Developing Adaptive Treatment Strategies using MOST Experimental Designs

1. Developing Adaptive Treatment Strategies using MOST Experimental Designs S.A. Murphy Univ. of Michigan Dallas: December, 2005

2. Goals • Adaptive Treatment Strategies • Seeds of MOST • MOST: Multiphase Optimization Strategy • Hypothetical Example • Discussion

3. Collaborators • Linda Collins (Health & Human Development at PennState) • Victor Strecher (Cancer Center at Univ. Mich.) • Vijay Nair (Engineering & Statistics at Univ. Mich.)

4. Adaptive Treatment Strategies • Adaptive treatment strategies are individually tailored treatments, with treatment type and dosage changing with subject outcomes. • Adaptive treatment strategies operationalize the sequential clinical decisions that are necessary in managing the chronic forms of addiction and mental disorders • Adaptive treatment strategies are multi-component treatments

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 the patient is provided telephone disease management.

6. Components of an adaptive treatment strategy • Tailoring Variables (which ones and how to measure?) • Decision Options (what are the options at this time?) • Decision Rules (input the tailoring variables and output a decision) one per key decision • An adaptive treatment strategy is a sequence of decision rules that input tailoring variables and output recommended decisions

7. Tailoring Variables: Response (e.g. heavy drinking days), adherence to medication 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 the patient is provided telephone disease management.

8. Decision Options: medication type, CBI, telephone disease management 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 the patient is provided telephone disease management.

9. Some components • What is the best sequencing of treatments? • What is the best timings of alterations in treatments? • What information do we use to make these treatments? • The usual components: medication, counseling, staff training, motivation-to-adhere components, delivery mechanism (telephone, group, individual counseling), monitoring schedule………..

10. Seeds of MOST • In the middle of the last century, R. Fisher (one of the fathers of genetics) and his protégé G. Box confronted problems in which the goal was to construct a multi-component “treatment.” • Each multi-component treatment was very expensive to construct, e.g. “counseling frequency * medication type* adherence program intensity * extra staff training” • “Subjects” were very expensive. • Resources were constrained.

11. Seeds of MOST • Colleagues and other scientists were employing the “one-component-at-a-time” experimental strategy. • Two arm studies in which the new treatment differs from the old treatment on one component. • Much dissatisfaction due to • Results did not replicate well, • Took a long time to “optimize” the multi-component treatment, • Some components were costly and • Heavy reliance on expert opinion or best guesses.

12. Colleagues and other scientists were employing the “one-component-at-a-time” experimental strategy. • Two arm studies in which the new treatment differs from the old treatment on one component. • Much dissatisfaction due to • Results did not replicate well (missed interactions), • Took a long time to “optimize” the multi-component treatment (method depends on no interactions), • Some components were costly (retained costly, inactive components) and • Heavy reliance on expert opinion or best guesses (to choose not only the components but the level of these components)

13. MOST: Multiphase Optimization Strategy • Phase 1 Goal: Figure out which components are active and which interact; are there interactions with patient/clinic characteristics? • Often it is wonderful if a component is inactive. Why? • Phase 2 Goal: Figure out best level of component (best dose/intensity or type?). If an unexpected interaction in phase 1 is detected then seek to confirm this. • Phase 3 Goal: Evaluate your best against current treatment or control. • Collins et al. (2005)

14. MOST • Phase 1 (screening): Figure out which components are active and which interact; are there interactions with patient/clinic characteristics? • Choose two extremal levels of each candidate component • Decide which interactions are most interesting. • Implement a balanced design (a carefully chosen subset of the many possible multi-component treatments) • To test significance of a component compare the two groups corresponding to the two levels of the component.

15. Hypothetical Example • Components: Counseling Dose (high/low dose), Counseling Type (tele-group or group), Adherence program (low/high intensity), Extra Staff Training (for dealing with patient adherence, motivation—yes/no) • Interesting Interactions: Staff Training * Adherence program, Counseling Dose * Adherence program • There are 16 different multi-component treatments (treatment conditions).

16. Balanced Design of 8 Conditions Counseling Counseling Adherence Staff Dose Type Program Training

17. Hypothetical Example • Reduced number of implemented multi-component treatments (16 to 8) (multi-component treatments are expensive to construct and implement yet we want to detect interactions) • To test for significance always compare average response for ½ of the groups with average response for the remaining ½ of the groups (power is related to ½ sample size as in a two arm study) (subjects are expensive)

18. Assessing Activity of Counseling Type: Compare blue versus black Counseling Counseling Adherence Staff Dose Type Program Training

19. Hypothetical Example • Test the significance for sums of interactions. • staff training * adherence program + counseling dose * type • counseling dose * adherence program + staff training * counseling type • counseling type * adherence program + staff training * counseling dose • To test for significance always compare average response for ½ of the groups with average response for the remaining ½ of the groups

20. Hypothetical Example • Suppose we find that • the choice of counseling dose, adherence program and staff training are important • the combination “counseling dose * adherence program + staff training * counseling type” is important • We must ask ourselves: “Should we be concerned about a “staff training * counseling type” interaction? If yes then we should investigate counseling type options in stage 2, otherwise we use whatever counseling type is most convenient. We decide NO.

21. Hypothetical Example • Phase 2 (refining): In this stage we decide whether to consider alternate doses for counseling and/or consider alternate intensities for the adherence program. • We decide to only consider alternate doses for counseling. • Summary: Tele-group counseling with the higher intensity adherence program and extra staff training. Decide on the best dose of counseling.

22. Balanced Design of 4 Conditions Counseling Adherence Counseling Staff Dose Program Type Training

23. Hypothetical Example • Suppose we find that • a counseling dose at the medium level with low intensity adherence program works as well as a counseling dose at the high level with high intensity adherence program. • Most promising multi-component treatment is Counseling Adherence Counseling Staff Dose Program Type Training

24. Hypothetical Example • Most promising multi-component treatment is • Conduct a two arm randomized trial comparing the above multi-component treatment with standard care. Counseling Adherence Counseling Staff Dose Program Type Training

25. Discussion • How can MOST help us construct high quality adaptive treatment strategies? • Help us sort through timing components (should we give up on present treatment after 2 heavy drinking days or should we wait until 5 heavy drinking days?) • Is it worthwhile to consider adherence programs if a person did not respond to initial treatment? • Do some treatments improve the patient’s ability to take advantage of low level relapse monitoring help?

26. Discussion • What are the biggest disadvantages of MOST? • Requires a change in the way clinical scientists think about constructing multi-component treatments • Must intermix experimentation and clinical experience, theory, expert opinion at a deeper level than heretofore. • Requires the translation from completely constructing multi-component treatment (but not discriminating between interactions) to thinking about which interactions are most important • Requires statisticians to be comfortable with the overt use of theory and clinical experience in designing non-confirmatory experiments.

27. Discussion • What are the biggest advantages of MOST? • Most useful in a setting in which resources/time are highly constrained. • The one component-at-a-time trials are ok if you have a resource rich environment. • The utility of several treatment components can be assessed in a single trial. • Efficiently take advantage of interactions • Requires the use of clinical experience, expert opinion, theory in clinical experimentation but provides protection from incorrect opinions.

28. The Collins, Murphy, Nair and Strecher paper with more details can be found at http://www.stat.lsa.umich.edu/~samurphy/papers/ MOST.pdf This seminar can be found at: http://www.stat.lsa.umich.edu/~samurphy/seminars/ My email address: samurphy@umich.edu