HIV and Cardiovascular Disease.How Worried Should We Be ? 2015
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In this downloadable slideset, David A. Wohl, MD, reviews the association between HIV and cardiovascular disease, including potential contributing factors and best practices in prevention. Format: Microsoft PowerPoint (.ppt) File size: 5.01 MB Date posted: 6/26/2015
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HIV and Cardiovascular Disease.How Worried Should We Be ? 2015
- 1. David Alain Wohl, MD Associate Professor of Medicine School of Medicine Site Leader, AIDS Clinical Trials Unit-Chapel Hill University of North Carolina at Chapel Hill Director, North Carolina AIDS Training and Education Center Chapel Hill, North Carolina Co-Director for HIV Services North Carolina Department of Correction Raleigh, North Carolina HIV and Cardiovascular Disease: How Worried Should We Be? Supported by educational grants from AbbVie, Bristol-Myers Squibb, Gilead Sciences, Janssen, Merck, and ViiV.
- 2. clinicaloptions.com 25th Annual CCO HIV and Hepatitis C Symposium About These Slides Users are encouraged to use these slides in their own noncommercial presentations, but we ask that content and attribution not be changed. Users are asked to honor this intent These slides may not be published or posted online without permission from Clinical Care Options (email permissions@clinicaloptions.com) Disclaimer The materials published on the Clinical Care Options Web site reflect the views of the authors of the CCO material, not those of Clinical Care Options, LLC, the CME providers, or the companies providing educational grants. The materials may discuss uses and dosages for therapeutic products that have not been approved by the United States Food and Drug Administration. A qualified healthcare professional should be consulted before using any therapeutic product discussed. Readers should verify all information and data before treating patients or using any therapies described in these materials.
- 3. clinicaloptions.com 25th Annual CCO HIV and Hepatitis C Symposium Disclosures David A. Wohl, MD, has disclosed that he has received consulting fees from Gilead Sciences and Janssen and funds for research support from Merck.
- 4. clinicaloptions.com 25th Annual CCO HIV and Hepatitis C Symposium Outline There are data suggesting increased risk of comorbidities, including CVD, in people with HIV CVD is clearly more common in people with HIV What is unclear is why – Possibilities – More risk factors (smoking, sedentariness, stress, depression) – HIV (via immune and inflammatory mechanisms, microbial translocation, CMV) – ART Assessing risk Approaches to prevention
- 5. clinicaloptions.com 25th Annual CCO HIV and Hepatitis C Symposium Outline There are data suggesting increased risk of comorbidities, including CVD, in people with HIV CVD is clearly more common in people with HIV What is unclear is why – Possibilities – More risk factors (smoking, sedentariness, stress, depression) – HIV (via immune and inflammatory mechanisms, microbial translocation, CMV) – ART Assessing risk Approaches to prevention
- 6. clinicaloptions.com 25th Annual CCO HIV and Hepatitis C Symposium The Link between HIV and CVD Rates of AMI compared in HIV+ and HIV- pts at 2 Boston hospitals – N of ~ 3800 for HIV+ pts; > 1 million for HIV- pts – 8-yr period 1996-2004 The HIV cohort had significantly > proportions of hypertension (21.2% vs 15.9%), diabetes (11.5% vs 6.6%), and dyslipidemia (23.3% vs 17.6%) (P < .0001 for each) Triant VA, et al. J Clin Endocrinol Metab. 2007;92:2506-2512. Eventsper1000PYsEventsper1000PYs 18-34 35-44 45-54 55-64 65-74 Age Group (Yrs) 0 20 40 80 100 60 0 2 4 10 12 8 6 RR 1.75* P < .0001 HIV Positive HIV Negative *Adjustment was made for these plus age, sex, race, hypertension.
