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STAR*D: Results and Implications for Clinicians, Researchers, and Policy Makers Bradley N. Gaynes, M.D., M.P.H. Associate Professor of Psychiatry University.

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Presentation on theme: "STAR*D: Results and Implications for Clinicians, Researchers, and Policy Makers Bradley N. Gaynes, M.D., M.P.H. Associate Professor of Psychiatry University."— Presentation transcript:

1 STAR*D: Results and Implications for Clinicians, Researchers, and Policy Makers Bradley N. Gaynes, M.D., M.P.H. Associate Professor of Psychiatry University of North Carolina School of Medicine Chapel Hill, North Carolina AcademyHealth Annual Research Meeting 2007

2 What is STAR*D? Sequenced Treatment Alternatives to Relieve Depression Sequenced Treatment Alternatives to Relieve Depression

3 Overall Aim of STAR*D Define preferred treatments for treatment-resistant depression Define preferred treatments for treatment-resistant depression

4 4 Overview - I Duration: 7 years (October September 2006) Duration: 7 years (October September 2006) Funding: National Institute of Mental Health Funding: National Institute of Mental Health National Coordinating Center, UT Southwestern Medical Center, Dallas National Coordinating Center, UT Southwestern Medical Center, Dallas Data Coordinating Center, Pittsburgh Data Coordinating Center, Pittsburgh

5 Overview - II 14 Regional Centers 14 Regional Centers 41 Clinical Sites 41 Clinical Sites 18 Primary Care Settings (PC) 18 Primary Care Settings (PC) 23 Psychiatric Care Settings (Specialty Care, or SC) 23 Psychiatric Care Settings (Specialty Care, or SC)

6 Obtain Consent CIT Follow-Up Level 2 Satisfactory response Satisfactory response Unsatisfactory response* Unsatisfactory response* *Response = >50% improvement in QIDS-SR from baseline Level 1

7 Level 2 RandomizeRandomize Switch Options Augmentation Options SER BUP-SR VEN-XR CT CIT + BUP-SR CIT + BUS CIT + CT

8 Level 2A RandomizeRandomize Switch Options BUP-SR VEN-XR

9 Level 3 RandomizeRandomize Switch Options Augmentation Options MRT NTP L-2 Tx + Li L-2 Tx + THY

10 Level 4 RandomizeRandomize Switch Options TCP VEN-XR + MRT

11 Participants Major depressive disorder Major depressive disorder Nonpsychotic Nonpsychotic Representative primary and specialty care practices (nonacademic/non efficacy venues) Representative primary and specialty care practices (nonacademic/non efficacy venues) Self-declared patients Self-declared patients

12 Inclusion Criteria Clinician deems antidepressant medication indicated. Clinician deems antidepressant medication indicated years of age years of age. Baseline HRSD Baseline HRSD Most concurrent Axis I, II, III disorders allowed. Most concurrent Axis I, II, III disorders allowed. Suicidal patients allowed Suicidal patients allowed

13 Clinical Procedures Open treatment with randomization Open treatment with randomization Symptoms/side effects measured at each clinical visit (measurement- based care, or MBC) Symptoms/side effects measured at each clinical visit (measurement- based care, or MBC) Clinicians guided by algorithms/ supervision Clinicians guided by algorithms/ supervision

14 Research Innovations Real world patient participants from nonacademic/nonefficacy research venues Real world patient participants from nonacademic/nonefficacy research venues Non-research clinicians Non-research clinicians Identical criteria and concurrent enrollment from PC and SC sites Identical criteria and concurrent enrollment from PC and SC sites Broadly selective inclusion criteria Broadly selective inclusion criteria Patient preference built into study design Patient preference built into study design

15 STAR*D Hybrid Design - I Efficacy*Effectiveness STAR D Patients Symptomatic Volunteers Self-declaredSelf-declared Masked Treatment YesNoNo Masked Raters YesYesYes Baseline Severity HRSD 17 >20 Variable HRSD 17 >14 Diagnostic Method Structured Interview ClinicalClinical Concurrent Axis I and Axis III Allowed MinimalMostMost *To establish efficacy versus placebo. Allowed to enter if MDD requires medication.

