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An Experimental Paradigm for Developing Adaptive Treatment Strategies

An Experimental Paradigm for Developing Adaptive Treatment Strategies. S.A. Murphy NIDA Meeting on Treatment and Recovery Processes January, 2004. Setting : Management of chronic, relapsing disorders such as alcohol addiction, substance abuse and mental illness Characteristics:

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An Experimental Paradigm for Developing Adaptive Treatment Strategies

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  1. An Experimental Paradigm for Developing Adaptive Treatment Strategies S.A. Murphy NIDA Meeting on Treatment and Recovery Processes January, 2004

  2. Setting: Management of chronic, relapsing disorders such as alcohol addiction, substance abuse and mental illness • Characteristics: • May need a sequence of treatments prior to improvement • Improvement marred by relapse • Intervals during which more intense treatment is required alternate with intervals in which less treatment is sufficient

  3. Adaptive Treatment Strategies are individually tailored treatments, with treatment type and dosage changing with ongoing subject need. Mimic Clinical Practice. • Brooner et al. (2002) Treatment of Opioid Addiction • Breslin et al. (1999) Treatment of Alcohol Addiction • Prokaska et al. (2001) Treatment of Tobacco Addiction • Rush et al. (2003) Treatment of Depression

  4. GOAL: Provide experimental paradigm for developing treatment decision rules.

  5. We need an experimental paradigm that will help us answer: • When to start treatment? • Which treatment to start and for whom? • When to step-up treatment? • Which step-up treatment and for whom? • When to step down treatment to maintenance/monitoring? • Which maintenance/monitoring treatment and for whom? • What information to use to make each of the above decisions?

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

  7. GOAL: Design trials that have the goal of developing treatment decision rules leading to a minimization of the mean response, (mean drinking score over time). PROPOSAL: Sequential within-person randomization: Randomize at each decision point.

  8. Why randomize subjects multiple times? • Initial treatments are best compared in the context of available secondary treatments. • Initial treatment may have delayed effects. • Initial treatment may work together with a particular secondary treatment to lead to an enhanced effect. • Assess best sequencing of treatments.

  9. Examples of sequentially within-person randomized trials: • CATIE (2001) Treatment of Psychosis in Alzheimer’s Patients • CATIE (2001) Treatment of Psychosis in Schizophrenia • STAR*D (2001) Treatment of Depression • Thall et al. (2001) Treatment of Prostate Cancer

  10. Principles in Designing a Sequentially Within-Person Randomized Trial • Secondary treatment alternatives should vary by only a simple low dimension summary (responder status) instead of all intermediate outcomes (adherence, burden, craving, etc.). • Collect intermediate outcomes that might be useful in ascertaining for whom each treatment works best; information that might enter into the decision rules.

  11. Principles in Designing a Sequentially Within-Person Randomized Trial • Choose a primary hypothesis that is both scientifically interesting and aids in the development of the adaptive treatment strategy. • Choose secondary hypotheses that further develop the adaptive treatment strategy and use the randomization to reduce confounding.

  12. Proposal • Primary Analysis: discriminate between strategies with different initial treatments. • In primary analysis consider only simple adaptive treatment strategies with decision rules depending only on summaries of intermediate outcomes (responder/nonresponder) • Use a weighted regression analysis.

  13. Proposal • Secondary analyses: consider more complex adaptive treatment strategies with decision rules depending on intermediate outcomes. • Test if other intermediate outcomes differentiate for whom each future treatment is best and if any pretreatment information differentiates for whom each initial treatment is best. (Murphy, 2003; Robins, 2003)

  14. An analysis that is less useful in the development of adaptive treatment strategies! • Decide whether initial treatment A is better than initial treatment B by comparing intermediate outcomes (responder status).

  15. Two Challenges • How do we use high dimensional information to improve decision making? • Many potential treatment components in an adaptive strategy: how do we discover which are active and if there are unexpected negative interactions?

  16. The paper can be found at http://www.stat.lsa.umich.edu/~samurphy/papers/ExperimentalEvidence.pdf

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