- 7. clinicaloptions.com 25th Annual CCO HIV and Hepatitis C Symposium 100 80 60 40 20 0 Post WS, et al. Ann Intern Med. 2014;160:458-467. HIV Infection and Subclinical Coronary Atherosclerosis + - + - + - + - + - + - 40-44 53 26 45-49 124 45 50-54 118 88 55-59 91 60 60-64 50 54 65+ 14 36Men in Each Group, n HIV Status Age, yrs Prevalenceof NoncalcifiedPlaque (%)
- 8. clinicaloptions.com 25th Annual CCO HIV and Hepatitis C Symposium
- 9. clinicaloptions.com 25th Annual CCO HIV and Hepatitis C Symposium Outline There are data suggesting increased risk of comorbidities, including CVD, in people with HIV CVD is clearly more common in people with HIV What is unclear is why – Possibilities – More risk factors (smoking, sedentariness, stress, depression) – HIV (via immune and inflammatory mechanisms, microbial translocation, CMV) – ART Assessing risk Approaches to prevention
- 10. clinicaloptions.com 25th Annual CCO HIV and Hepatitis C Symposium Outline There are data suggesting increased risk of comorbidities, including CVD, in people with HIV CVD is clearly more common in people with HIV What is unclear is why – Possibilities – More risk factors (smoking, sedentariness, stress, depression) – HIV (via immune and inflammatory mechanisms, microbial translocation, CMV) – ART Assessing risk Approaches to prevention
- 11. clinicaloptions.com 25th Annual CCO HIV and Hepatitis C Symposium The Link Between HIV and CVD Rates of AMI compared in HIV+ and HIV- pts at 2 Boston hospitals – N of ~ 3800 for HIV+ pts; > 1 million for HIV- pts – 8-yr period 1996 to 2004 The HIV cohort had significantly > proportions of hypertension (21.2% vs 15.9%), diabetes (11.5% vs 6.6%), and dyslipidemia (23.3% vs 17.6%) (P < .0001 for each) Triant VA, et al. J Clin Endocrinol Metab. 2007;92:2506-2512. Eventsper1000PYsEventsper1000PYs 18-34 35-44 45-54 55-64 65-74 Age Group (Yrs) 0 20 40 80 100 60 0 2 4 10 12 8 6 RR 1.75* P < .0001 HIV Positive HIV Negative *Adjustment was made for these plus age, sex, race, hypertension.
- 12. clinicaloptions.com 25th Annual CCO HIV and Hepatitis C Symposium How Big Is the Contribution of HIV and HIV- Related Factors to CVD and Other Conditions Associated With Aging? Traditional Factors
- 13. clinicaloptions.com 25th Annual CCO HIV and Hepatitis C Symposium
- 14. clinicaloptions.com 25th Annual CCO HIV and Hepatitis C Symposium HIV Serostatus and Coronary Artery Plaque Post WS, et al. Ann Intern Med. 2014;160:458-467. Variable Prevalence of plaque Noncontrast CT scans (n = 1001) CAC present Contrast-enhanced CT scans (n = 759) Any plaque present Noncalcified plaque present Mixed plaque present Calcified plaque present Coronary artery stenosis > 50% Coronary artery stenosis > 70% Minimally Adjusted Model* 1.21 (1.08 to 1.35) 1.14 (1.05 to 1.24) 1.28 (1.13 to 1.45) 1.35 (1.10 to 1.65) 1.05 (0.88 to 1.27) 1.48 (1.06 to 2.07) 1.20 (0.70 to 2.05) .001 .001 < .001 .004 .58 .02 .51 1.12 (0.99 to 1.26) 1.13 (1.04 to 1.23) 1.25 (1.10 to 1.43) 1.22 (0.98 to 1.52) 1.02 (0.84 to 1.23) 1.23 (0.86 to 1.75) 0.76 (0.44 to 1.30) .076 .004 .001 .070 .88 .26 .31 Adjusted for CAD Risk Factors† PR (95% CI)‡ P Value PR (95% CI)‡ P Value Extent of plaque§ Noncontrast CT scans CAC Agatston score (n = 527) Contrast-enhanced CT scans Segment involvement score Total coronary plaque score (n = 579) Noncalcified plaque score (n = 449) Mixed plaque score (n = 254) Calcified plaque score (n = 278) Mean