SMART Designs for Developing Adaptive Treatment Strategies

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SMART Designs for Developing Adaptive Treatment Strategies S.A. Murphy K. Lynch, J. McKay, D. Oslin & T.Ten Have CPDD June, 2005

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SMART Designs for Developing Adaptive Treatment Strategies. S.A. Murphy K. Lynch, J. McKay, D. Oslin & T.Ten Have CPDD June, 2005. Setting : Management of chronic, relapsing disorders such as drug dependence and mental illness Characteristics: - PowerPoint PPT Presentation

Transcript of SMART Designs for Developing Adaptive Treatment Strategies

Page 1: SMART Designs for Developing Adaptive Treatment Strategies

SMART Designs for Developing Adaptive Treatment Strategies

S.A. Murphy

K. Lynch, J. McKay, D. Oslin & T.Ten Have

CPDD

June, 2005

Page 2: SMART Designs for Developing Adaptive Treatment Strategies

Setting: Management of chronic, relapsing disorders such as drug dependence and mental illness

Characteristics:

•May need a sequence of treatments prior to improvement

•Improvement often marred by relapse

•Intervals during which more intense treatment is required alternate with intervals in which less treatment is sufficient

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Adaptive Treatment Strategies are individually tailored treatments, with treatment type and dosage changing with patient need. Mimic Clinical Practice.

•Brooner et al. (2002) Treatment of Cocaine Addiction

•Breslin et al. (1999) Treatment of Alcohol Addiction

•Prokaska et al. (2001) Treatment of Tobacco Addiction

•Rush et al. (2003) Treatment of Depression

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EXAMPLE: Treatment of alcohol dependency. Primary outcome is a summary of heavy drinking scores over time.

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Treatment of Alcohol Dependency

Initial Txt Intermediate Outcome Secondary Txt

TDM +Responder counseling

TDM

Med B

Med ANonresponder

EM + Med B+ Psychosocial

Intensive OutpatientProgram

Responder TDM +counseling

TDM

Med A + Psychosocial Med B

Nonresponder

EM +Med B+Psychosocial

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GOAL: Provide experimental methods for developing treatment assignment, i.e. decision, rules.

Primary Outcome: a summary of drinking scores over time

GOAL: How do we design trials so as to develop decision rules that minimize drinking?

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The Challenges

•Delayed Effects

---sequential multiple assignment randomized trials (SMART)

•Adaptive Treatment Strategies are High Dimensional Multi-component Treatments

---series of developmental, randomized trials prior to confirmatory trial (MOST).

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What is a sequential multiple assignment randomized trial (SMART)?

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Sequential Multiple Assignment Randomization

Initial Txt Intermediate Outcome Secondary Txt

TDM +

Responder R counseling

TDM

Med B

Med A

Nonresponder REM + Med B+ Psychosocial

R

Responder TDM +

R counseling

TDM

Med A + Psychosocial Med B

Nonresponder R

EM +Med B+Psychosocial

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Why a SMART design?

Or, why choosing the best initial treatment on the basis of a randomized trial of initial treatments and choosing the best secondary treatment on the basis of a randomized trial of secondary treatments is not the best way to construct an adaptive treatment strategy.

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Cohort Effects

Subjects who will enroll in, who remain in or who are adherent in the trial of the initial treatments may be quite different from the subjects in SMART.

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Delayed Effects

Negative synergies: An initial treatment may produce a higher proportion of responders but also produce side effects that reduce the effectiveness of subsequent treatments for those that do not respond. Or the burden imposed by this initial treatment may be sufficiently high so that nonresponders are less likely to adhere to subsequent treatments.

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Delayed Effects

Positive synergies: A treatment may not appear best initially but may have enhanced long term effectiveness when followed by a particular maintenance treatment. Or the initial treatment may lay the foundation for an enhanced effect of subsequent treatments.

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Summary:

When evaluating and comparing initial treatments we need to take into account the effects of the secondary

treatments thus SMART

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Sequential Multiple Assignment Randomization

Initial Txt Intermediate Outcome Secondary Txt

TDM+

Responder R counseling

TDM

Med B

Med A

Nonresponder REM + Med B+ Psychosocial

R

Responder TDM+

R counseling

TDM

Med A + Psychosocial Med B

Nonresponder R

EM +Med B+Psychosocial

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Examples of SMART designs:

•CATIE (2001) Treatment of Psychosis in Alzheimer’s Patients

•CATIE (2001) Treatment of Psychosis in Schizophrenia

•STAR*D (2003) Treatment of Depression

•Thall et al. (2000) Treatment of Prostate Cancer

•Oslin (on-going) Treatment of Alcohol Dependence

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SMART Designing Principles

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SMART Designing Principles

•At each decision point, restrict class of treatments only by ethical, feasibility or strong scientific considerations. Use a low dimension summary (responder status) instead of all intermediate outcomes (time until nonresponse, adherence, burden, stress level, etc.) to restrict class of treatments.

•Collect intermediate outcomes that might be useful in ascertaining for whom each treatment works best; information that might enter into the decision rules.

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SMART Designing Principles

•Choose a primary hypothesis that is both scientifically important and aids in developing the adaptive treatment strategy.

•EXAMPLE: Hypothesize that given the secondary treatments provided, the initial treatment Med A + psychosocial counseling leads to lower drinking than the initial treatment Med A alone.

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SMART Designing Principles

•Choose secondary hypotheses that further develop the adaptive treatment strategy and use the randomization to eliminate confounding.

•EXAMPLE: Hypothesize that non-adhering non-responders will have lower drinking if provided a change in medication + EM+ counseling as compared to a change in medication only.

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Discussion

• Trial design and analyses targeted at scientific goal.• Increased confidence that developed adaptive

treatment strategy will be better than standard care (increased power).

• Lower chance of wanting/needing to change treatment decision rules midway through confirmatory trial.

• Employ MOST to construct an adaptive treatment strategy.

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This seminar can be found at:http://www.stat.lsa.umich.edu/~samurphy/

seminars/CPDD0605.ppt

This seminar is based on a paper with Kevin Lynch, Jim McKay, David Oslin and Tom Ten Have. Email me with questions or if you would like a copy:

[email protected]