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Sequential multiple assignment randomization trials with enrichment design
Author(s) -
Liu Ying,
Wang Yuanjia,
Zeng Donglin
Publication year - 2017
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/biom.12576
Subject(s) - randomization , restricted randomization , computer science , sequential analysis , statistics , mathematics , medicine , clinical trial
Summary Sequential multiple assignment randomization trial (SMART) is a powerful design to study Dynamic Treatment Regimes (DTRs) and allows causal comparisons of DTRs. To handle practical challenges of SMART, we propose a SMART with Enrichment (SMART ER ) design, which performs stage‐wise enrichment for SMART. SMART ER can improve design efficiency, shorten the recruitment period, and partially reduce trial duration to make SMART more practical with limited time and resource. Specifically, at each subsequent stage of a SMART, we enrich the study sample with new patients who have received previous stages’ treatments in a naturalistic fashion without randomization, and only randomize them among the current stage treatment options. One extreme case of the SMART ER is to synthesize separate independent single‐stage randomized trials with patients who have received previous stage treatments. We show data from SMART ER allows for unbiased estimation of DTRs as SMART does under certain assumptions. Furthermore, we show analytically that the efficiency gain of the new design over SMART can be significant especially when the dropout rate is high. Lastly, extensive simulation studies are performed to demonstrate performance of SMART ER design, and sample size estimation in a scenario informed by real data from a SMART study is presented.

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