Difference (95% CI)ǁ 0.07 (-0.23 to 0.38) 0.14 (0.02 to 0.25) 0.19 (0.05 to 0.33) 0.16 (0.03 to 0.29) 0.15 (-0.05 to 0.35) -0.02 (-0.21 to 0.17) .65 .023 .009 .015 .133 .83 0.03 (-0.34 to 0.29) 0.11 (-0.01 to 0.22) 0.13 (-0.01 to 0.27) 0.15 (0.02 to 0.29) 0.16 (-0.04 to 0.36) -0.07 (-0.27 to 0.12) .88 .075 .062 .026 .109 .46 *Adjusted for age, race, CT scanning center, cohort (before vs after 2001). † Adjusted for age, race, CT scanning center, cohort, and CAD risk factors (systolic blood pressure, antihypertensive medication use, diabetes medication use, fasting glucose level, total and high-density lipoprotein cholesterol levels, use of lipid-lowering medications, body mass index, and pack-yrs of smoking). ‡ Ratio of HIV-infected to HIV-uninfected men. § Analyses (in natural log scale) include men with plaque present (plaque score >0). ǁ HIV-infected minus HIV-uninfected men. P Value Mean Difference (95% CI)ǁ P Value
- 15. clinicaloptions.com 25th Annual CCO HIV and Hepatitis C Symposium 1. Klein DB, et al. CROI 2014. Abstract 737. 2. Klein DB, et al. Clin Infect Dis. 2015;60:1278-1280. 3. Marcus JL, et al. CROI 2014. Abstract 741. 4. Marcus JL, et al. AIDS. 2014;28:1911-1919. [3,4] The reduced MI incidence rates for HIV+ in recent yrs is likely a result of: – CVD risk factor reduction – Use of more lipid-friendly ART – Reduced immunodeficiency Yr 200 150 100 50 1996-1999 2000-2003 2004-2007 2008-2009 2010-2011 250 0 Stroke Rates by HIV Status and Yr[3,4] Casesper100,000PYs HIV+ HIV- 400 MIsper100,000PYs 300 200 100 0 1996-99 2000-03 2004-07 2008-09 2010-11 HIV+ HIV- MI Rates Over Time by HIV Status[1,2]
- 16. clinicaloptions.com 25th Annual CCO HIV and Hepatitis C Symposium Hanna D, et al. CROI 2015. Abstract 729. 2001-2012 mortality data NYC The NYC HIV Surveillance Registry and Vital Statistics Registry National Death Index 145,000 HIV+ people – 29,000 deaths Over time, as HIV+ persons were less likely to die of HIV-related causes, the proportion succumbing to CVD increased 70 60 50 40 30 20 10 0 70 60 50 40 30 20 10 0 2001-2002 2003-2004 2005-2006 2007-2008 2009-2010 2011-2012 Yr of Death PercentofAllDeaths 2001-2002 2003-2004 2005-2006 2007-2008 2009-2010 2011-2012 Calendar Yr CVDDeathsper1000 Persons(Age-Standardized) HIV-related, women HIV-related, men Malignant neoplasms, women Malignant neoplasms, men Major cardiovascular diseases, women Major cardiovascular diseases, men General population, men General population, women HIV diagnosed, men HIV diagnosed, women Leading Underlying Causes of Death for HIV-Diagnosed New Yorkers, by Proportion Age-Standardized CVD Mortality Rate, by HIV Diagnosis Status and Sex
- 17. clinicaloptions.com 25th Annual CCO HIV and Hepatitis C Symposium Risk Factors for CVD Events in HIV+ Pts Risk ratios for PI and boosted PI were estimated per additional yr, TC and HDL cholesterol per mmol/L higher, and systolic BP per 10 mmHg higher. Friis-Moller N, et al. European J of CV Prevention and Rehab. 2010;17:491-501. PI Boosted PI M ale Sex NRTI Age (per 5 Yrs O lder) Current Cigarette Sm oking Fam ily History of CVD Exsm oking Diabetes Total Cholesterol HDL Cholesterol Systolic BP Estimated Risk Ratio of CVD Events Among 22,625 HIV-Positive Pts (D:A:D Study) 3.5 3.0 2.5 2.0 1.5 1.0 0.5 0 1.00 1.08 1.63 1.70 1.42 1.43 2.35 1.27 1.92 1.21 0.67 1.05 EstimatedRiskRatio(95%CI) GreaterRisk
