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Presented by The Johns Hopkins University School of Medicine

Maintaining Cardiovascular Health in HIV-positive Patients: An Interactive Meeting to Discuss Assessment and Management of Risk. Presented by The Johns Hopkins University School of Medicine Produced in collaboration with ViralEd LLC Supported by an educational grant from Gilead Sciences.

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Presented by The Johns Hopkins University School of Medicine

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  1. Maintaining Cardiovascular Health in HIV-positive Patients: An Interactive Meeting to Discuss Assessment and Management of Risk Presented by The Johns Hopkins University School of Medicine Produced in collaboration with ViralEd LLC Supported by an educational grant from Gilead Sciences

  2. Welcome and Introduction Moderator: Ian Frank, MD Discussants: Wendy Post, MD Cal Cohen, MD

  3. Accreditation Statement The Johns Hopkins University School of Medicine is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians. Credit Designation Statement:The Johns Hopkins University School of Medicine designates this educational activity for a maximum of 2.0 AMA PRA Category 1 Credits™. Physicians should only claim credit commensurate with the extent of their participation in the activity. To obtain CME credit, on the home page of this program under the heading “Instructions for Obtaining Continuing Medical Education Credit” there is a “CME Post Test and Evaluation” link that take you to the CME test.

  4. This program is made possible through an educational grant from Gilead Sciences

  5. Program Objectives At the conclusion of this activity the participant should be able to: 1) Clinically assess and utilize risk factors for coronary heart disease (CHD) and predict an HIV-positive patient’s pre-ARV treatment risk of CHD 2) Describe, discuss and apply the data from the SMART study on CHD risk associated with ARV treatment interruption and be able to integrate these data into ARV treatment plans and algorithms for HIV-positive patients 3) Analyze and apply current data on the risk of CHD associated with certain ARV drugs and/or regimens and use this information to select ARV drugs and regimens that minimize CHD risk for HIV-positive patients, and, in particular, for those patients with increased baseline risk for CHD 4) Analyze and use in clinical cases the current clinical trial data on treatment of hyperlipidemia, hyperglycemia and other CHD risk factors and use this information to select appropriate therapeutic strategies for HIV-positive patients to mitigate the CHD risk associated with them

  6. Course Directors John Bartlett, MDProfessor of MedicineJohns Hopkins School of MedicineBaltimore, Maryland Wendy Post, MD Associate Professor of MedicineJohns Hopkins School of MedicineBaltimore, Maryland

  7. Cardiology Faculty James H. Stein, MD University of Wisconsin School of Medicine and Public Health Madison, Wisconsin Richard F. Wright, MD Pacific Heart Institute David Geffen School of Medicine at UCLA Los Angeles, California W. Virgil Brown, MD Emory University School of Medicine Atlanta Veterans Affairs Medical Center Atlanta, Georgia Laurence Sperling, MD Emory University School of Medicine Atlanta, Georgia Priscilla Hsue, MD University of California, San Francisco School of Medicine San Francisco, California Michael Miller, MD University of Maryland Medical Center Baltimore, Maryland Nicole M. Weinberg, MD Pacific Heart Institute Los Angeles, CA

  8. HIV Faculty Rafael E. Campo, MDUniversity of Miami School of MedicineMiami, Florida Calvin J. Cohen, MD, MSResearch Director, CRI New EnglandClinical Instructor, Harvard Medical SchoolBoston, Massachusetts Eric Daar, MDDavid Geffen School of Medicine at UCLALos Angeles, California Edwin DeJesus, MDOrlando Immunology CenterOrlando, Florida Richard A. Elion, MDGeorge Washington University Medical CenterWashington, DC Ian Frank, MDUniversity of Pennsylvania Philadelphia, Pennsylvania Trevor Hawkins, MDSouthwest CARE CenterSanta Fe, New Mexico Graeme J. Moyle, MD, MB, BSChelsea & Westminster HospitalLondon, England Paul Sax, MDHarvard Medical SchoolBoston, Massachusetts Luther A. Virgil, Jr., MDNational Minority ClinicalResearch AssociationFairfield, New Jersey

