adaptive treatment design and analysis

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Adaptive Treatment Design and Analysis S.A. Murphy TRC, UPenn April, 2007

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Adaptive Treatment Design and Analysis. S.A. Murphy TRC, UPenn April, 2007. Collaborations with: L. Collins K. Lynch J. McKay D. Oslin J. Pineau A. J. Rush T. Ten Have Discussions with D. Marlowe. Outline. Why Adaptive Treatment Strategies? Why SMART experimental designs? - PowerPoint PPT Presentation

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Page 1: Adaptive Treatment Design and Analysis

Adaptive Treatment Design and Analysis

S.A. Murphy

TRC, UPenn

April, 2007

Page 2: Adaptive Treatment Design and Analysis

• Collaborations with:– L. Collins – K. Lynch– J. McKay– D. Oslin– J. Pineau – A. J. Rush – T. Ten Have

• Discussions with – D. Marlowe

Page 3: Adaptive Treatment Design and Analysis

Outline

• Why Adaptive Treatment Strategies?

• Why SMART experimental designs?

• SMART Design Considerations

• SMART Example Designs

• Discussion

Page 4: Adaptive Treatment Design and Analysis

Adaptive Treatment Strategies are individually tailored treatments, with treatment type and dosage adapted to patient outcomes/characteristics. Operationalize clinical practice.

•Brooner et al. (2002, 2006) 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

Page 5: Adaptive Treatment Design and Analysis

Why Adaptive Treatment Strategies?

• In Treatment– 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– Intervals during which more intense treatment

is required alternate with intervals in which less treatment is sufficient

– Co-occurring disorders may be common

Page 6: Adaptive Treatment Design and Analysis

Why not combine all possible efficacious therapies and provide all of these to patient now and in the future?

•Treatment incurs side effects and substantial burden, particularly over longer time periods. •Adherence is problematic:

•Variations of treatment or different delivery mechanisms may increase adherence•Excessive treatment may lead to non-adherence

•Treatment is costly (Would like to devote additional resources to patients with more severe problems)

More is not always better!

Page 7: Adaptive Treatment Design and Analysis

Example of an Adaptive Treatment Strategy

Drug Court Program for drug abusing offenders. Goal is to minimize recidivism and drug use.

High risk offenders are provided biweekly court hearings; low risk offenders are provided “as-needed court hearings.” In either case the offender is provided standard drug counseling. If the offender becomes non-responsive then intensive case management along with assessment and referral for adjunctive services is provided. If the offender becomes noncompliant during the program, the offender is subject to a court determined disposition.

Page 8: Adaptive Treatment Design and Analysis

Hypothetical Adaptive Drug Court Program

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

low risk + standard counseling + ICM

high risk

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

non-responsive

Page 9: Adaptive Treatment Design and Analysis

The Big Questions

•What is the best sequencing of treatments?

•What is the best timings of alterations in treatments?

•What information do we use to make these decisions? (how do we customize the sequence of treatments?)

Page 10: Adaptive Treatment Design and Analysis

Why SMART Trials?

What is a sequential multiple assignment randomized trial (SMART)?

These are multi-stage trials; each stage corresponds to a critical decision and conceptually a randomization takes place at each critical decision.

Goal is to inform the construction of an adaptive treatment strategy.

Page 11: Adaptive Treatment Design and Analysis

Sequential Multiple Assignment Randomization

Initial Txt Intermediate Outcome Secondary Txt

Relapse

Responder R Prevention

Low-levelMonitoring

Switch toTx C

Tx A

Nonresponder RAugment withTx D

R

Responder Relapse

R Prevention

Low-levelMonitoring

Tx B

Switch toTx C

Nonresponder R

Augment withTx D

Page 12: Adaptive Treatment Design and Analysis

First Alternate Approach

• Why not use data from multiple trials to construct the adaptive treatment strategy?

• Choose the best initial treatment on the basis of a randomized trial of initial treatments and choose the best secondary treatment on the basis of a randomized trial of secondary treatments.

Page 13: Adaptive Treatment Design and Analysis

Delayed Therapeutic Effects

Why not use data from multiple trials to construct the adaptive treatment strategy?

Positive synergies: Treatment A may not appear best initially but may have enhanced long term effectiveness when followed by a particular maintenance treatment. Treatment A may lay the foundation for an enhanced effect of particular subsequent treatments.