- 18. clinicaloptions.com 25th Annual CCO HIV and Hepatitis C Symposium Chronic Inflammation Is Associated With Increased Risk for Comorbidities in HIV+ Pts Deeks SG. Annu Rev Med. 2011;62:141-155. Untreated HIV Infection HIV replication ART Loss of immunoregulatory cells Loss of gut mucosal integrity and microbial translocation Decreased but persistent chronic inflammation, immune activation, elevated coagulation markers, microbial translocation, and increased risk of coinfection Increased incidence of comorbidities and clinical disease Traditional comorbidity risk factors, such as dyslipidemia, smoking, lipodystrophy, HTN, obesity, substance use
- 19. clinicaloptions.com 25th Annual CCO HIV and Hepatitis C Symposium 100 60 0 -40 80 40 -20 -60 20 *Adjusted for age, race, smoking, HCV infection, obesity, diabetes and MACS site. † Error bars represent 99.7% CIs, calculated with Bonferroni adjustment to maintain a family-wise error rate of 0.05. Filled markers represent statistical significance (P < .002). Biomarkers of Inflammation Are Elevated in HIV+ Pts Even on ART Wada NI, et al. AIDS. 2015;29:463-471. Adjusted Percentage Differences in Biomarkers of Inflammation and Immune Activation in HIV-Positive Pts and Uninfected Individuals*† (Multicenter AIDS Cohort Study, 1984-2009) Difference(%) CXC L10sC D 27IL-10sIL-2R α IL-2 sTN FR 2IFN -γ CXC L13TNF-α IL-12p70sIL-6RBAFFCC L2 IL-6sC D 14 G M -C SFC C L11 CR P IL-1β sG P130 IL-8CC L13CC L17CC L4 HIV suppressed relative to ART naive HIV suppressed relative to HIV uninfected
- 20. clinicaloptions.com 25th Annual CCO HIV and Hepatitis C Symposium Plasma IL-6 Levels Correlated With Incidence of Mortality SMART and ESPRIT 19,000 PYs of follow-up among 4304 PYs (median age: 42 yrs; median CD4: 526; 77% men) – 157 all-cause deaths – 117 non-AIDS deaths – 101 progressions to AIDS – 121 CVD – 99 NADM IL-6 (baseline) was found to be a stronger predictor of all cause mortality and many fatal non-AIDS events than the other 2 markers Adjustment attenuated the associations but IL-6 remained significant including for CVD Borges A, et al. CROI 2015. Abstract 761. 25 20 15 10 5 0 CrudeIncidenceRates per1000PYFU(95%CI) All- cause death Non-AIDS/ violent/ accidental death AIDS CVD NADM Crude Incidence Rates of Clinical Outcomes Across Biomarker Quartiles* Events, n IL-6 1st quartile 2nd quartile 3rd quartile 4th quartile 14 21 35 87 72 23 6 16 36 24 15 26 54 33 21 13 42 28 19 10 *Quartiles were defined differently in SMART and ESPRIT trials.
- 21. clinicaloptions.com 25th Annual CCO HIV and Hepatitis C Symposium Role of Monocytes in Atheromatous Plaque Development HIV activates monocytes and endothelial cells (in conjunction with proatherogenic lipids) – Increase monocyte transmigration – Increase uptake of oxLDL – Promote differentiation into foam cells – And contribute to atherosclerotic plaque formation Campbell J, et al AIDS. 2014;28:2175-2187.
- 22. clinicaloptions.com 25th Annual CCO HIV and Hepatitis C Symposium HIV Is Associated With Increased Arterial Inflammation HIV-positive individuals had signs of increased arterial inflammation compared with noninfected controls with similar cardiac risk factors Aortic inflammation in HIV-positive individuals was associated with the soluble inflammatory marker sCD163 Subramanian S et al. JAMA. 2012;308(4):379-386. Arterial Inflammation Was Significantly Correlated With sCD163 Levels 3.6 3.2 2.8 2.4 2.0 1.6 1.2 5 6 7 8 9 rho = 0.44, P = .03 Natural Log of sCD163 (ng/mL) AorticTarget-to- BackgroundRatio