  9. Disclosures As a provider accredited by the Accreditation Council for Continuing Medical Education (ACCME), it is the policy of the Johns Hopkins University School of Medicine to require the disclosure of the existence of any significant financial interest or any other relationship a faculty member or a sponsor has with the manufacturers of any commercial products discussed in an educational presentation. The disclosures of the faculty for this program can be found in your handout materials and are presented in the following slides:

  10. Course Director Disclosures John Bartlett, MD Consulting Agreements: Johnson & Johnson; Tibotec; Merck & Co. Speakers' Bureau/Honorarium Agreements: Abbott Labs, Merck & Co. Financial Interests/Stock Ownership: None Other Financial or Material Support: DSMB; Tibotec Wendy Post, MD Grant Research: None Consulting Agreements: None Speakers' Bureau/Honorarium Agreements: None Financial Interests/Stock Ownership: None Other Financial or Material Support: None

  11. Discussant Disclosures • Wendy Post, MD • None to report • Cal Cohen, MD • Grant Research: GSK, BMS, Tibotec, Gilead, Virco, Merck, Abbott, Pfizer • Consulting Agreements: GSK, BMS, Tibotec, Gilead, Virco, Merck, Abbott, Pfizer • Speakers' Bureau/Honorarium Agreements: GSK, BMS, Tibotec, Gilead, Virco, Merck, Abbott, Pfizer • Financial Interests/Stock Ownership: None • Other Financial or Material Support: ViralEd LLC • This presentation includes information on studies and data presented off-label uses of efavirenz, nevirapine, raltegravir, abacavir, emtricitabine, atazanavir, and raltegravir.

  12. The Johns Hopkins University School of Medicine takes responsibility for the content, quality, and scientific integrity of this CME activity.

  13. Assessment of Coronary Heart Disease Risk in Patients with HIV Infection

  14. Presentation Outline • Prediction of coronary hear t disease (CHD) risk in the general population • Prediction of CHD risk in patients with HIV • Effects of antiretroviral therapy (ART) on short term CHD risk • Effects of specific ART classes and agents on CHD risk • Integrating CHD risk factors and ART-associated CHD risk

  15. CHD Risk Factors • Key Point #1: The vast majority of CHD can be predicted by knowing a patient’s traditional risk factors • Key Point #2: Traditional CHD risk factors also are the major determinants of CHD risk in patients with HIV infection

  16. Major Risk Factors for Coronary Heart Disease • Powerful, non-modifiable risk factors include • Aging • Male sex • Best studied, modifiable risk factors • Dyslipidemia • Hypertension • Cigarette smoking • Diabetes mellitus • Adverse dietary habits Greenland P, et al. JAMA 2003;290:891

  17. CHA FHS MRFIT Over 87% of Patients with Fatal CHD Have at Least One Major CHD Risk Factor all CHA, MRFIT p<0.001 Greenland P, et al. JAMA 2003;290:891

  18. CHA FHS MRFIT Patients With At Least One Major CHD Risk Factor at “Higher Than Favorable” Levels • Total cholesterol ≥ 200 mg/dL (or use of cholesterol med) • BP > 120/80 mmHg (or use of BP med) • Current cigarette use • Diabetes mellitus all CHA, MRFIT p<0.001, except CHA W 18-39, p=0.03 Greenland P, et al. JAMA 2003;290:891

  19. Current smoking Females Diabetes Males Hypertension Abdominal obesity Psychosocial index Fruits/Vegetables Exercise Alcohol ApoB-ApoA1 ratio 0.25 0.5 1 2 4 8 16 INTERHEART: Effect of Modifiable Risk Factors on MI Incidence Odds ratio (99% CI) Yusuf S, et al. Lancet 2004;364:937

  20. INTERHEART: Population Attributable Risk of MI • All nine risk factors = 90% • All lifestyle = 63% Yusuf S, et al. Lancet 2004;364:937

  21. Complications of Central Obesity • Hyperinsulinemia ± glucose intolerance • Atherogenic lipoprotein phenotype • Low HDL-C • Hypertriglyceridemia • Increased numbers of small dense LDL • Hypertension • Proinflammatory state • Prothrombotic state