16 STAR*D Hybrid Design - II Efficacy*Effectiveness STAR D Treatment Methods ProtocolClinician Protocol + Clinician Symptomatic Outcomes YesSometimesYes Functional Outcomes NoYesYes Cost/Utilization Outcomes NoYesYes Psychotherapy Allowed NoYesSometimes Placebo Allowed YesNoNo Suicidal Patients Allowed NoYesYes *To establish efficacy versus placebo. Allowed if not depression-targeted, empirically tested therapy.

17 Level 1 Findings

18 Patients from real world settings are quite chronically ill Mean (SD) HRSD 17 (ROA) 21.8 (5.2) No. of MDEs 6.0 (11.4) Length of current MDE (months) 24.6 (51.7) Length of illness (years) 15.5 (13.2) No. No. with either chronic or recurrent MDE 85% Depressed 2 years 25% No. with concurrent medical conditions 67%

19 Depressed patients in PC and SC settings are surprisingly similar No difference in No difference in depressive severity depressive severity distribution of depressive severity distribution of depressive severity specific depressive symptom presentation specific depressive symptom presentation likelihood of presenting with a comorbid psychiatric illness likelihood of presenting with a comorbid psychiatric illness Main difference: SC patients more likely to have made prior suicide attempt, but common in both (20% vs. 14%, p<0.0001) Main difference: SC patients more likely to have made prior suicide attempt, but common in both (20% vs. 14%, p<0.0001)

20 Outcomes for PC and SC depressed patients were identical Remission rates were the same (27% PC vs. 28% SC, p=0.40) Remission rates were the same (27% PC vs. 28% SC, p=0.40) Time to remission did not differ by site (6.7 weeks PC vs. 7.3 weeks CS, p=0.11) Time to remission did not differ by site (6.7 weeks PC vs. 7.3 weeks CS, p=0.11) Gaynes et al., BMJ, under review

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22 Conclusions One-quarter of patients have been depressed for >2 years and 2/3 have concurrent GMCs One-quarter of patients have been depressed for >2 years and 2/3 have concurrent GMCs About 1/3 will remit About 1/3 will remit Response occurs in 1/3 AFTER 6 weeks Response occurs in 1/3 AFTER 6 weeks MBC is feasible and works, with equivalent outcomes in PC or SC settings MBC is feasible and works, with equivalent outcomes in PC or SC settings Studies of remission require longer study periods than 8 weeks Studies of remission require longer study periods than 8 weeks

23 Level 2 Medication Switch

24 Conclusions: Level 2 Switch Either switching to the same class of antidepressant (SSRI to SSRI) or to a different class (SSRI to non-SSRI) did not matter Either switching to the same class of antidepressant (SSRI to SSRI) or to a different class (SSRI to non-SSRI) did not matter Substantial differences in pharmacology did not translate into substantial clinical differences in efficacy Substantial differences in pharmacology did not translate into substantial clinical differences in efficacy

25 Level 2 Medication Augmentation

26 Conclusions: Level 2 Augmentation There was no substantial differences in the likelihood of either of the two augmentation medications to produce remission There was no substantial differences in the likelihood of either of the two augmentation medications to produce remission

27 Patients had clear preferences about accepting augmentation vs. switching, and, accordingly, the groups differed at entry into level 2 Patients had clear preferences about accepting augmentation vs. switching, and, accordingly, the groups differed at entry into level 2 Consequently, whether switching vs. augmenting is preferred after one treatment failure could not be addressed Consequently, whether switching vs. augmenting is preferred after one treatment failure could not be addressed

28 QIDS-SR 16 Remission Rates * Theoretical

29 Conclusions Cumulative remission rate is over 50% with first 2 steps Cumulative remission rate is over 50% with first 2 steps Patient preference plays a big role in strategy selection Patient preference plays a big role in strategy selection Pharmacological distinctions do not translate into large clinical differences Pharmacological distinctions do not translate into large clinical differences

