Adaptive Treatment Strategies
S.A. MurphyCCNIA Proposal Meeting
2008
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Outline
• What are Adaptive Treatment Strategies?• What are SMART trials?• SMART Designing Principles and
Analysis
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Adaptive Treatment Strategies are individually tailored sequences of treatments, with treatment type and dosage adapted to the patient.
•Generalization from a one-time decision to a sequence of decisions concerning treatment
•Operationalize clinical practice.
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Why use an Adaptive Treatment Strategy?
– High heterogeneity in response to any one treatment
• 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 is not the same as cured.
– Co-occurring disorders/adherence problems are common
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Example of an Adaptive Treatment Strategy
Treatment of alcohol dependence. Goal is to achieve and maintain remission.
Provide Naltrexone for up to 8 weeks.
If the patient experiences 2 heavy drinking days prior to the end of the 8 weeks, then switch the patient to CBI.
If the patient makes the 8 weeks with at most 1 heavy drinking day, then maintain Naltrexone and add TDM.
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What are Sequential Multiple Assignment Randomized Trials?
• Pinpoint a small number of critical decisions per patient to investigate.
• A randomization takes place at each critical decision (multiple randomizations for each patient).
•Goal is to inform the construction of an adaptive treatment strategy.
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Remitter/Non-Remitter Trial
Stage 1 Intermediate Stage 2 Final Decision Outcome Decision Outcome
NTX Response
R NTX + TDM
NTXCBI
Non-response RNTX +CBI
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From a Remitter/Non-Remitter Trial to a SMART
Stage 1 Intermediate Stage 2 Final Decision Outcome Decision Outcome
NTX + TDM Response R
NTXNTX +Early NTX + CBI
Non-response RCBI
RNTX + CBI
Non-response RCBI
NTX + Late NTX + TDM
RResponse NTX
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SMART Designing Principles
•KEEP IT SIMPLE: At each stage, restrict class of treatments only by ethical, feasibility or strong scientific considerations. Use a summary (responder status) instead of all intermediate outcomes (time until nonresponse, adherence, burden, stress level, etc.) to restrict class of next treatments.
•Collect intermediate outcomes that might be useful in ascertaining for whom each treatment works best; information that might enter into the adaptive treatment strategy.
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SMART Designing Principles
•Choose primary hypotheses that are both scientifically important and aid in developing the adaptive treatment strategy.
•Power trial to address these hypotheses.
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SMART Designing Principles:Primary Hypothesis
•EXAMPLE 1: (sample size is highly constrained): Hypothesize that the initial decision, NTX with early trigger for non-response to lower levels of symptoms over entire study than the initial decision, NTX with a late trigger for non-response (controlling for subsequent treatments via experimental design).
•EXAMPLE 2: (sample size is less constrained): Hypothesize that non-responders will experience fewer symptoms if provided NTX + CBI as opposed to only NTX. (embedded non-responder trial).
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Ex. 1: Two-Group ComparisonStage 1 Intermediate Stage 2 Final Decision Outcome Decision Outcome
NTX + TDM Response R
NTXNTX +Early NTX +CBI
Non-response RCBI
RNTX + CBI
Non-response RCBI
NTX + Late NTX + TDM
RResponse NTX
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Ex. 2: Two-Group ComparisonStage 1 Intermediate Stage 2 Final Decision Outcome Decision Outcome
NTX + TDM Response R
NTXNTX +Early NTX +CBI
Non-response RCBI
RNTX + CBI
Non-response RCBI
NTX + Late NTX + TDM
RResponse NTX
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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 to NTX will do better on NTX + CBI as opposed to CBI only.
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Regression using stage 1 non-adherence as a moderator
Stage 1 Intermediate Stage 2 Final Decision Outcome Decision Outcome
NTX + TDM Response R
NTXNTX +Early NTX +CBI
Non-response RCBI
RNTX + CBI
Non-response RCBI
NTX + Late NTX + TDM
RResponse NTX
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Discussion
• Secondary analyses can use patient characteristics/outcomes to provide evidence for a more sophisticated adaptive treatment strategy.
• SMART studies and analyses targeted at scientific goal of informing the construction of a high quality adaptive treatment strategy
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Acknowledgements: This presentation is based on work with many individuals including Linda Collins, Kevin Lynch, Jim McKay, David Oslin, and Tom Ten Have.
Email address: [email protected]
Slides with notes at:
http://www.stat.lsa.umich.edu/~samurphy/
Click on seminars > health science seminars
Extra slides follow
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Oslin ExTENd
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
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Adaptive Treatment for ADHD
• Ongoing study at the State U. of NY at Buffalo (B. Pelham)
• Goal is to learn how best to help children with ADHD improve functioning at home and school.