  22. Diagnosis of Metabolic Syndrome For diagnosis of metabolic syndrome, need 3 of: • Waist >40″ in men, 35″ in women • Asian-Americans: >35″ in men, 31″ in women • HDL-C <40 in men, <50 mg/dL in women • Triglycerides 150 mg/dL • BP 130/85 mmHg • Fasting Plasma Glucose 100 mg/dL NCEP Expert Panel. JAMA 2001, 285:2486 Grundy S, et al. Circulation 2005, 112:2735

  23. Cardiovascular All-Cause 25% RR (95% CI): 3.55 (1.96-6.43) RR (95% CI): 2.43 (1.64-3.61) 20% 15% 10% 5% years 0 2 4 6 8 10 12 0 2 4 6 8 10 12 Yes No Mortality From Metabolic Syndrome Metabolic Syndrome Lakka HM, et al. JAMA 2002; 288:2709

  24. Subclinical Atherosclerosis Increases with More Components of the Metabolic Syndrome r = 0.997, ptrend < 0.001 Tzou WS, et al. J Am Coll Cardiol 2005; 46:457

  25. No DM (N=1373) DM (N=1059) Type II Diabetes Mellitus is a CHD Risk Equivalent 7 year risk of MI (%) Haffner S, et al. N Engl J Med 1998;339:229

  26. 10 3.31 3.24 1.95 1.73 0.97 Adjusted OR CVD 1 Age >40 Diabetes Hyperlipidemia HTN Nadir HDL-C p<0.001 p<0.001 p=0.024 p=0.059 p=0.004 0.1 CHD Risk Factors Predict Cardiovascular Disease Events in the HOPS Cohort Lichtenstein K, et al. 13th CROI 2006. Abstract 735

  27. Risk Factors for MI in D:A:D DAD Study Group. N Engl J Med 2007; 356:1723

  28. D:A:D CHD Risk Equation • N = 9,023 with 157 cases of CHD over 35,594 person-years of follow-up • Events = CHD death, MI, coronary artery revascularization procedures • Best model of 5-year risk (AUC = 0.78 [0.76-0.82]) • Standard risk factors: age, sex, family history, systolic blood pressure smoking status, total/high-density lipoprotein cholesterol ratio, diabetes plus • Duration of PI exposure Friis-Moller N, et al. CROI 2007; Poster 808

  29. 100 100 % Patients on HAART Combined rate of AIDS and death 80 60 CombinedAIDS and Death Rates Patients % 10 40 20 0 1 Sept 1994 Sept1999–March 2000 Sept 2000–March2001 Sept1998–March 1999 March 1995–Sept1995 Sept 1995–March1996 March 1996–Sept 1996 Sept 1996–March1997 M<arch 1995 March 1997–Sept1997 Sept1997–March 1998 March 1998–Sept 1998 March 2000–Sept2000 Sept 2001–onwards EuroSIDA: Decreases in AIDS and Death Since the Introduction of Active ART Mortality across Europe, Israel and Argentina in 9803 patients March 2001– Sept 2001 March 1999– Sept 1999 Mocroft A, et al. Lancet2003;362:22

  30. 70.0 Any antiretroviral Nucleoside analog Protease inhibitor Non-nucleoside RT inhibitor 60.0 50.0 40.0 Years of Exposure/100 Patient-Yr 30.0 20.0 10.0 0.0 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 25.00 Inpatient stay for myocardial infarction,stroke, or death from any cause All cause mortality Inpatient stay for myocardial infarctionor equivalent 20.00 15.00 No. of Events/100 Patient-Yr 10.00 5.00 0.00 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 Short-Term CHD Risk with ART • Retrospective study of electronic data from VA (1993-2003) • 168,213 person-yrs of follow-up • Average f/up = 4 years • 19,898 deaths, CVD admissions, strokes • CHD rate not increased by any ART class Bozette S, et al. JAIDS 2008; 47:338

