Adaptive Treatment Strategies

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Adaptive Treatment Strategies. S.A. Murphy CCNIA Proposal Meeting 2008. Outline. What are Adaptive Treatment Strategies? What are SMART trials? SMART Designing Principles and Analysis. - PowerPoint PPT Presentation

Transcript of Adaptive Treatment Strategies

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: samurphy@umich.edu

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