feasibility concerns, and to prepare investigators for a full‐scale SMART. We consider an example SMART for the development of an ATS in the treatment of pediatric generalized anxiety disorders. Using the example SMART, we identify and discuss design issues unique to SMARTs that are best addressed in an external pilot study prior to the full‐scale SMART. We also address the question of how many participants are needed in a SMART pilot study. A properly executed pilot study can be used to effectively address concerns about acceptability and feasibility in preparation for (that is, prior to) executing a full‐scale SMART. Copyright © 2012 John Wiley & Sons, Ltd.

Subfields: Economics and Econometrics, Statistics and Probability

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Citations in the corpus

Supervised Reinforcement Learning with Recurrent Neural Network for Dynamic Treatment Recommendation (2018, background): “Early treatment recommendation systems heuristically map diseases into medications based on expert systems [2, 13, 43].”
An introduction to implementation science for the non-specialist (2015, methodology): “A quantitative version of formative evaluation in clinical trials is the use of sequential multiple assignment randomized trials (SMART) or adaptive intervention designs, which are used to either augment or switch treatments at critical decision points where there is evidence of initial non-response”
Experimental and Quasi-Experimental Designs in Implementation Research (2019, background): “Researchers interested in optimizing sequences of implementation strategies that adapt to ongoing needs over time may be interested in a variant of factorial designs known as the sequential, multiple-assignment randomized trial (SMART; Almirall et al., 2012; Collins et al., 2014b; Kilbourne et al., ”
Adaptive Interventions in Child and Adolescent Mental Health (2016, background): “Other adaptive intervention design considerations are discussed in Collins et al. (2004) and Almirall et al. (2012).”
LEAP: Learning to Prescribe Effective and Safe Treatment Combinations for Multimorbidity (2017, background): “Existing treatment recommendation systems are mainly implemented using rule-based protocols defined by doctors based on clinical guidelines or personal experience [1, 8, 14].”
A Pilot SMART for Developing an Adaptive Treatment Strategy for Adolescent Depression (2015, unknown): “, recruitment, randomization) and (b) implement the treatments that compose the ATSs (Almirall et al., 2012).”