Sequenced Treatment Alternatives to Relieve Depression (STAR*D) Stephen Wisniewski, PhD Epidemiology Data Center STAR*D Data Coordinating Center University of Pittsburgh

Outline Overview of STAR*D Overview of STAR*D Introduction to the Equipoise-Stratified Randomized Design Introduction to the Equipoise-Stratified Randomized Design Implementation of the Equipoise Stratified Randomized Design in STAR*D Implementation of the Equipoise Stratified Randomized Design in STAR*D

Overview of STAR*D Organization Organization National Coordinating Center (Department of Psychiatry, University of Texas Southwestern Medical Center) National Coordinating Center (Department of Psychiatry, University of Texas Southwestern Medical Center) Data Coordinating Center (Epidemiology Data Center, University of Pittsburgh) Data Coordinating Center (Epidemiology Data Center, University of Pittsburgh) 14 Regional Centers 14 Regional Centers 2-4 Clinical Sites 2-4 Clinical Sites Primary Care and Specialty (Psychiatry) Primary Care and Specialty (Psychiatry) Goal: Determine the best “next step” treatments for those with treatment resistant depression Goal: Determine the best “next step” treatments for those with treatment resistant depression

*Defined as nonremission Obtain Consent Level 2 Follow-up Satisfactory Response Unsatisfactory Response* CIT Level 1

Randomization Which treatments to test as second-step treatments? Which treatments to test as second-step treatments? Efficacy studies have identified a number of different types of treatments that were effective in treating depression. Efficacy studies have identified a number of different types of treatments that were effective in treating depression. After much discussion, debate, arguing, etc., seven treatments were selected for the Level 2: After much discussion, debate, arguing, etc., seven treatments were selected for the Level 2: Level 2 Treatment Options Venlafaxin Sertraline Bupropion Cognitive Therapy Citalopram + Cognitive Therapy Citalopram + Bupropion Citalopram + Buspirone

Randomize SERBUP-SRVEN-XRCT CIT + BUP-SR CIT + BUS CIT + CT Level 2 Augmentation Options Switch Options

Level 2A Randomize BUP-SR VEN-XR Switch

Level 3 MRTNTP L-2 Tx + Li L-2 Tx + THY SwitchAugmentation Randomize

Level 4 TCP VEN-XR + MRT Randomize Switch

How do we randomly assign a subject to one of the seven treatments in Level 2?

Complete Randomization Patient and clinician must be willing to accept all treatments offered Patient and clinician must be willing to accept all treatments offered Advantage: simple approach Advantage: simple approach Disadvantage: Disadvantage: Subjects and clinicians may have treatment preferences and would not be willing to be randomly assigned to a number of treatments. Subjects and clinicians may have treatment preferences and would not be willing to be randomly assigned to a number of treatments. Because of this, those that are willing to accept all the treatment assignments do not represent a general population Because of this, those that are willing to accept all the treatment assignments do not represent a general population

Clinician’s Choice Define broad classifications and let the clinician choose the treatment within the class. Define broad classifications and let the clinician choose the treatment within the class. Patient and clinician must be willing to accept at least one treatment option within each class Patient and clinician must be willing to accept at least one treatment option within each class Advantages: Advantages: Clinician, in theory, knows something about the patient so the choice of the treatment can be optimized Clinician, in theory, knows something about the patient so the choice of the treatment can be optimized More generalizable More generalizable

Clinician’s Choice Disadvantages: Disadvantages: Because the assignment of treatment options within a class are not randomly assigned, the “best” treatment option within a class cannot be identified Because the assignment of treatment options within a class are not randomly assigned, the “best” treatment option within a class cannot be identified

The Equipoise-Stratified Design Equipoise-Stratified (Lavori et al., 2000) Equipoise-Stratified (Lavori et al., 2000) What is equipoise? What is equipoise? To be in equipoise with respect to a set of prospective treatment options is to regard them as approximately equal in terms of the likelihood of success. To be in equipoise with respect to a set of prospective treatment options is to regard them as approximately equal in terms of the likelihood of success. To consider a patient for entry into a study, the clinician and patient must be in equipoise with respect to the treatment options. To consider a patient for entry into a study, the clinician and patient must be in equipoise with respect to the treatment options.

Example Application of ESRD Conducting a study to compare four treatments (TX1, TX2, TX3, TX4). Conducting a study to compare four treatments (TX1, TX2, TX3, TX4). The treatment options can be combined into two treatment strategies The treatment options can be combined into two treatment strategies Strategy A (TX1, TX2) Strategy A (TX1, TX2) Strategy B (TX3, TX4) Strategy B (TX3, TX4) This would create the following acceptability strata This would create the following acceptability strata

Example Application of ESRD Acceptability of Treatment Options Acceptable Treatment Options Eligible Acceptability Strategy A Strategy B For StratumTX1TX2TX3TX4Study 1YYYYY 2YYYNY 3YYNYY 4YNYYY 5NYYNY 6YYNNY 7YNNYY 8NNYYY

Example Application of ESRD Acceptability of Treatment Options Acceptable Treatment Options Eligible Acceptability Strategy A Strategy B For StratumTX1TX2TX3TX4Study 9YNNYY 10NYNYY 11NYYNY 12NNNYN 13NNYNN 14NYNNN 15YNNNN 16NNNNN

Example Application of ESRD For the equipoise-stratified design, subjects from acceptability strata 1 through 11 are included in the study For the equipoise-stratified design, subjects from acceptability strata 1 through 11 are included in the study For the completely randomized design, only those from acceptability stratum 1 are included in the study For the completely randomized design, only those from acceptability stratum 1 are included in the study For the clinician’s choice design, the comparison of treatments cannot be made. For the clinician’s choice design, the comparison of treatments cannot be made.