  31. 10 5 Change in FMD from Baseline to Week 24 (%) 0 -5 All Subjects PI-Sparing(EFV+NRTIs) NNRTI-Sparing(LPV/r+NRTIs) NRTI-Sparing(EFV-LPV/r) Short-Term Treatment with ART Improves Endothelial Function • Treatment-naïve HIV infected patients (N=82) • Randomized to 3 class-sparing ART regimens • Brachial artery flow-mediated dilation (FMD) increased by 1.48% (p<0.001) • FMD improvement similar in each arm, despite significant differences in lipids Stein JH, et al. J Am Coll Cardiol 2008; 52:569

  32. SMART: Increased Cardiovascular Riskin Drug Conservation Arm (N = 5472) CD4-guided drug conservation strategy had greater disease progression or death than continuous viral suppression: RR 2.6 (95% CI 1.9–3.7; p<0.001) • Cardiovascular disease events not associated with being off ART or VL • Total/HDL cholesterol ratio higher in DC arm, because HDL-C decreased El Sadr WM, et al.N Engl J Med 2006; 355:2283 Phillips A, et al. 14th CROI, Los Angeles 2007, #41

  33. Faculty Discussion

  34. CHD Risk with ART • Key Point #3: Effective ART improves survival and may reduce short-term CHD risk • Key Point #4: Long-term use of PIs may increase CHD risk; an observation that is partially related to adverse metabolic effects • Key Point #5: Use of abacavir may increase short-term CHD risk

  35. 10 Protease inhibitors Nonnucleoside reverse-transcriptase inhibitors 9 8 7 6 Incidence per 1000 Person-Yr 5 4 3 2 1 0 0 0 <1 1-2 2-3 3-4 4-5 5-6 >6 Exposure (yr) Use of Protease Inhibitors Increased MI Risk in the D:A:D Study PIs: adjusted RR = 1.16 (1.10-1.23, p<0.001) NNRTIs: adjusted RR = 1.05 (0.98-1.13, p=0.17) DAD Study Group. N Engl J Med 2007; 356:1723

  36. PI* NNRTI 1.9 1.13 1.1 RR Per Year (95%CI) 1 0.9 IDV NFV LPV/r SQV NVP EFV PYFU: MI: 68,469 298 56,529 197 37,136 150 44,657 221 61855 228 58,946 221 IDV and LPV/r Increased MI Risk in D:A:D Study • N = 33,308 patients (580 with MI) * Approximate test for heterogeneity: P=0.02 Lundgren J, et al. CROI 2009, abstract 44, 2/8/2009

  37. NRTIs and MI Risk in D:A:D • N = 33,347 patients with 517 cases of MI • 157,912 person-years • Background MI rate = 3.3/1000 patient-years • Increased MI risk with ongoing/recent exposure to • Abacavir (RR 1.90, 95% CI 1.47-2.24) • Didanosine (RR 1.49, 95% CI 1.14-1.95) • Excess risk not seen in those who had stopped ABC or ddI • No excess risk with 3TC or thymidine analogues DAD Study Group. Lancet 2008;371:1417

  38. No recent didanosine 35 35 Recent didanosine 30 30 25 25 20 20 Rate (per 1000 patient-years) 15 15 10 10 5 5 0 0 Events Patient years 393 130184 124 27728 78 59281 24 13102 86 14289 26 3383 134 6914 34 1474 95 49700 40 9770 No recent abacavir Recent abacavir Rate (per 1000 patient-years) Events Patient years 325 126581 192 31331 60 57628 42 14754 79 13372 33 4300 100 6293 68 2095 86 49288 49 10182 Overall Low Moderate High Not Known Predicted 10-year Risk of Coronary Heart Disease NRTIs and MI Risk in D:A:D • Increased risk from ABC and ddI most marked in those at “high” risk (6% of D:A:D) • Numbers needed to harm/5 years • ABC = 11 • ddI = 20 DAD Study Group. Lancet 2008;371:1417 Stein JH, Currier JS. Lancet 2008;371:1391

  39. Additional D:A:D data confirm Abacavir Increases MI risk • N = 33,308 patients (580 with MI) • Recent (<6 months) exposure to ABC and ddI increased MI risk • Cumulative exposure to ABC also increased MI risk • 3TC, thymidine analogs and TDF exposure did not increase MI risk Lundgren J, et al. 16th CROI, 2009. Abstract 44.

