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

Slides:



Advertisements
Similar presentations
Piloting and Sizing Sequential Multiple Assignment Randomized Trials in Dynamic Treatment Regime Development 2012 Atlantic Causal Inference Conference.
Advertisements

Treatment Effect Heterogeneity & Dynamic Treatment Regime Development S.A. Murphy.
Experimenting to Improve Clinical Practice S.A. Murphy AAAS, 02/15/13 TexPoint fonts used in EMF. Read the TexPoint manual before you delete this box.:
1 Developing Dynamic Treatment Regimes for Chronic Disorders S.A. Murphy Univ. of Michigan RAND: August, 2005.
Journal Club Alcohol, Other Drugs, and Health: Current Evidence January–February 2009.
1 Dynamic Treatment Regimes Advances and Open Problems S.A. Murphy ICSPRAR-2008.
1 Developing Adaptive Treatment Strategies using MOST Experimental Designs S.A. Murphy Univ. of Michigan Dallas: December, 2005.
Methodology for Adaptive Treatment Strategies for Chronic Disorders: Focus on Pain S.A. Murphy NIH Pain Consortium 5 th Annual Symposium on Advances in.
Experiments and Dynamic Treatment Regimes S.A. Murphy Univ. of Michigan JSM: August, 2005.
SMART Designs for Constructing Adaptive Treatment Strategies S.A. Murphy 15th Annual Duke Nicotine Research Conference September, 2009.
Dynamic Treatment Regimes, STAR*D & Voting D. Lizotte, E. Laber & S. Murphy LSU ---- Geaux Tigers! April 2009.
Journal Club Alcohol, Other Drugs, and Health: Current Evidence May-June 2007.
Substance Abuse, Multi-Stage Decisions, Generalization Error How are they connected?! S.A. Murphy Univ. of Michigan CMU, Nov., 2004.
An Experimental Paradigm for Developing Dynamic Treatment Regimes S.A. Murphy Univ. of Michigan March, 2004.
Constructing Dynamic Treatment Regimes & STAR*D S.A. Murphy ICSA June 2008.
Screening Experiments for Developing Dynamic Treatment Regimes S.A. Murphy At ICSPRAR January, 2008.
SMART Designs for Developing Adaptive Treatment Strategies S.A. Murphy K. Lynch, J. McKay, D. Oslin & T.Ten Have CPDD June, 2005.
Dynamic Treatment Regimes: Challenges in Data Analysis S.A. Murphy Survey Research Center January, 2009.
Sizing a Trial for the Development of Adaptive Treatment Strategies Alena I. Oetting The Society for Clinical Trials, 29th Annual Meeting St. Louis, MO.
Experiments and Dynamic Treatment Regimes S.A. Murphy Univ. of Michigan Florida: January, 2006.
SMART Experimental Designs for Developing Adaptive Treatment Strategies S.A. Murphy NIDA DESPR February, 2007.
Hypothesis Testing and Dynamic Treatment Regimes S.A. Murphy Schering-Plough Workshop May 2007 TexPoint fonts used in EMF. Read the TexPoint manual before.
Michigan Team February, Amy Wagaman Bibhas Chakraborty Herle McGowan Susan Murphy Lacey Gunter Danny Almirall Anne Buu.
An Experimental Paradigm for Developing Adaptive Treatment Strategies S.A. Murphy Univ. of Michigan UNC: November, 2003.
Experiments and Dynamic Treatment Regimes S.A. Murphy Univ. of Michigan PSU, October, 2005 In Honor of Clifford C. Clogg.
Planning Survival Analysis Studies of Dynamic Treatment Regimes Z. Li & S.A. Murphy UNC October, 2009.
Statistical Issues in Developing Adaptive Treatment Strategies for Chronic Disorders S.A. Murphy Univ. of Michigan CDC/ATSDR: March, 2005.
SMART Experimental Designs for Developing Adaptive Treatment Strategies S.A. Murphy RWJ Clinical Scholars Program, UMich April, 2007.
Hypothesis Testing and Dynamic Treatment Regimes S.A. Murphy, L. Gunter & B. Chakraborty ENAR March 2007.
1 SMART Designs for Developing Adaptive Treatment Strategies S.A. Murphy K. Lynch, J. McKay, D. Oslin & T.Ten Have UMichSpline February, 2006.
Dynamic Treatment Regimes, STAR*D & Voting D. Lizotte, E. Laber & S. Murphy ENAR March 2009.
Methodology for Adaptive Treatment Strategies R21 DA S.A. Murphy For MCATS Oct. 8, 2009.
An Experimental Paradigm for Developing Adaptive Treatment Strategies S.A. Murphy Univ. of Michigan ACSIR, July, 2003.
Dynamic Treatment Regimes, STAR*D & Voting D. Lizotte, E. Laber & S. Murphy Psychiatric Biostatistics Symposium May 2009.
An Experimental Paradigm for Developing Adaptive Treatment Strategies S.A. Murphy Univ. of Michigan February, 2004.
Experiments and Dynamic Treatment Regimes S.A. Murphy Univ. of Michigan Yale: November, 2005.
Methods for Estimating the Decision Rules in Dynamic Treatment Regimes S.A. Murphy Univ. of Michigan IBC/ASC: July, 2004.
Discussion of Profs. Robins’ and M  ller’s Papers S.A. Murphy ENAR 2003.
1 Possible Roles for Reinforcement Learning in Clinical Research S.A. Murphy November 14, 2007.
Experiments and Dynamic Treatment Regimes S.A. Murphy Univ. of Michigan April, 2006.