30 Level 2 Cognitive Therapy Findings

31 Conclusions CT is an acceptable switch option in the second step CT is an acceptable switch option in the second step CT is an acceptable augmentation option in the second step CT is an acceptable augmentation option in the second step Whether CT responders/remitters fare better in follow-up is in analysis Whether CT responders/remitters fare better in follow-up is in analysis CT was not as popular as expected CT was not as popular as expected

32 Remission Rates by Levels a a By QIDS-SR 16 <5 at level exit Level 1 (2876)32.9 Level 2 (1439) Switch (789) Augment (650) Level 3 (377) Switch (235) Augment (142) Level 4 (109)14.7

33 Are Efficacy and Real World Patients Different?

34 STAR*D Participant Flow (CONSORT Chart) Screened (4,790) Not offered Consent or Refused to Consent (613) Ineligible (136) Consented (4,177) Efficacy Sample (635) Nonefficacy Sample (2,220) Could Not Be Classified (21) Failed to Return (234) Eligible (4,041) HRSD 17 >14 (3,110) Eligible for Analysis (2,876) HRSD 17 < 14 a (607) Or Missing (324) a Some of these subjects were eligible for entry into Level 2. Wisniewski et al, The Lancet, in preparation

35 Clinical Features a a Descriptive statistics presented as mean±sd and n (%N). Sums do not always equal N due to missing values. Percentages based on available data; b p<.01; c p<.05 Wisniewski et al, The Lancet, in preparation Feature Efficacy (n=635) Nonefficacy (n=2220) Illness duration (yrs.) b 1316 Suicide attempt c 15%19% Anxious features b 47%55% Atypical features b 14%20% Melancholic features 25%23% Psychiatric care b 70%59%

36 Outcomes a - I a Descriptive statistics presented as mean±sd and n (%N). Sums do not always equal N due to missing values. Percentages based on available data QIDS-SR 16 = 16-item Quick Inventory of Depressive Symptomatology – Self-report Wisniewski et al, The Lancet, in preparation Outcome Efficacy (n=635) Nonefficacy (n=2220) QIDS-SR 16 remission 35%25% QIDS-SR 16 response 52%39% Exit QIDS-SR QIDS-SR 16 % change

37 Outcomes a - II a Descriptive statistics presented as mean±sd and n (%N). Sums do not always equal N due to missing values. Percentages based on available data; b Adjusted for regional center, clinical setting, age, race, Hispanic ethnicity, education, employment status, income, medical insurance, marital status, illness duration, suicide attempt, family history of substance abuse, anxious and atypical features; QIDS-SR 16 = 16-item Quick Inventory of Depressive Symptomatology – Self-reportWisniewski et al, The Lancet, in preparation Adjusted Analyses b OutcomeOR (95% CI) P QIDS-SR 16 remission 1.331(1.073,1.651) QIDS-SR 16 response 1.371(1.122,1.675) OutcomeΒ (95% CI) P Exit QIDS-SR (-1.198,-.165) QIDS-SR 16 % change (-7.424,-.129)0.0078

38 Phase III clinical trial criteria do not recruit samples representative of depressed patients who seek treatment in typical clinical practice. Phase III clinical trial criteria do not recruit samples representative of depressed patients who seek treatment in typical clinical practice. The use of broader inclusion criteria The use of broader inclusion criteria would make findings more generalizable to typical care-seeking outpatients would make findings more generalizable to typical care-seeking outpatients may reduce placebo response and remission rates in Phase III trials, and may reduce placebo response and remission rates in Phase III trials, and may reduce the risk of failed trials, at the risk of increasing adverse events and decreasing symptomatic benefit. may reduce the risk of failed trials, at the risk of increasing adverse events and decreasing symptomatic benefit.

39 What is the pay off? By any measure, success By any measure, success Over 4000 patients involved Over 4000 patients involved Over 150 clinicians Over 150 clinicians Active involvement of PC sites Active involvement of PC sites 51 publications to date, and more in press or preparation 51 publications to date, and more in press or preparation At least 3 large scale ancillary studies (Child, Alcohol, Genetics), each of which has its own cadre of publications At least 3 large scale ancillary studies (Child, Alcohol, Genetics), each of which has its own cadre of publications Depression Treatment Network infrastructure, supporting rapid trial turn around Depression Treatment Network infrastructure, supporting rapid trial turn around

40 What questions could not be answered? How does high quality measurement- based care compare to usual care? How does high quality measurement- based care compare to usual care? Is switching or augmentation the preferred strategy after 1 or 2 failures? Is switching or augmentation the preferred strategy after 1 or 2 failures? What is the role of cognitive therapy? What is the role of cognitive therapy?