  40. 1.9 1.9 1.5 1.5 1.2 1.2 RR Yes/No (95%CI) RR Per Year (95%CI) ** 1 1 0.8 0.8 0.6 0.6 ZDV ddl ddC d4T 3TC ABC TDF #PYFU: #MI: 138,109 523 74,407 331 29,676 148 95,320 405 152,009 554 53,300 221 39,157 139 NRTIs and MI Risk in D:A:D *Recent use=current or within the last 6 months. **Not shown (low number of patients currently on ddC) Lundgren J, et al. CROI 2009, abstract 44, 2/8/2009

  41. SMART Study:Increased MI Risk with Abacavir • N = 2752 subjects assigned to continuous ART • Use of abacavir (but not ddI) associated with increased cardiovascular disease compared to other NRTIs • ABC also associated with increased hs-CRP and IL-6 SMART/INSIGHT and D:A:D Study Groups. AIDS 2008;22:F17

  42. ANRS: Increased Risk of MI with Short-term, Recent ABC Use Nested, case-control study to evaluate association between risk of MI and exposure to NRTIs >115,000 HIV-infected patients enrolled between 1989 and 2006 Data collected for cases and controls Cardiovascular risk factors and treatments HIV history and treatment *P=0.025 Lang S, et al .16th CROI, Montreal, Canada, 2009. Abst . 43LB.

  43. GSK: Exposure to ABC Did Not Increase CV Risk in ABC Clinical Trials Limitations: Relatively small number of events; studies not designed to look for CV risk Cutrell A, et al. 17th IAC, Mexico City, 2008; Abst. WEAB0106.

  44. ACTG 5001:ABC Not Associated with CV Risk Evaluation of association between ABC and risk of MI or severe CVD after starting HAART Patients randomized to first ART in 5 ACTG studies evaluated for CV risk factors (N=3,205) 63 severe CVD, including 27 MI No association of ABC and severe CVD or MI found Limitations: Relatively small number of events; studies not designed to look for CV risk Benson C, et al. 16th CROI, Montreal, Canada, 2009. Abst. 721.

  45. Integrating CHD Risk Factors and ART-Associated CHD Risk • ART associations with CHD are derived from observational data which can be subject to biases and unmeasured confounding • Some degree of increased risk is attributable to cumulative metabolic effects, such as dyslipidemia • Although the relative risk associated with ART is small over the short-term, it is clinically relevant over longer periods of exposure • Absolute risk associated with ART is important in moderate or high risk patients • Studies not finding risk associated with certain ARV use may be confounded by a number of factors: • Small number of patients enrolled • Not being designed to assess CV risk and events • Limited follow-up

  46. Faculty Discussion

  47. CHD Risk Assessment and Prevention • Key Point #6: Absolute CHD risk estimates should drive clinical decisions regarding CHD prevention

  48. CHD Risk Assessment • Guiding principle: A patient’s absolute CHD risk determines the intensity of risk-reducing interventions • CHD risk is assessed by three steps • Evaluating for the presence of coronary heart disease or risk equivalent conditions • Counting risk factors • Framingham risk assessment if ≥2 risk factors • Absolute risk is used to set goals for lipids and other preventive interventions – higher risk patients get more aggressive interventions NCEP ATP III. JAMA 2001; 285:2486

  49. Categorical CHD Risk Factors that Modify LDL-C Goals • Age (men 45 years; women 55 years) • Family history of premature CHD • CHD in male first degree relative <55 yo • CHD in female first degree relative <65 yo • Cigarette smoking • Hypertension (BP 140/90 mmHg or on antihypertensive medication) • Low HDL-C (<40 mg/dL)* *HDL-C 60 mg/dL counts as a “negative” risk factor NCEP ATP III. JAMA 2001; 285:2486

  50. LDL Cholesterol Goals are Based on Level of CHD Risk Grundy SM, et al. Circulation 2004;110:227

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