Optimal Dynamic Treatment Regimes

Murphy, Susan A.

doi:10.1111/1467-9868.00389

Cited by 831 publications

(942 citation statements)

References 29 publications

(71 reference statements)

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“…AIs are also known by a variety of different names. In the statistical literature, they are commonly referred to as dynamic treatment regimes [17,19,[25][26][27][28][29][30][31][32][33][34][35][36][37] (or, more appropriately, regimens). In the mental health and substance use literatures, they are more commonly known as adaptive treatment strategies [38,39].…”

Section: Adaptive Interventionsmentioning

confidence: 99%

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

Almirall

Nahum‐Shani

Sherwood

et al. 2014

Behav. Med. Pract. Policy Res.

337

274

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The management of many health disorders often entails a sequential, individualized approach whereby treatment is adapted and readapted over time in response to the specific needs and evolving status of the individual. Adaptive interventions provide one way to operationalize the strategies (e.g., continue, augment, switch, step-down) leading to individualized sequences of treatment. Often, a wide variety of critical questions must be answered when developing a highquality adaptive intervention. Yet, there is often insufficient empirical evidence or theoretical basis to address these questions. The Sequential Multiple Assignment Randomized Trial (SMART)-a type of research design-was developed explicitly for the purpose of building optimal adaptive interventions by providing answers to such questions. Despite increasing popularity, SMARTs remain relatively new to intervention scientists. This manuscript provides an introduction to adaptive interventions and SMARTs. We discuss SMART design considerations, including common primary and secondary aims. For illustration, we discuss the development of an adaptive intervention for optimizing weight loss among adult individuals who are overweight. KEYWORDS

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Section: Adaptive Interventionsmentioning

confidence: 99%

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

Almirall

Nahum‐Shani

Sherwood

et al. 2014

Behav. Med. Pract. Policy Res.

337

274

View full text Add to dashboard Cite

show abstract

“…For those who desire more precision, we recommend looking into research in statistics, medicine, computer science, and other fields, where determining the optimal decision rule is currently an extremely active area. For example, see Shachter (1986), Owens et al (1997), Murphy (2003), Bather (2000), Cowell et al (1999), and Bertsekas and Tsitsiklis (1996). In particular, the last four consider the highly complex time-varying setting, where interactions among tailoring variables and effects of prior decisions are incorporated.…”

Section: Articulating the Model Relating Tailoring Variables Dosagementioning

confidence: 99%

“…As more scientists articulate these relations, perhaps information will accumulate that will be helpful to the prevention science community at large, including new procedures for establishing the relations empirically. Research is also needed on methods for estimating decisions rules that will optimize response (e.g., Murphy, 2003).…”

Section: Future Research Directions and Open Questionsmentioning

confidence: 99%

A Conceptual Framework for Adaptive Preventive Interventions

2004

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Recently, adaptive interventions have emerged as a new perspective on prevention and treatment.Adaptive interventions resemble clinical practice in that different dosages of certain prevention or treatment components are assigned to different individuals, and/or within individuals across time, with dosage varying in response to the intervention needs of individuals. To determine intervention need and thus assign dosage, adaptive interventions use prespecified decision rules based on each participant's values on key characteristics, called tailoring variables. In this paper, we offer a conceptual framework for adaptive interventions, discuss principles underlying the design and evaluation of such interventions, and review some areas where additional research is needed. Keywords adaptive interventions; prevention; research designFor most of the history of research-based interventions aimed at prevention and treatment, the composition and dosage of these interventions have been fixed, in other words, a single composition and dosage has been offered to all program participants. For example, a schoolbased drug abuse prevention curriculum might be delivered to all sixth graders. Every component of the intervention that may be necessary for any particular participant is included in the curriculum, and each child is given the same intervention. Although it is recognized that individuals may have different intervention needs, it is expected that the intervention is in no way diluted or made counterproductive if components that are particularly relevant for an individual are combined with components that may have less, or even no, relevance for that individual.Recently, adaptive interventions have emerged as a new perspective on research-based prevention and treatment. According to this perspective, the varying intervention needs of individuals may not be met optimally by using a single uniform composition and dosage. For this reason, an adaptive intervention assigns different dosages of certain program components across individuals, and/or within individuals across time. Dosage varies in response to the intervention needs of individuals, and dosages are assigned based on decision rules linking characteristics of the individual with specific levels and types of

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“…It is crucial that methods from statistics be combined with methods from reinforcement learning to reduce the bias when observational data is used. This is the subject of extensive research in statistics (Murphy, 2003;Robbins, 2004).…”

Section: Resultsmentioning

confidence: 99%

“…Clinical guidelines individualize treatment by recommending treatment type, dosage, or duration depending on the patient's history of treatment response, adherence, and burden. Adaptive treatment strategies Dawson, 1998,2003;Lavori et al, 2000;Murphy, 2003;Murphy and McKay, 2004;Collins et al, 2004) are operationalized clinical guidelines. These strategies consist of a sequence of "decision rules" which individually tailor a sequence of treatments for individual patients.…”

Section: Introductionmentioning

confidence: 99%

Constructing evidence-based treatment strategies using methods from computer science

Pineau

Bellemare

Rush

et al. 2007

Drug and Alcohol Dependence

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This paper details a new methodology, instance-based reinforcement learning, for constructing adaptive treatment strategies from randomized trials. Adaptive treatment strategies are operationalized clinical guidelines which recommend the next best treatment for an individual based on his/her personal characteristics and response to earlier treatments. The instance-based reinforcement learning methodology comes from the computer science literature, where it was developed to optimize sequences of actions in an evolving, time varying system. When applied in the context of treatment design, this method provides the means to evaluate both the therapeutic and diagnostic effects of treatments in constructing an adaptive treatment strategy. The methodology is illustrated with data from the STAR*D trial, a multi-step randomized study of treatment alternatives for individuals with treatment-resistant major depressive disorder.

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Optimal Dynamic Treatment Regimes

Cited by 831 publications

References 29 publications

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

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

A Conceptual Framework for Adaptive Preventive Interventions

Constructing evidence-based treatment strategies using methods from computer science

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