1. 1 SMART Designs for Developing Adaptive Treatment Strategies S.A. Murphy K. Lynch, J. McKay, D. Oslin & T.Ten Have UMichSpline February, 2006

2. 2 Setting: Management of chronic, relapsing disorders such as drug dependence and mental illness Characteristics: May need a sequence of treatments prior to improvement 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

3. 3 More is not always better! Treatment incurs side effects and substantial burden, particularly over longer time periods. Problems with adherence: 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) These characteristics motivate adaptive, sequential decision making.

4. 4 Adaptive Treatment Strategies are individually tailored treatments, with treatment type and dosage changing with patient need. Mimic Clinical Practice. Brooner et al. (2002) 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

5. 5 Example of an Adaptive Treatment Strategy Treatment of alcohol dependence. Goal is to reduce drinking. Following graduation from the intensive outpatient program the patient is prescribed naltrexone. The patient is monitored weekly over the next two months. If the patient experiences 2 or more heavy drinking days during this period and is nonadherent then the patient’s medication is augmented by CBI. If the patient experiences 2 or more heavy drinking days during this period and is adherent then the patient’s medication is switched to acamprosate. If the patient is able to make the entire 2 months with 1 or no heavy drinking days then the patient is continued on naltrexone and is provided telephone disease management.

6. 6 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?

7. 7 Sequential Multiple Assignment Randomized Trial Conceptually a randomization takes place at each critical decision point. Multiple randomizations per subject. Goal is to inform the construction of an adaptive treatment strategy.

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9. 9 Why a SMART design? Why choosing the best initial treatment on the basis of a randomized trial of initial treatments and choosing the best secondary treatment on the basis of a randomized trial of secondary treatments is not the best way to construct an adaptive treatment strategy.

10. 10 Cohort Effects 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.

11. 11 Delayed Effects Negative synergies: An initial treatment may produce a higher proportion of responders but also produce side effects that reduce the effectiveness of subsequent treatments for those that do not respond. Or the burden imposed by this initial treatment may be sufficiently high so that nonresponders are less likely to adhere to subsequent treatments.

12. 12 Delayed Effects Positive synergies: A treatment may not appear best initially but may have enhanced long term effectiveness when followed by a particular maintenance treatment. Or the initial treatment may lay the foundation for an enhanced effect of subsequent treatments.

13. 13 Summary: When evaluating and comparing initial treatments we need to take into account the effects of the secondary treatments thus SMART

14. 14 An Alternate Approach to SMART Why not use theory, clinical experience and expert opinion to construct the adaptive treatment strategy and then compare this regime against an appropriate alternative in a confirmatory randomized trial? The alternative may be the same strategy but with one component altered.

15. 15 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.

16. 16 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

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18. 18 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 Thall et al. (2000) Treatment of Prostate Cancer Oslin (on-going) Treatment of Alcohol Dependence

19. 19 SMART Designing Principles

20. 20 SMART Designing Principles KEEP IT SIMPLE: At each critical decision point, 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 treatments. Collect intermediate outcomes that might be useful in ascertaining for whom each treatment works best; information that might be used by the adaptive treatment strategy.

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22. 22 SMART Designing Principles Choose primary hypotheses that are both scientifically important and aid in developing the dynamic treatment regime. Power trial to address these hypotheses. Choose secondary hypotheses that further develop the dynamic treatment regime and use the randomization to eliminate confounding. Trial is not necessarily powered to address these hypotheses.

23. 23 SMART Designing Principles: Primary Hypothesis EXAMPLE 1: (sample size is highly constrained): Hypothesize that given the secondary treatments provided, the initial treatment Med A + psychosocial counseling leads to lower drinking than the initial treatment Med A alone. EXAMPLE 2: (sample size is less constrained): Hypothesize that a particular adaptive treatment strategy beginning with Med A+ psychosocial counseling results in lower drinking than a particular adaptive treatment strategy beginning with Med A.

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26. 26 An analysis that is less useful in the development of adaptive treatment strategies: Decide whether med A is better than med A + psychosocial counseling by comparing intermediate outcomes (proportion of immediate responders).

27. 27 SMART Designing Principles Choose secondary hypotheses that further develop the adaptive treatment strategy and use the randomization to preserve the validity of the comparisons. EXAMPLE: Hypothesize that non-adhering non- responders will have lower drinking if provided a change in medication + EM+ counseling as compared to a change in medication only.

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29. 29 How might this work out? 1.Use sample size so as to power the primary analysis with type I error of.1 and power of.9. 2.In the primary analysis calculate the mean drinking score for each adaptive treatment strategies (4 with initial treatment A; 4 with initial treatment A+ psychosocial counseling. Compare best treatment strategy beginning with treatment A with best treatment strategy beginning with A + psychosocial counseling. 3.Suppose best treatment strategy beginning with A + psychosocial counseling produces approximately the same mean drinking score as the best treatment strategy beginning with A alone.

30. 30 How might this work out? 1.In secondary analyses, we find that the intermediate outcome “adherence during initial treatment” differentiates between nonresponders who are assigned med B versus EM + med B+ psychosocial counseling. 2.In secondary analyses, we see no difference between secondary treatments for responders. Recall study not powered for these secondary analyses.

31. 31 How might this work out? In second developmental trial, provide treatment A to all patients. If responder, randomly assign TDM alone versus TDM + telephone counseling. If nonresponder, randomly assign med B versus EM+med B+ psychosocial counseling versus EM +med B. Power second trial for both of these analyses.

32. 32 How might this work out? We see no difference in drinking scores between secondary treatments for responders. We confirm the interaction: nonresponding-nonadherers benefit more from EM + med B than med B alone whereas nonresponding-adherers benefit the same amount from EM+ med B as from med B. A comparison of EM+ med B versus EM + med B + psychosocial indicates no benefit of psychosocial counseling above and beyond EM+ med B.

33. 33 How might this work out? Confirmatory trial comparing two groups. 1)Treatment Strategy: Assign med A initially. If responder provide TDM; if nonresponder- nonadherer assign EM+med B; if nonresponder- adherer assign med B. Versus 2) Standard Care.

34. 34 Discussion Secondary analyses can use pretreatment variables and patient outcomes during treatment to provide evidence for which subsequent treatment is best in an adaptive treatment strategy. (when and for whom?) SMART design and analyses targeted at scientific goal of informing the construction of a high quality adaptive treatment strategy Adherence is not a nuisance; adherence indicates need to tailor treatment.

35. 35 This seminar can be found at: http://www.stat.lsa.umich.edu/~samurphy/ seminars/UMSpline0206.ppt This seminar is based on a paper with Kevin Lynch, Jim McKay, David Oslin and Tom Ten Have. Email me with questions or if you would like a copy: samurphy@umich.edu