Slides - HIV CENTER

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Slides - HIV CENTER

  1. 1. Mark V. Bradley, M.D. Research Fellow, HIV Center for Clinical and Behavioral Studies, NewYork State Psychiatric Institute and Columbia University HIV Center for Clinical and Behavioral Studies Grand Rounds June 26, 2008
  2. 2. The effectiveness of antiretroviral regimens depends upon high levels of patient adherence.  Treatment failure is predicted by poor adherence  High levels of adherence are required to ensure virologic suppression and prevent resistant strains (varies by regimen class type).  Most studies show that 40-60% of patients are less than 90% adherent
  3. 3.  Structural • Housing • Access to care • Financial resources • Transportation  Medication Regimen Characteristics • Complexity/Pill burden • Side effects  Individual-level factors • Education and health literacy • Physical symptoms • Use of avoidant coping strategies • Health beliefs • Psychiatric symptoms/disorders
  4. 4.  Substance use disorders  Intravenous drug use  Marijuana  Cocaine use including crack  Problem alcohol use  Methamphetamine  “Serious mental illness”: psychotic illnesses and bipolar disorder  Anxiety disorders including PTSD  Depressive symptoms / disorders
  5. 5.  High prevalence of depressive disorders in HIV+ samples  Depression predicts poorer medical outcomes in HIV (Clinical progression, mortality), even after controlling for adherence
  6. 6. Depression is a robust predictor of nonadherence across a range of studies and methodologies Most of these studies have examined depression symptoms rather than categorical diagnoses.  Wagner et al, J Clin Epidemiol, 2001. 54 Suppl 1: p. S91-8.  Palepu et al, substance abuse treatment. Addiction, 2004. 99(3): p. 361-8.  Barfod et al AIDS Patient Care STDS, 2005. 19(5): p. 317-25.  Ammassari A., et al., Psychosomatics, 2004. 45(5): p. 394-402.  Arnsten et al, J Gen Intern Med, 2002. 17(5): p. 377- 81.  Blanco et al, AIDS Res Hum Retroviruses, 2005. 21(8): p. 683-8.  Boarts et al, AIDS Behav, 2006.  Carrieri et al., Int J Behav Med, 2003. 10(1): p. 1-14.  Catz et al., Health Psychol, 2000. 19(2): p. 124-33.  Gonzalez et al, Health Psychol, 2004. 23(4): p. 413- 8.  Gordillo, et al Aids, 1999. 13(13): p. 1763-9.  Murphy et al., Arch Pediatr Adolesc Med, 2005. 159(8): p. 764-70.  Holzemer et al., AIDS Patient Care STDS, 1999. 13(3): p. 185-97.  Reynolds et al., AIDS Behav, 2004. 8(2): p. 141-50.  Tucker et al., Am J Med, 2003. 114(7): p. 573-80.  Waldrop-Valverde et al, Patient Care STDS, 2005. 19(5): p. 326-34.
  7. 7. Cardiac disease and diabetes research has also found that depression predicts poor medication adherence  Gehi, A., et al., Depression and medication adherence in outpatients with coronary heart disease: findings from the Heart and Soul Study. Arch Intern Med, 2005. 165(21): p. 2508-13.  Kalsekar, I.D., et al., Depression in patients with type 2 diabetes: impact on adherence to oral hypoglycemic agents. Ann Pharmacother, 2006. 40(4): p. 605-11.  Lustman, P.J. and R.E. Clouse, Depression in diabetic patients: the relationship between mood and glycemic control. J Diabetes Complications, 2005. 19(2): p. 113-22.  Barth, J., M. Schumacher, and C. Herrmann-Lingen, Depression as a risk factor for mortality in patients with coronary heart disease: a meta- analysis. Psychosom Med, 2004. 66(6): p. 802-13.
  8. 8.  Two studies provide retrospective evidence that treatment of depression improves adherence in HIV+ populations (Yun et al, JAIDS 2005; Cook et al, AIDS Care 2006)  Research in other medical illnesses (diabetes, cardiocascular disease) have suggested prospectively and retrospectively that treating depression may improve adherence (Lustman, Arch Gen Psychiatry 2006; Katon et al, Arch Intern Med 2005 )
  9. 9. • To date, no published prospective research has demonstrated that treating depression improves adherence in HIV-positive depressed, nonadherent medical patients. • The symptom threshold for adherence problems is not known. • The time from depression response to adherence improvement is not known. • The specific components of depression symptomatology responsible for adherence failures are not known.
  10. 10.  Naturalistic design  Following depressed, antiretroviral nonadherent HIV+ clinic patients who have recently started or optimized treatment for depression  Monitoring their depressive symptoms and antiretroviral adherence as they continue antidepressant treatment.
  11. 11.  HIV+ adult patients  Referred to study based on history of depression and/or nonadherence  Recent initiation or change in antidepressant treatment (medication switch, titration, or augmentation) or initiation of psychotherapy  Followed in one of three HIV medical or mental health clinics at Columbia Med Ctr., or the Center for Special Studies at Cornell.