SMART Designs for Developing Dynamic Treatment Regimes S.A. Murphy MD Anderson December 2006.
Exploratory Analyses Aimed at Generating Proposals for Individualizing and Adapting Treatment S.A. Murphy BPRU, Hopkins September 22, 2009.
SMART Experimental Designs for Developing Adaptive Treatment Strategies S.A. Murphy ISCTM, 2007.
1 Section IV Study Designs for Investigating Adaptive Treatment Strategies Murphy.
Experiments and Adaptive Treatment Strategies S.A. Murphy Univ. of Michigan Chicago: May, 2005.
Susan Murphy, PI University of Michigan Acknowledgements: MCAT network and NIH The Goal To facilitate methodological collaborations necessary for producing.
1 Dynamic Treatment Regimes: Interventions for Chronic Conditions (such as Poverty or Criminality?) S.A. Murphy Univ. of Michigan In Honor of Clifford.
SMART Designs for Developing Dynamic Treatment Regimes S.A. Murphy Symposium on Causal Inference Johns Hopkins, January, 2006.
Experiments and Dynamic Treatment Regimes S.A. Murphy At NIAID, BRB December, 2007.
1 Machine/Reinforcement Learning in Clinical Research S.A. Murphy May 19, 2008.
Adaptive Treatment Strategies S.A. Murphy CCNIA Proposal Meeting 2008.
Adaptive Treatment Strategies S.A. Murphy Workshop on Adaptive Treatment Strategies Convergence, 2008.
Practical Application of Adaptive Treatment Strategies in Trial Design and Analysis S.A. Murphy Center for Clinical Trials Network Classroom Series April.
Experiments and Dynamic Treatment Regimes S.A. Murphy Univ. of Michigan January, 2006.
1 Variable Selection for Tailoring Treatment S.A. Murphy, L. Gunter & J. Zhu May 29, 2008.
Hypothesis Testing and Adaptive Treatment Strategies S.A. Murphy SCT May 2007.
Adaptive Treatment Design and Analysis S.A. Murphy TRC, UPenn April, 2007.
Adaptive Treatment Strategies: Challenges in Data Analysis S.A. Murphy NY State Psychiatric Institute February, 2009.
Sequential, Multiple Assignment, Randomized Trials and Treatment Policies S.A. Murphy UAlberta, 09/28/12 TexPoint fonts used in EMF. Read the TexPoint.
Overview of Adaptive Treatment Regimes Sachiko Miyahara Dr. Abdus Wahed.
The NIDA Clinical Trials is conducting the Prescription Opioid Addiction Treatment Study (POATS) – a multi- site trial examining different lengths and.
Sequential, Multiple Assignment, Randomized Trials and Treatment Policies S.A. Murphy MUCMD, 08/10/12 TexPoint fonts used in EMF. Read the TexPoint manual.
Obtaining housing associated with achieving abstinence after detoxification in adults with addiction Tae Woo Park, Christine Maynié-François, Richard Saitz.
Sequential, Multiple Assignment, Randomized Trials Module 2—Day 1 Getting SMART About Developing Individualized Adaptive Health Interventions Methods Work,
Introduction Sample Size Calculation for Comparing Strategies in Two-Stage Randomizations with Censored Data Zhiguo Li and Susan Murphy Institute for Social.
A SMART Design to Optimize a Palliative Care Intervention for Patient and Family Caregiver Outcomes Mi-Kyung Song, PhD, RN, FAAN University of North Carolina.
1 SMART Designs for Developing Adaptive Treatment Strategies S.A. Murphy K. Lynch, J. McKay, D. Oslin & T.Ten Have NDRI April, 2006.
Motivation Using SMART research designs to improve individualized treatments Alena Scott 1, Janet Levy 3, and Susan Murphy 1,2 Institute for Social Research.
Designing An Adaptive Treatment Susan A. Murphy Univ. of Michigan Joint with Linda Collins & Karen Bierman Pennsylvania State Univ.
SMART Trials for Developing Adaptive Treatment Strategies S.A. Murphy Workshop on Adaptive Treatment Designs NCDEU, 2006.
Presentation transcript:

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: 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

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

GOAL: Provide experimental paradigm for developing treatment decision rules.

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?

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

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.

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.

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

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.

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.

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.

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)

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).

Two Challenges 1)How do we use high dimensional information to improve decision making? 2)Many potential treatment components in an adaptive strategy: how do we discover which are active and if there are unexpected negative interactions?

The paper can be found at idence.pdf