41 What important questions does STAR*D raise? Clinical Clinical Given chronicity and low remission rates of most depressions, should combination meds (broad spectrum antidepressants) be started at initial treatment step? Given chronicity and low remission rates of most depressions, should combination meds (broad spectrum antidepressants) be started at initial treatment step? How do you balance the effort at adequately treating those identified with identifying those undetected? Could system keep up? How do you balance the effort at adequately treating those identified with identifying those undetected? Could system keep up? Study Design Study Design How best do you handle the role of patient preference in study design? How best do you handle the role of patient preference in study design?

42 Policy Policy Why not include more broadly representative patients in placebo-controlled trials used to develop treatments? Why not include more broadly representative patients in placebo-controlled trials used to develop treatments? If you could ensure patient safety and ensure internal validity in such trials, the results would be more directly applicable to our patients, who are less likely to spontaneously improve. If you could ensure patient safety and ensure internal validity in such trials, the results would be more directly applicable to our patients, who are less likely to spontaneously improve. What should the arsenal of available antidepressants be at the state level? What should the arsenal of available antidepressants be at the state level? How best do you keep these infrastructures funded? How best do you keep these infrastructures funded?

43 The STAR*D Study Investigators National Coordinating Center A. John Rush, MD Madhukar H. Trivedi, MD Diane Warden, PhD, MBA Melanie M. Biggs, PhD Kathy Shores-Wilson, PhD Diane Stegman, RNC Michael Kashner, PhD, JD Data Coordinating Center Stephen R. Wisniewski, PhD G.K. Balasubramani, PhD James F. Luther, MA Heather Eng, BA. University of Alabama Lori Davis, MD University of California, Los Angeles Andrew Leuchter, MD Ira Lesser, MD Ian Cook, MD Daniel Castro, MD University of California, San Diego Sidney Zisook, MD Ari Albala, MD Timothy Dresselhous, MD Steven Shuchter, MD Terry Schwartz, MD Northwestern University Medical School, Chicago William T. McKinney, MD William S. Gilmer, MD

44 The STAR*D Study Investigators University of Kansas, Wichita and Clinical Research Institute Sheldon H. Preskorn, MD Ahsan Khan, MD Massachusetts General Hospital, Boston Jonathan Alpert, MD Maurizio Fava, MD Andrew A. Nierenberg, MD University of Michigan, Ann Arbor Elizabeth Young, MD Michael Klinkman, MD Sheila Marcus, MD New York State Psychiatric Institute and Columbia College of Physicians and Surgeons, New York Frederic M. Quitkin, MD Patrick J. McGrath, MD Jonathan W. Stewart, MD Harold Sackeim, PhD University of North Carolina, Chapel Hill Robert N. Golden, MD Bradley N. Gaynes, MD

45 The STAR*D Study Investigators Laureate Healthcare System, Tulsa Jeffrey Mitchell, MD William Yates, MD University of Pittsburgh Medical Center, Pittsburgh Michael E. Thase, MD Edward S. Friedman, MD Vanderbilt University Medical Center, Nashville Steven Hollon, PhD Richard Shelton, MD The University of Texas Southwestern Medical Center, Dallas Mustafa M. Husain, MD Michael Downing, MD Diane Stegman, RNC Laurie MacLeod, RN Virginia Commonwealth University, Richmond Susan G. Kornstein, MD Robert K. Schneider, MD

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48 Pharmaceutical Industry Support for STAR*D Medications were provided gratis by Bristol-Myers Squibb Company, Forest Pharmaceuticals Inc., GlaxoSmithKline, King Pharmaceuticals, Organon Inc., Pfizer Inc., and Wyeth-Ayerst Laboratories.


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