- 23. clinicaloptions.com 25th Annual CCO HIV and Hepatitis C Symposium Pathogenesis of microbial translocation in HIV-positive pts Factors That Contribute to Chronic Immune Activation: Microbial Translocation Marchetti G, et al. Clin Microbiol Rev. 2013;26:2-18. HIV-Uninfected Pt HIV-Positive Pt
- 24. clinicaloptions.com 25th Annual CCO HIV and Hepatitis C Symposium A Marker of Microbial Translocation Declines During Suppressive ART but Does Not Normalize Progressors were chronically HIV-positive individuals and individuals with AIDS (< 200 CD4+ cells/mm3 ) Each group contains combined pt data from 2 unique cohorts, grouped according to HIV status and study design. Brenchley JM, et al. Nat Med. 2006;12:1365-1371. Progressors Untreated Progressors 48 Wks ART Uninfected 150 100 50 0 PlasmaLPS(pg/mL) P = .0107 P = .0026
- 25. clinicaloptions.com 25th Annual CCO HIV and Hepatitis C Symposium 7 clinical cohorts from NA-ACCORD (~ 20%) All ART users except those on ABC at study entry Only ART-naive persons observed to have initiated ART Awaiting more comprehensive analysis using marginal structural model with time updated data (if capable of doing with relatively small sample size) ABC and CV Disease: NA-ACCORD Palella F, et al. CROI 2015. Abstract 749LB. D:A:D replication Full Study Population Restricted Study Population 0 1.00 2.00 3.00 4.00 Adjusted HR
- 26. clinicaloptions.com 25th Annual CCO HIV and Hepatitis C Symposium NA-ACCORD: Risk Factors Associated With MI Palella F, et al. CROI 2015. Abstract 749LB. Recent ABC use Age < 40 (vs 50-59) yrs Age 40-49 (vs 50-59) yrs Age ≥ 60 (vs 50-59) yrs Smoking Hypertension Diabetes eGFR 30-59 (vs ≥ 60) mL/min/1.73m2 eGFR < 30 (vs ≥ 60) mL/min/1.73m2 High (≥ 240 vs < 240 mg/dL) total cholesterol Statin use High (≥ 300 vs < 300 mg/dL) triglycerides 0 8.006.004.002.00 Adjusted HR for MI Restricted study population Full study population
- 27. clinicaloptions.com 25th Annual CCO HIV and Hepatitis C Symposium D:A:D Renal Disease and CVD Ryom L, et al. CROI 2015. Abstract 742. 25 20 15 10 5 0 12 24 36 48 60 72 0 Mos After Baseline 24,605 9155 987 46 24,023 8907 937 39 22,376 8313 835 30 20,895 7681 760 26 18,979 6977 649 22 15,631 5989 524 13 13,001 5134 444 8 >90 >60-≤60 >30-≤60 ≤30 N Under Follow-up Kapian-Meier Progression to CVD by Confirmed Baseline eGFR PercentageWithCVD Baseline (confirmed) eGFR ≤30 >30-≤60 >60-≤90 >90
- 28. clinicaloptions.com 25th Annual CCO HIV and Hepatitis C Symposium Toxic Effects of Stress Helplessness and health – More helplessness > risk of CVD, DM, and depression Effects occur early and linger – Early hardships continue to be associated with illness later in life despite SE ascendancy Poverty by definition produces stress for which there are fewer resources to address problems Stress leads to biological changes (hypercortisolism, increases in markers of inflammation) – ? CNS changes such as reduced hippocampus volume?
- 29. clinicaloptions.com 25th Annual CCO HIV and Hepatitis C Symposium Take Homes This is complex Clear signals for role of discrimination in risk of CVD There are underlying psychosocial, genetic, and sex differences in one’s susceptibility to exposure to discrimination Depression is major co- occurrence Discrimination is a factor that needs to be included in CVD research Lewis T, et al. Annu Rev Clin Psychol. 2015;11:407-40.
