Literature DB >> 26243172

Identifying a set that contains the best dynamic treatment regimes.

Ashkan Ertefaie1, Tianshuang Wu2, Kevin G Lynch3, Inbal Nahum-Shani4.   

Abstract

A dynamic treatment regime (DTR) is a treatment design that seeks to accommodate patient heterogeneity in response to treatment. DTRs can be operationalized by a sequence of decision rules that map patient information to treatment options at specific decision points. The sequential, multiple assignment, randomized trial (SMART) is a trial design that was developed specifically for the purpose of obtaining data that informs the construction of good (i.e. efficacious) decision rules. One of the scientific questions motivating a SMART concerns the comparison of multiple DTRs that are embedded in the design. Typical approaches for identifying the best DTRs involve all possible comparisons between DTRs that are embedded in a SMART, at the cost of greatly reduced power to the extent that the number of embedded DTRs (EDTRs) increase. Here, we propose a method that will enable investigators to use SMART study data more efficiently to identify the set that contains the most efficacious EDTRs. Our method ensures that the true best EDTRs are included in this set with at least a given probability. Simulation results are presented to evaluate the proposed method, and the Extending Treatment Effectiveness of Naltrexone SMART study data are analyzed to illustrate its application.
© The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  Double robust; Marginal structural model; Multiple comparisons with the best; SMART designs

Mesh:

Year:  2015        PMID: 26243172      PMCID: PMC4679070          DOI: 10.1093/biostatistics/kxv025

Source DB:  PubMed          Journal:  Biostatistics        ISSN: 1465-4644            Impact factor:   5.899


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  9 in total

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7.  Bayesian set of best dynamic treatment regimes: Construction and sample size calculation for SMARTs with binary outcomes.

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