Example Application of ESRD Want to do identify best treatment Want to do identify best treatment Conduct all pairwise treatment comparisons Conduct all pairwise treatment comparisons TX1 vs. TX2, TX1 vs. TX3, TX1 vs. TX4, TX2 vs. TX3, TX2 vs. TX4, TX3 vs. TX4 TX1 vs. TX2, TX1 vs. TX3, TX1 vs. TX4, TX2 vs. TX3, TX2 vs. TX4, TX3 vs. TX4 For a given comparison (e.g., TX1 vs. TX2), compare rate out binary outcome across two treatments, stratified by acceptability stratum (Srata 1, 2, 3 and 6). For a given comparison (e.g., TX1 vs. TX2), compare rate out binary outcome across two treatments, stratified by acceptability stratum (Srata 1, 2, 3 and 6). Use Mantel-Haenszel chi-square test to combine comparison across strata. Use Mantel-Haenszel chi-square test to combine comparison across strata.

Example Application of ESRD Because conducting many pairwise tests, need to maintain the Type I error to be.05 Because conducting many pairwise tests, need to maintain the Type I error to be.05 Use Bonferroni corrections, so each pairwise comparison is conducted at the.0083 (.05/6) level. Use Bonferroni corrections, so each pairwise comparison is conducted at the.0083 (.05/6) level.

The Equipoise-Stratified Design Equipoise-Stratified Equipoise-Stratified Advantages Advantages Generalizable Generalizable Pairwise contrast can be built. For example, to compare A to B, can take subjects that selected either the ABC strata or the AB strata, and were randomly assigned to receive either treatment A or B. Pairwise contrast can be built. For example, to compare A to B, can take subjects that selected either the ABC strata or the AB strata, and were randomly assigned to receive either treatment A or B. Disadvantage: Complicated Disadvantage: Complicated

The Equipoise-Stratified Design In the second-step treatments of STAR*D In the second-step treatments of STAR*D Patients/clinicians considered four strategies Patients/clinicians considered four strategies Medication switch Medication switch Medication augment Medication augment Cognitive Therapy switch Cognitive Therapy switch Cognitive Therapy augment Cognitive Therapy augment Could exclude any of these, as long as multiple treatments were still available. Could exclude any of these, as long as multiple treatments were still available. Exclude medication augment, cognitive therapy switch, cognitive therapy augment - OK Exclude medication augment, cognitive therapy switch, cognitive therapy augment - OK Exclude medication switch, medication augment, cognitive therapy switch – not OK Exclude medication switch, medication augment, cognitive therapy switch – not OK

ESRD in STAR*D

Randomize SERBUP-SRVEN-XRCT CIT + BUP-SR CIT + BUS CIT + CT ESRD in STAR*D Study Design: Level 2 Augmentation Options Switch Options

ESRD in STAR*D Level 2 Approach Goal: Identify most effective 2 nd step treatment Goal: Identify most effective 2 nd step treatment Seven treatment options created too many strata Seven treatment options created too many strata Create acceptability stratum pooling strategies Create acceptability stratum pooling strategies Must be willing to accept all medication switches Must be willing to accept all medication switches Must be willing to accept all medication augments Must be willing to accept all medication augments Creates four treatment strategy strata Creates four treatment strategy strata Medication Switch Medication Switch Medication Augment Medication Augment Cognitive Therapy Switch Cognitive Therapy Switch Cognitive Therapy Augment Cognitive Therapy Augment

ESRD in STAR*D Level 2 Approach Analysis approach – step up procedure Analysis approach – step up procedure Identify most effect medication switch Identify most effect medication switch Identify most effect medication augment Identify most effect medication augment Identify most effective treatment strategy Identify most effective treatment strategy If a most effective medication switch or medication augment was identified, use those randomly assigned to that specific medication in the comparison across strategies. If a most effective medication switch or medication augment was identified, use those randomly assigned to that specific medication in the comparison across strategies. If a most effective medication switch or medication augment was not identified, pool those randomly assigned to any treatment that strategy for the comparison across strategies. If a most effective medication switch or medication augment was not identified, pool those randomly assigned to any treatment that strategy for the comparison across strategies.

ESRD in STAR*D : Level 2 Expected Acceptability Acceptability of Treatment Strata Enrolled in Level 2 of STAR*D Med Aug Med Switch CT Aug CT Switch Permitted Expected % Yes 8 NoYes < 1 YesNoYes < 1 Yes NoYes 1 NoYes1 No Yes 11 NoYesNoYes 12 NoYes NoYes0 No Yes 0 NoYesNoYes12 Yes No Yes25 YesNo Yes14 NoYesNo Yes14 No YesNo - YesNo-

ESRD in STAR*D : Level 2 Observed & Expected Acceptability Acceptability of Treatment Strata Enrolled in Level 2 of STAR*D Med Aug Med Switch CT Aug CT Switch Permitted Expected % Observed % Yes 81 NoYes < 1 YesNoYes < 1 Yes NoYes 10 NoYes12 No Yes 113 NoYesNoYes 127 NoYes NoYes0< 1 YesNo Yes 0< 1 YesNoYesNoYes1211 Yes No Yes254 YesNo Yes1430 NoYesNo Yes1441 No YesNo -- YesNo--

ESRD in STAR*D Any treatment: 1.5% (21/1,438 ) Any treatment: 1.5% (21/1,438 ) Cognitive Therapy: 25.6% (368/1,438) Cognitive Therapy: 25.6% (368/1,438) Medication Switch: 55.8% (803/1,438) Medication Switch: 55.8% (803/1,438) Medication Augment: 48.4 (696/1,438) Medication Augment: 48.4 (696/1,438)