Integration Models into Primary Health Care: the Example of Late-life Depression

1. Integration Models into Primary Health Care: the Example of Late-life Depression Benoit H. Mulsant, MD, MS, FRCPC Professor and Vice-Chair Department of Psychiatry University of Toronto Physician in Chief Centre for Addiction and Mental Health

2. Learning Objectives • At the conclusion of this session, the participants should be able to: • Assess the evidence supporting the efficacy of antidepressant medications in the treatment of late-life depression. • Assess the risks of antidepressant medications used in the treatment of late-life depression. • Maximize the effectiveness of pharmacotherapy when treating a patient with late-life depression in the primary care sector.

4. Treating Late-Life DepressionFighting therapeutic nihilism One of the few medical conditions in which treatment can make a rapid and dramatic difference in an elderly patient’s level of function

5. Pinquart, Duberstein, & Lyness Treatments for later-life depressive conditions: a meta-analytic comparison of pharmacotherapy and psychotherapy Am J Psych, 163(9):1493-501, 2006 Meta-analysis of 62 placebo-controlled studies (N = 3,921) Favorable outcomes: Drugs: 66% vs. Placebo: 31% “Available treatments for depression work, with effect sizes that are moderate to large…”

6. Outcome of Usual Care for Depressed Patients Treated by Well-Trained Psychiatrists • Six psychiatric clinics in Westchester County (USA) • 165 patients with major depression • 65% received an antidepressant • 45% received an adequate dose for 4+ weeks (academic vs. non-academic sites: 53% vs. 36%, p =0.04) • Remission rate after 3 months: 30% • Adequate treatment: 3 fold higher likelihood of remission (OR = 3.2; p = 0.04) Meyers et al (2002) Archives Gen Psych

7. Treating Late-Life Depression Closing the Efficacy-Effectiveness Gap • Systematic vs. personalized approach • Selecting a class and a specific agent • Optimal dose • Optimal trial duration • Management of treatment resistance

8. Outline • 1. Argument for a systematic approach (“algorithm”, “clinical pathways”, “stepped care”) vs. an individualized approach (“usual care”) • Defining one’s algorithm for late-life depression: • What is your first-line intervention? • Your second-line intervention? • Your third-line intervention? • How long should each step lasts? • When do you switch? When do you augment?

9. Systematic Approach Based on best evidence or guidelines Clinical experience based on large number of patients Keeping the course: the clinician is protected against personal biases, pressures form the patient or family Focus is on the patient Usual Care Based on fad “du jour” Little cumulative experience due to small numbers of patients receiving many different medications Ill-advised or ill-timed changes in treatment Focus is on the treatment (making decisions is exhausting) A Tale of Two Approaches

10. Systematic Approach (algorithm, stepped care) vs. Individualized Approach (usual care) • Two Examples of Randomized Comparisons for Stepped-Care for Late-Life Depression: • IMPACT (Unutzer et al, JAMA, 2002) • PROSPECT (Bruce et al, JAMA, 2004)

11. PROSPECT: A Case Study Patient & Family Psycho-Education Physician Education Identification of Diagnosis & DEPRESSION SPECIALIST TREATMENT ALGORITHM

12. PROSPECT: Treatment Algorithm

13. Main Features of Treatment Algorithm • Based on evidence and practice guideline • Modified for the primary care office • Use of psychopharmacological and psychosocial interventions • Psychiatric consultation is offered in complex cases • Covers acute and continuation/maintenance treatment • Covers a wide range of syndromes ranging from mild to severe depression

14. PROSPECT Algorithm (1)

15. PROSPECT Algorithm (2)

16. PROSPECT: Results

17. PROSPECT: Cumulative Probability of Remission All comparisons: p < 0.001Alexopoulos et al (2005) Am J Psych

18. PROSPECT: Probability of Being Treated All comparisons: p < 0.001 Alexopoulos et al (2009) Am J Psych

19. Psychoeducation is Essential for Successful Antidepressant Treatment • Address the patient’s personal illness model • It takes 2-6 weeks to show beneficial effects • Side effects occur right away • Patients must be encouraged and supported to be take dose regularly as prescribed • Reassure that side effects usually wear off • Need for continuation and maintenance treatment Mulsant et al (2003) CNS Spectrum; 8: 27-34

20. Response Rates in 13 Studies of Treatment-Resistant Late-Life Depression Cooper et al (2011) Am J Psych; 168: 681-688

22. Outline • 1. Argument for a systematic approach (“algorithm”, “clinical pathways”, “stepped care”) vs. an individualized approach (“usual care”) • Defining one’s algorithm for late-life depression: • What is your first-line intervention? • Your second-line intervention? • Your third-line intervention? • How long should each step lasts? • When do you switch? When do you augment?

23. Possible Criteria for Choosing an Antidepressants for an Older Adult Efficacy Tolerability Safety Cost

24. Response Rates (%) in Eight Published Randomized Placebo-Controlled Trials * * * * 1. Tollefson et al (1995) Int Psychogeriatrics; 7:89–104 – 2. Schneider et al (2003) Am J Psych; 160:1277-85 – 3. Rapaport et al (2003) J Clin Psych; 64:1065–74 –4. Roose et al (2004) Am J Psych; 161:2050-9– 5. Kasper et al (2005) Am J Geri Psych; 13:884-91 – 6. Schatzberg & Roose (2006) Am J Geri Psych; 14:361-70 – 7. Bose et al. (2008) Am J Geri Psych; 16:14-20 – 8. Raskin et al (2007) Am J Psychiatry; 164:900-9

25. Fluoxetine in the treatment of late-life depression Marked site variability in remission rates Small et al (1996) Int J Geri Psych; 11:1089-95