  12. 12.  Currently on antiretrovirals  Meet the criteria for Major Depressive Disorder, Minor Depressive Disorder, or Dysthymic Disorder (SCID)  Demonstrates <80% adherence at baseline  Does not meet criteria for substance use disorder in the past month  Fluent in English  No h/o bipolar disorder
  13. 13.  Adherence : • Chesney’s ACTG Follow-Up Questionnaire for Adherence to Antiretroviral Medications • Visual Analog Scale • Pill Count • Viral load  Depression : • Hamilton Depression Scale • Depression Module of the SCID
  14. 14.  Substance use: HIV Center Substance Use Questionnaire (potential depression- nonadherence mediator)  Cognition: • Rey Verbal Learning Test • WAIS Letter-Number Sequence • Stroop • Color Trails A and B • Controlled Oral Word Association • WAIS Test of Adult Reading
  15. 15. Assessment Time Baseline assessment (0 weeks) Follow up assessment 1 (4 weeks) Follow up assessment 2 (8 weeks) Measures -SCID -Adherence measures -HAM-D -Substance use Questionnaire -Demographics -Brief Cognitive Battery -Adherence measures -Substance use questionnaire -HAM-D -Depression module of SCID -Adherence measures -Substance use questionnaire -HAM-D -Depression module of SCID -Brief Cognitive Battery
  16. 16.  Linear regression models to examining associations between changes in adherence scores and changes in HAM-D scores, controlling for substance use at each time point.  Generalized estimating equations will be used to account for within-subject correlation across the three time points.  In secondary analyses, we will examine relationships between specific depression symptoms (such as depressed mood, insomnia, and anergia) and adherence
  17. 17.  Recruitment procedures commenced in November, 2007  Recruitment represented a major challenge to this study  The intersection of specific eligibility criteria in several domains resulted in many patients being screened out of the study: • Depressive disorder • <80% adherent in past 4 days - 1 week • Recent onset/change in depression treatment • Fluent in English • Not actively using substances • No history of bipolar disorder • No psychotic symptoms
  18. 18.  Many patients identified and treated for depression demonstrate good adherence  Many patients systematically identified as nonadherent by their clinicians also demonstrate other exlusionary features, especially active substance use and comorbid psychopathology
  19. 19. 9 participants recruited to date N % Gender 5 men 4 women 56 44 Ethnicity African- American 4 44 White 3 33 More than one 2 22 Inclusion diagnosis 6 MDD 3 Dysthymic 66 33 Sexual orientation 5 straight 4 gay 56 44 Unmployed 8 89
  20. 20. mean range Baseline 21-item Hamilton 13.67 3-22 Baseline Adherence 69.3 52.5-80.5
  21. 21.  4 participants have completed to date. • These subjects have overall demonstrated some evidence of improvement in adherence which occurred alongside improvements in depression scores  2 participants have not followed up after baseline due to re-emergent, severe substance use problems  3 participants remain in the process of data collection
  22. 22. Baseline 4 weeks 8 weeks Subject HAM- D ADH % HAM- D ADH % Dep Dx HAM- D ADH % Dep Dx 1 11 67.5 2 81.5 None 3 67.3 None 2 13 64.1 9 95 None 15 95 None 3 20 52.5 10 98 None 4 100 None 4 10 80.5 7 90.5 MDD 3 100 None Means 13.5 66.3 7 91.3 6.25 90.6
  23. 23.  Depressed, nonadherent HIV-positive patients demonstrate a degree of psychosocial complexity and comorbidity that makes recruitment challenging.  Studies designed to examine this population may require a degree of “tolerance” for this complexity, rather than highly restrictive eligibility criteria
  24. 24.  When substance use disorders are not an active issue, individual cases suggest that treating depressive disorders may be one method for improving adherence in depressed patients  Future research will require larger samples and longer follow-up periods in order to elucidate relationships between depression treatment and adherence changes.
  25. 25.  This study has been funded by the HIV Center’s Pilot Studies Program and by the Columbia Department of Psychiatry Frontier Fund.  Dr. Bradley is supported by a training grant from NIMH (T32 MH19139; Behavioral Sciences Research in HIV Infection; Principal Investigator, Anke A. Ehrhardt Ph.D.;Training Director:Theo Sandfort, Ph.D.).  The HIV Center for Clinical and Behavioral Studies at the New York State Psychiatric Institute and Columbia University is supported by a grant from NIMH (P30-MH43520; Principal Investigator: Anke A. Ehrhardt Ph.D.).
  26. 26. Mentor Robert H. Remien, PhD Study Advisors Judith G. Rabkin, PhD Milton Wainberg, MD Cheng-Shiun Leu, PhD HIV Center Expertise Patricia Warne, PhD Katherine Elkington, PhD Research Assistant Elizabeth Arias, MA Harkness-6 Karen Brudney, MD Noga Shalev, MD Anne Skomorowsky, MD Lucy Ann Wicks Clinic Joan Storey, PhD Vera Smith, PhD Alexandra Bloom, PhD Elizabeth Wade, PhD Center for Special Studies Todd P. Loftus, MD Joseph F. Murray, MD

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