Page 14: Adaptive Treatment Design and Analysis

Delayed Therapeutic Effects

Why not use data from multiple trials to construct the adaptive treatment strategy?

Negative synergies: Treatment A may produce a higher proportion of responders but also result in side effects that reduce the variety of subsequent treatments for those that do not respond. Or the burden imposed by treatment A may be sufficiently high so that nonresponders are less likely to adhere to subsequent treatments.

Page 15: Adaptive Treatment Design and Analysis

Diagnostic Effects

Why not use data from multiple trials to construct the adaptive treatment strategy?

Treatment A may not produce as high a proportion of responders as treatment B but treatment A may elicit symptoms that allow you to better match the subsequent treatment to the patient and thus achieve improved response to the sequence of treatments as compared to initial treatment B.

Page 16: Adaptive Treatment Design and Analysis

Cohort Effects

Why not use data from multiple trials to construct the adaptive treatment strategy?

Subjects who will enroll in, who remain in or who are adherent in the trial of the initial treatments may be quite different from the subjects in SMART.

Page 17: Adaptive Treatment Design and Analysis

Summary:

•When evaluating and comparing initial treatments, in a sequence of treatments, we need to take into account the effects of the secondary treatments thus SMART

•Standard randomized trials may yield information about different populations from SMART trials.

Page 18: Adaptive Treatment Design and Analysis

Second Alternate Approach to SMART

Why not use theory, clinical experience and expert opinion to construct the adaptive treatment strategy and then compare this strategy against an appropriate alternative in a confirmatory randomized trial?

The alternative may be the same strategy but with one component altered.

Page 19: Adaptive Treatment Design and Analysis

Problems with the two group trials (or repeated cycles of randomized two group trials)

•Adaptive treatment strategies are multi-component treatments:

•When to start treatment?, when to alter treatment?, which treatment is best next?, what information to use to make each of the above decisions?

•We are not opening the black box— we don’t know why we get or do not get significance and

•Heavy reliance on expert opinion or best guesses --to choose not only the components but the level of these components and when to use

Page 20: Adaptive Treatment Design and Analysis

Problems with the two group comparison (or repeated cycles of randomized two group trials)

•Results may not replicate well --miss interactions,

•Takes a long time to “optimize” the multi-component treatment --method depends on no interactions and

•Some components are costly --retain costly, inactive components

Page 21: Adaptive Treatment Design and Analysis

Sequential Multiple Assignment Randomization

Initial Txt Intermediate Outcome Secondary Txt

Relapse

Responder R Prevention

Low-levelMonitoring

Switch toTx C

Tx A

Nonresponder RAugment withTx D

R

Responder Relapse

R Prevention

Low-levelMonitoring

Tx B

Switch toTx C

Nonresponder R

Augment withTx D

Page 22: Adaptive Treatment Design and Analysis

Examples of “SMART” designs:•CATIE (2001) Treatment of Psychosis in Alzheimer’s Patients

•CATIE (2001) Treatment of Psychosis in Schizophrenia

•STAR*D (2003) Treatment of Depression

•Pelham (on-going) Treatment of ADHD

•Oslin (on-going) Treatment of Alcohol Dependence

Page 23: Adaptive Treatment Design and Analysis

SMART Design

Page 24: Adaptive Treatment Design and Analysis

SMART Design•KEEP IT SIMPLE: At each stage, restrict class of treatments only by ethical, feasibility or strong scientific considerations. Use a low dimension 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.

Page 25: Adaptive Treatment Design and Analysis

SMART Design

•Choose primary hypotheses that are both scientifically important and aid in developing the adaptive treatment strategy.

•Power trial to address these hypotheses.

•Choose secondary hypotheses that further develop the adaptive treatment strategy and use the randomization to eliminate confounding.

•Trial is not necessarily powered to address these hypotheses.

Page 26: Adaptive Treatment Design and Analysis

SMART Design:Primary Hypothesis

•EXAMPLE 1: (sample size is highly constrained): Hypothesize that given the secondary treatments provided, the initial treatment A results in lower symptoms than the initial treatment B.

•EXAMPLE 2: (sample size is less constrained): Hypothesize that among non-responders a switch to treatment C results in lower symptoms than an augment with treatment D.