26. Citalopram in the treatment of depression in the very oldMarked site variability in response and remission rates Roose et al (2004) Am J Psych; 161:2050-9

27. Possible Criteria for Choosing an Antidepressants for an Older Adult Efficacy Tolerability Safety Cost

28. Discontinuation Rates (%) Attributed to Adverse Effects in Eight RpCTs * * * * * 1. Tollefson et al (1995) Int Psychogeriatr; 7:89–104 – 2. Schneider et al (2003) Am J Psych; 160:1277-85 – 3. Rapaport et al (2003) J Clin Psych; 64:1065–74 –4. Roose et al (2004) Am J Psych; 161:2050-9– 5. Kasper et al (2005) Am J Geri Psych;13:884-91 – 6. Schatzberg & Roose (2006). Am J Geriatr Psychiatry; 14:361370 - 7. Bose et al. (2008) Am J Geriatr Psychiatry; 16:14-20 – 8. Raskin et al (2007) Am J Psychiatry; 164:900-9

29. Overall Discontinuation Rates (%) in Eight RpCTs * 1. Tollefson et al (1995) Int Psychogeriatr; 7:89–104 – 2. Schneider et al (2003) Am J Psych; 160:1277-85 – 3. Rapaport et al (2003) J Clin Psych; 64:1065–74 –4. Roose et al (2004) Am J Psych; 161:2050-9– 5. Kasper et al (2005) Am J Geri Psych;13:884-91 – 6. Schatzberg & Roose (2006). Am J Geri Psych; 14:361-70 -- 7. Bose et al. (2008) Am J Geri Psych; 16:14-20 – 8. Raskin et al (2007) Am J Psychiatry; 164:900-9

30. What is new since 2001? Role of newer antidepressants? • Escitalopram • Desvenlafaxine • Duloxetine Role of atypical antipsychotics? • Quetiapine XR •Aripiprazole New Safety Concerns • Venlafaxine • Citalopram & Escitalopram • Atypical antipsychotics

31. Response Rates (%): Older vs. Newer Medications * * * * * 1. Tollefson et al (1995) Int Psychogeriatrics; 7:89–104 – 2. Schneider et al (2003) Am J Psych; 160:1277-85 – 3. Rapaport et al (2003) J Clin Psych; 64:1065–74 – 5. Kasper et al (2005) Am J Geri Psych;13:884-91 – 7. Bose et al. (2008) Am J Geri Psych; 16:14-20 – 8. Raskin et al (2007) Am J Psych; 164:900-9 – 9. Katila et al (2012) Am J Geri Psych

32. Discontinuation Rates Attributed to Adverse Effects: Older vs. Newer Medications 1. Tollefson et al (1995) Int Psychogeriatrics; 7:89–104 – 2. Schneider et al (2003) Am J Psych; 160:1277-85 – 3. Rapaport et al (2003) J Clin Psych; 64:1065–74 – 5. Kasper et al (2005) Am J Geri Psych;13:884-91 – 7. Bose et al. (2008) Am J Geri Psych; 16:14-20 – 8. Raskin et al (2007) Am J Psych; 164:900-9 – 9. Katila et al (2012) Am J Geri Psych

33. What is new since 2001? Role of newer antidepressants? • Escitalopram • Desvenlafaxine • Duloxetine Role of atypical antipsychotics? • Quetiapine •Aripiprazole New Safety Concerns • Venlafaxine • Citalopram & Escitalopram • Atypical antipsychotics

34. Atypical Antipsychotics and Risk of Sudden Cardiac Death Among Patients of All Age Ray WA et al (2009) New England Journal of Medicine; 360:225-35

35. What is new since 2001? Role of newer antidepressants? • Escitalopram • Desvenlafaxine • Duloxetine Role of atypical antipsychotics? • Quetiapine •Aripiprazole New Safety Concerns • Venlafaxine • Citalopram & Escitalopram • Atypical antipsychotics

36. Drug-drug interactions1 Hyponatremia2 Falls3,4 Hip fractures5,6 GI bleeds7 Cardiovascular effects,8,9 Cognitive impairment10,11,12 Suicide13 Bone metabolism14, 15 Antidepressants for the Older AdultPotential Safety Concerns 1. Mulsant & Pollock, BG (2004). American Psychiatric Publishing Textbook of Geriatric Psychiatry, 3rd Edition – 2. Fabian et al (2004) Arch Int Med; 164:327-32 – 3. Joo et al (2002) J Clin Psych; 63:936-41 – 4. Thapa et al (1998) NEJM; 339:875-82 – 5. Liu et al (1998) Lancet;351:1303-7 – 6. Richards et al (2007) Arch Int Med; 167:188-95 – 7. Yuan et al (2006) Am J Med; 119:719-27 – 8. Johnson et al (2006) Am J Geri Psych; 14:796-802 – 9. Oslin et al (2003) J Clin Psych; 64:875–882 – 10. Furlan et al (2001) Am J Geri Psych; 9:429-38 – 11. Ridout et al (2003) Hum Psychopharm; 18:261 – 12. Wingen et al (2005) J Clin Psych; 66:436-43 – 13. Jurlink et al (2006) Am J Psych;163:813-21 – 14. Diem et al (2007) Arch Intern Med; 167:1240-5 – 15: Richards et al (2007) Arch Intern Med 167:188–94

37. Augmentation v. SwitchingTolerability and Safety Discontinuation due to Adverse Events: 51% augmentation v. 8% switching Falls: 42% augmentation v. 24% switching Whyte et al (2004) J. Clin Psych; 65: 1634-1641

38. Conclusions: Late-Life Depression • Can be effectively treated • Success requires a systematic approach • Success requires persistence • DO NOT GIVE UP!

40. Questions and Discussion