Methodology for Adaptive Treatment Strategies

R21 DA019800

S.A. MurphyFor MCATSOct. 8, 2009

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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 2004 - August 2006

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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

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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

non-responsiveAs-needed court hearings As-needed court hearings

low risk + standard counseling + ICM

non-compliant non-complianthigh risk

non-responsiveBi-weekly court hearings Bi-weekly court hearings + standard counseling + ICM

non-compliant Court-determined disposition

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?)

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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 forNonresponse

8 wks Response

TDM + Naltrexone

CBIRandom

assignment:

CBI +Naltrexone

Nonresponse

Early Trigger for Nonresponse

Randomassignment:

Randomassignment:

Randomassignment:

Naltrexone

8 wks Response

Randomassignment:

CBI +Naltrexone

CBI

TDM + Naltrexone

Naltrexone

Nonresponse

Does improving adherence help?

Late Trigger forNonresponse

8 wks Response

TDM + Naltrexone

CBIRandom

assignment:

CBI +Naltrexone

Nonresponse

Early Trigger for Nonresponse

Randomassignment:

Randomassignment:

Randomassignment:

Naltrexone

8 wks Response

Randomassignment:

CBI +Naltrexone

CBI

TDM + Naltrexone

Naltrexone

Nonresponse

Least Intensive vs Most Intensive

Late Trigger forNonresponse

8 wks Response

TDM + Naltrexone

CBIRandom

assignment:

CBI +Naltrexone

Nonresponse

Early Trigger for Nonresponse

Randomassignment:

Randomassignment:

Randomassignment:

Naltrexone

8 wks Response

Randomassignment:

CBI +Naltrexone

CBI

TDM + Naltrexone

Naltrexone

Nonresponse

Drug-Addicted Pregnant Women (Jones; NIDA)

rRBT

2 wks Response

rRBT

tRBTRandom

assignment:

rRBT

Nonresponse

tRBT

Randomassignment:

Randomassignment:

Randomassignment:

aRBT

2 wks Response

Randomassignment:

eRBT

tRBT

tRBT

rRBT

Nonresponse

ADHD (Pelham, IES)

B. Begin low dosemedication

8 weeks

Assess-Adequate response?

B1. Continue, reassess monthly; randomize if deteriorate

B2. Increase dose of medication with monthly changes

as neededRandom

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 butmedication dose may vary

Randomassignment:

A3. Increase intensity of BEMOD with adaptive modifi-

cations based on impairment

Yes

No

Randomassignment:

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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

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Example of Q-Learning output (CATIE)

Begin with OlanzapineIf non-responder then

If preference is to try for efficacy improvement thenIf PANSS > 94 then switch to ClozapineElse switch to either Quetiapine or Risperidone

If preference is to try for tolerable med. thenIf Olanzapine was not tolerable then switch to RisperidoneIf Olanzapine was not efficacious then switch to Quetiapine

PANSS: Positive and Negative Syndrome Scale

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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.

Email address: samurphy@umich.edu

Slides with notes at:

http://www.stat.lsa.umich.edu/~samurphy/

Click on seminars > health science seminars

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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