Page 27: Adaptive Treatment Design and Analysis

EXAMPLE 1

Initial Txt Intermediate Outcome Secondary Txt

Relapse

Responder Prevention

Low-levelMonitoring

Switch toTx C

Tx A

Nonresponder Augment withTx D

Responder Relapse

Prevention

Low-levelMonitoring

Tx B

Switch toTx C

Nonresponder

Augment withTx D

Page 28: Adaptive Treatment Design and Analysis

EXAMPLE 2

Initial Txt Intermediate Outcome Secondary Txt

Relapse

Responder Prevention

Low-levelMonitoring

Switch toTx C

Tx A

Nonresponder Augment withTx D

Responder Relapse

Prevention

Low-levelMonitoring

Tx B

Switch toTx C

Nonresponder

Augment withTx D

Page 29: Adaptive Treatment Design and Analysis

An analysis that is less useful in the development of adaptive treatment

strategies:

Decide whether treatment A is better than treatment B by comparing intermediate outcomes (proportion of immediate responders).

Page 30: Adaptive Treatment Design and Analysis

SMART Design:Sample Size Formula

•EXAMPLE 1: (sample size is highly constrained): Hypothesize that given the secondary treatments provided, the initial treatment A results in lower symptoms than the initial treatment B. Sample size formula is same as for a two group comparison.

•EXAMPLE 2: (sample size is less constrained): Hypothesize that among non-responders a switch to treatment C results in lower symptoms than an augment with treatment D. Sample size formula is same as a two group comparison of non-responders.

Page 31: Adaptive Treatment Design and Analysis

Sample Sizes, Mean ComparisonsN=trial size

Example 1 Example 2

Δμ/σ =.3

Δμ/σ =.5

α = .05, power =1 – β=.85

N = 402 N = 402/initial nonresponse rate

N = 146N = 146/initial nonresponse rate

Page 32: Adaptive Treatment Design and Analysis

SMART Design

•Choose secondary hypotheses that further develop the adaptive treatment strategy and use the randomization to eliminate confounding.

•EXAMPLE: Hypothesize that non-adhering non-responders will exhibit lower symptoms if their treatment is augmented with D as compared to an switch to treatment C (e.g. augment D might include motivational interviewing or behavioral contingencies).

Page 33: Adaptive Treatment Design and Analysis

EXAMPLE 2

Initial Txt Intermediate Outcome Secondary Txt

Relapse

Responder Prevention

Low-levelMonitoring

Switch toTx C

Tx A

Nonresponder Augment withTx D

Responder Relapse

Prevention

Low-levelMonitoring

Tx B

Switch toTx C

Nonresponder

Augment withTx D

Page 34: Adaptive Treatment Design and Analysis

SMART Experimental Protocol

•From the subject’s point of view, he/she is being offered a treatment strategy.

•Obtain consent from subjects for the entire strategy as opposed obtaining consent at each stage separately.

•Try to collect identical research assessments (both in frequency and in type) from subjects regardless of the subject’s responses.

•Same research assessments on early responders and non-responders.

Page 35: Adaptive Treatment Design and Analysis

SMART Example Designs

Page 36: Adaptive Treatment Design and Analysis

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

Page 37: Adaptive Treatment Design and Analysis

Pellman 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:

Page 38: Adaptive Treatment Design and Analysis

Discussion• Secondary analyses can use pretreatment variables and

outcomes to provide evidence for a more sophisticated adaptive treatment strategy. (when and for whom?)

• We are evaluating a sample size formula that specifies the sample size necessary to detect an adaptive treatment strategy that results in a mean outcome δ standard deviations better than the other strategies with 90% probability (J. Levy is collaborator)

• Aside: Non-adherence is an outcome (like side effects) that indicates need to tailor treatment.

Page 39: Adaptive Treatment Design and Analysis

Discussion• Industry should be interested in the SMART

design because:– For some individuals the treatment may require an

adjunctive therapy—when should this therapy be provided and to whom should this therapy be provided?

– Some treatments may be most useful when considered as part of a sequence of treatments (e.g. a treatment may not be effective for all patients but has low side effects/is inexpensive and when it is not effective, patient responses provide an indication of which treatment should be used next.)

Page 40: Adaptive Treatment Design and Analysis

This seminar can be found at:

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

seminars/TRC0407.ppt

Email me with questions or if you would like a copy:

[email protected]