Literature DB >> 20101597

Designing a sequentially randomized study with adherence enhancing interventions for diabetes patients.

Jozefien Buyze1, Bart Van Rompaye, Els Goetghebeur.   

Abstract

Adaptive treatment strategies can change treatment prescription over time in response to intermediate outcomes. They are the natural choice for treating chronic diseases or for prevention, since the condition of subjects tends to change over the long term. Similarly, flexible intervention strategies are vital for generating or sustaining better adherence in long term treatment settings. When a cost-efficient first-line treatment is available, for instance, good adherence is expected to help delay or avoid second-line treatment.Sequentially randomized trials enable unbiased evaluation of how to best adapt adherence supporting interventions to a history of outcomes and adherence with the goal to optimize future treatment response. In this paper we propose and study different sequential designs targeting cost-efficient control of type II diabetes under first-line treatment through two different classes of adherence support: by (bio)technical and by behavioural means. We study their respective and joint impact first through double factorial adaptive designs, where interventions are triggered by an elevated risk of current treatment failure predicted by poor surrogate response.We develop the double factorial design and several derived designs that are more cost-efficient in the context of managed care of diabetes patients. We evaluate the marginal responses over time to different adaptive treatment strategies by means of doubly robust estimators. We consider sample sizes needed to thus detect realistic and worthwhile effects and discuss the relative practical and theoretical merits of the separate designs.

Entities:  

Mesh:

Year:  2010        PMID: 20101597     DOI: 10.1002/sim.3856

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  5 in total

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2.  Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research.

Authors:  Daniel Almirall; Inbal Nahum-Shani; Nancy E Sherwood; Susan A Murphy
Journal:  Transl Behav Med       Date:  2014-09       Impact factor: 3.046

3.  Design and inference for the intent-to-treat principle using adaptive treatment.

Authors:  Ree Dawson; Philip W Lavori
Journal:  Stat Med       Date:  2015-01-11       Impact factor: 2.373

4.  Introduction to dynamic treatment strategies and sequential multiple assignment randomization.

Authors:  Philip W Lavori; Ree Dawson
Journal:  Clin Trials       Date:  2014-05-01       Impact factor: 2.486

5.  SMART designs in cancer research: Past, present, and future.

Authors:  Kelley M Kidwell
Journal:  Clin Trials       Date:  2014-04-14       Impact factor: 2.486

  5 in total

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