Methodology for Adaptive Treatment Strategies R21 DA S.A. Murphy For MCATS Oct. 8, 2009

2 Overview Network involving computer scientists, engineers, physicians (mental health, infectious disease, substance abuse ), psychologists and statisticians. Goal: Identify major challenges & kick-start collaborations leading to longer term research initiatives Two workshops; white paper; special issue of Drug and Alcohol Dependence in 2007 September August 2006

3 Some Consequences A number of funded grants: R01s and a P01 Many papers + book by J. McKay : Treating Substance Use Disorders With Adaptive Continuing Care. Summer program (2007) for computer scientists, engineers and statisticians at the Statistical and Applied Mathematical Sciences Institute. Clinical trials designed to inform adaptive treatment strategies

4 Adaptive Treatment Strategies operationalize multi- stage decision making. These are individually tailored sequences of treatments, with treatment type and dosage adapted to the individual. Generalization from a one-time decision to a sequence of decisions concerning treatments Operationalize clinical practice. Each decision corresponds to a stage of treatment

Adaptive Drug Court Program

Critical Questions What is the best sequencing of treatments? Which treatment to provide first, second? What is the best timings of alterations in treatments? What information do we use to make these decisions? (how do we individualize the sequence of treatments?)

7 Methodological Innovations New experimental designs for comparing and constructing adaptive treatment strategies: SMART Transfer/generalization of data analysis methods for multi-stage decision making from the fields of computer science and engineering: Q-Learning

SMART Sequential Multiple Assignment Randomized Trial These are multi-stage trials; individuals move through multiple stages of treatment and are initially randomized and then re-randomized at each stage. Each stage corresponds to a critical decision.

SMART Precursors of the SMART design: CATIE (2001), STAR*D (2003), many in cancer SMART designs: Treatment of Alcohol Dependence (Oslin, data analysis; NIAAA) Treatment of ADHD (Pelham, data analysis ; IES) Treatment of Drug Abusing Pregnant Women (Jones, in field; NIDA) Treatment of Autism (Kasari, in field; Foundation) Treatment of Alcoholism (McKay, in field; NIAAA) Treatment of Prostate Cancer (Millikan, 2007)

Alcohol Dependence (Oslin; NIAAA) Late Trigger for Nonresponse 8 wks Response TDM + Naltrexone CBI Random assignment: CBI +Naltrexone Nonresponse Early Trigger for Nonresponse Random assignment: Naltrexone 8 wks Response Random assignment: CBI +Naltrexone CBI TDM + Naltrexone Naltrexone Nonresponse

Does improving adherence help? Late Trigger for Nonresponse 8 wks Response TDM + Naltrexone CBI Random assignment: CBI +Naltrexone Nonresponse Early Trigger for Nonresponse Random assignment: Naltrexone 8 wks Response Random assignment: CBI +Naltrexone CBI TDM + Naltrexone Naltrexone Nonresponse

Least Intensive vs Most Intensive Late Trigger for Nonresponse 8 wks Response TDM + Naltrexone CBI Random assignment: CBI +Naltrexone Nonresponse Early Trigger for Nonresponse Random assignment: Naltrexone 8 wks Response Random assignment: CBI +Naltrexone CBI TDM + Naltrexone Naltrexone Nonresponse

Drug-Addicted Pregnant Women (Jones; NIDA) rRBT 2 wks Response rRBT tRBT Random assignment: rRBT Nonresponse tRBT Random assignment: aRBT 2 wks Response Random assignment: eRBT tRBT rRBT Nonresponse

ADHD (Pelham, IES) B. Begin low dose medication 8 weeks Assess- Adequate response? B1. Continue, reassess monthly; randomize if deteriorate B2. Increase dose of medication with monthly changes as needed Random assignment: B3. Add BEMOD treatment with adaptive Modifications based on impairment; medication dose remains stable No A. Begin low-intensity behavior modification 8 weeks Assess- Adequate response? A1. Continue, reassess monthly; randomize if deteriorate A2. Add medication; BEMOD remains stable but medication dose may vary Random assignment: A3. Increase intensity of BEMOD with adaptive modifi- cations based on impairment Yes No Random assignment:

15 Q-Learning is used to constructing proposals for more deeply tailored adaptive treatment strategies Q stands for “Quality of Treatment” Q-Learning is a generalization of regression to multistage treatment

16 Example of Q-Learning output (CATIE) Begin with Olanzapine If non-responder then If preference is to try for efficacy improvement then If PANSS > 94 then switch to Clozapine Else switch to either Quetiapine or Risperidone If preference is to try for tolerable med. then If Olanzapine was not tolerable then switch to Risperidone If Olanzapine was not efficacious then switch to Quetiapine PANSS: Positive and Negative Syndrome Scale

17 Acknowledgements: This presentation is based on work with MCAT members as well as many individuals including Linda Collins, Dave Oslin, Joelle Pineau, John Rush and Scott Stroup. address: Slides with notes at: Click on seminars > health science seminars

18 Why use an Adaptive Treatment Strategy? –High heterogeneity in response to any one intervention What works for one person may not work for another What works now for a person may not work later –Improvement often marred by relapse Remitted or few current symptoms is not the same as cured. –Co-occurring disorders/adherence problems are common