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ADHD Study
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 behavioral
treatment; medication dose remains stable but intensity
of bemod may increase with adaptive modifications
based on impairment
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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Studies under review
• H. Jones study of drug-addicted pregnant women (goal is to reduce cocaine/heroin use during pregnancy and thereby improve neonatal outcomes)
• J. Sacks study of parolees with substance abuse disorders (goal is reduce recidivism and substance use)
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Jones’ Study for Drug-Addicted Pregnant Women
rRBT
2 wks Response
rRBT
tRBTRandom
assignment:
rRBT
Nonresponse
tRBT
Randomassignment:
Randomassignment:
Randomassignment:
aRBT
2 wks Response
Randomassignment:
eRBT
tRBT
tRBT
rRBT
Nonresponse
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Sack’s Study of Adaptive Transitional Case Management
Standard Services
Standard TCM
Randomassignment:
Randomassignment:
4 wks Response
Standard TCM
Augmented TCM
Standard TCM
Nonresponse
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Example 2: Classical Continuation Trial
Subjects who have responded are randomized to one of three groups:
1) Continue on lower intensity version of treatment for 24 additional weeks as long as there is no relapse
2) Continue on lower intensity version of treatment for 12 additional weeks as long as there is no relapse
3) No treatment as long as there is no relapse
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Example 2: Continuation TrialStage 1 12 Wk Stage 2 FollowupDecision Outcome Decision Outcome
Med Continued R Response Monitor
Med
Relapse Transfer
Response to R Med+CBT
Relapse Transfer
Monitor
Continued Response Monitor
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Example 2: Continuation to SMART Initial 12 Wk Second Followup Decision Outcome Decision Outcome
Med Continued R Response Monitor
Med
Relapse Med +CBT
Response to R Med+CBT Med
Relapse RCBT
Monitor
Continued Response Monitor
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The Big Questions
•What is the best sequencing of treatments?
•What is the best timing of alterations in treatments?
•What information do we use to make these decisions?
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Classical Non-Remitter Trial
Patients who have not remitted following an adequate course of an SSRI are randomized to one of two groups:
1) Augment with Med C
OR
1) Switch to Med D
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Remitter/Non-Remitter Trial
Stage 1 Intermediate Stage 2 Final Decision Outcome Decision Outcome
WebDM Remission
R Monitor
SSRIAugment w C
No Remission RSwitch to D
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From a Remitter/Non-Remitter Trial to a SMART
Stage 1 Intermediate Stage 2 Final Decision Outcome Decision Outcome
WebDM Remission
SSRI
Augment w C No Remission R
Switch to D
RAugment w C
No Remission RSwitch to D
SSRI +WebCBT WebDM
Remission
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From a Remitter/Non-Remitter Trial to a SMART
Stage 1 Intermediate Stage 2 Final Decision Outcome Decision Outcome
WebDM Remission R
Monitor SSRI
Augment w C No Remission R
Switch to D
RAugment w C
No Remission RSwitch to D
SSRI +WebCBT WebDM
RRemission Monitor
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SMART Designing Principles:Primary Hypothesis
•EXAMPLE 1: (sample size is highly constrained): Hypothesize that the initial treatment SSRI + WebCBT leads to lower levels of symptoms over entire study than the initial treatment, SSRI alone (controlling for subsequent treatments via experimental design).
•EXAMPLE 2: (sample size is less constrained): Hypothesize that subjects who do not remit at the first stage of treatment will exhibit higher remission rates if provided a switch to med D as opposed to augmenting by med C. (embedded non-remitter trial).
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Ex. 1: Two-Group ComparisonStage 1 Intermediate Stage 2 Final Decision Outcome Decision Outcome
WebDM Remission R
Monitor SSRI
Augment w C No Remission R
Switch to D
RAugment w C
No Remission RSwitch to D
SSRI +WebCBT WebDM
RRemission Monitor
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Ex. 2: Two-Group ComparisonStage 1 Intermediate Stage 2 Final Decision Outcome Decision Outcome
WebDM Remission R
Monitor SSRI
Augment w C No Remission R
Switch to D
RAugment w C
No Remission RSwitch to D
SSRI +WebCBT WebDM
RRemission Monitor
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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 patients who have experienced less than a 50% improvement in response in the first stage will be more likely to remit if they receive a switch to Med D as opposed to augmentation by Med C.
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Regression using Response Level during Stage 1
Stage 1 Intermediate Stage 2 Final Decision Outcome Decision Outcome
WebDM Remission R
Monitor SSRI
Augment w C No Remission R
Switch to D
RAugment w C
No Remission RSwitch to D
SSRI +WebCBT WebDM
RRemission Monitor