- 30. clinicaloptions.com 25th Annual CCO HIV and Hepatitis C Symposium Chronic depressive symptoms Present Absent HIV Status Infected Uninfected Race Black Hispanic Whites and others BMI category Underweight or nomal BMI Overweight Obese Education Completed high school/GED Did not complete high school Household income level < $12,000/yr $12,000/yr Use of antidepressants Present Absent Illicit drug use Present Absent Alcohol use Present Absent 2.4 ± 0.6 0.1 ± 0.3 0.8 ± 0.3 -0.4 ± 0.6 1.3 ± 0.4 -0.5 ± 0.5 -0.3 ± 0.7 0.2 ± 0.5 -0.2 ± 0.6 1.5 ± 0.5 0.6 ± 0.4 0.4 ± 0.5 1.4 ± 0.4 -0.4 ± 0.4 1.7 ± 0.5 0.2 ± 0.3 1.0 ± 0.6 0.4 ± 0.3 -1.4 ± 0.8 0.8 ± 0.3 < .01 .07 .01 .23 .7 < .01 .02 .41 < .01 1.3 ± 0.6 -0.3 ± 0.4 0.3 ± 0.4 0.2 ± 0.6 0.9 ± 0.4 0.3 ± 0.6 0.2 ± 0.6 0.7 ± 0.5 0.02 ± 0.5 0.7 ± 0.5 0.4 ± 0.5 0.5 ± 0.5 0.6 ± 0.4 0.3 ± 0.5 0.6 ± 0.5 0.4 ± 0.4 1.0 ± 0.5 -0.03 ± 0.5 -0.4 ± 0.6 1.3 ± 0.4 < .01 .52 .34 .37 .86 .51 .72 .07 < .01 Variable Unadjusted Estimated FRS (Mean ± SE) P Value Adjusted* Estimated FRS P Value *Adjusted for initial visit Framingham risk score in addition to factors displayed in the table. Note: Bold values denote P < .01 Chronic Depressive Symptoms and Framingham Coronary Risk in HIV-Infected and Uninfected Women
- 31. clinicaloptions.com 25th Annual CCO HIV and Hepatitis C Symposium Demographics, CVD Risk Factors, and Other Important Covariates Models HIV-Specific Factors Models HR (95% CI) HR (95% CI) Any depressive disorder 1.31 (1.03-1.67) 1.31 (1.03-1.67) MDD 1.27 (0.98-1.64) 1.28 (0.99-1.65) Dysthymic disorder 1.46 (1.07-1.99) 1.47 (1.08-2.01) Association of Depressive Disorders With Incident AMI (separate models) 2.59 3.32 3.28 3.88 Unadjusted Incident AMI Rates per 1000 Person-Yrs by Depressive Disorder 5.0 4.0 3.0 2.0 1.0 No Depressive Disorder Any Depressive Disorder MDD Dysthymic Disorder Depressive Disorders Predicts Incident AMI in HIV+ Veterans: Veterans Aging Cohort Study
- 32. clinicaloptions.com 25th Annual CCO HIV and Hepatitis C Symposium Outline There are data suggesting increased risk of comorbidities, including CVD, in people with HIV CVD is clearly more common in people with HIV What is unclear is why – Possibilities – More risk factors (smoking, sedentariness, stress, depression) – HIV (via immune and inflammatory mechanisms, microbial translocation, CMV) – ART Assessing risk Approaches to prevention
- 33. clinicaloptions.com 25th Annual CCO HIV and Hepatitis C Symposium CVD Risk Prediction Equations Developed for the General Population Consistently Underestimate CVD Risk in HIV Pts An outpatient study cohort (n=2392) had similar findings of underestimated CVD risk (15% to 25%)[2] 1. Regan S, et al. CROI 2015. Abstract 751. 2. Thompson-Paul A, et al. CROI 2015. Abstract 747. 5-Yr Predicted Rate (%) Framingham Risk Score 5-YrEventRate(%) 5-YrEventRate(%) ACC/AHACVD Risk Calculator 5-Yr Predicted Rate (%) Observed Predicted Observed Predicted Observed vs Predicted 5-Yr CVD Outcomes in Partners Healthcare System HIV Longitudinal Cohort of 2270 HIV-Positive Pts[1] 25 20 15 10 5 0 25 20 15 10 5 0 < 2.5 2.5-4.9 5.0-7.4 7.5-9.9 < 2.5 2.5-4.9 5.0-7.4 7.5-9.9
- 34. clinicaloptions.com 25th Annual CCO HIV and Hepatitis C Symposium Outline There are data suggesting increased risk of comorbidities, including CVD, in people with HIV CVD is clearly more common in people with HIV What is unclear is why – Possibilities – More risk factors (smoking, sedentariness, stress, depression) – HIV (via immune and inflammatory mechanisms, microbial translocation, CMV) – ART Assessing risk Approaches to prevention
- 35. clinicaloptions.com 25th Annual CCO HIV and Hepatitis C Symposium Address: Reducing Traditional CVD Risk Factors Can Decrease Risk of CVD in Older HIV-Positive Pts Effective treatment of modifiable risk factors, such as smoking, cholesterol, and BP, can significantly reduce an individual’s CVD risk Model for Change in Relative Risk of CVD from Smoking Cessation, Reducing Cholesterol,* or Reducing Systolic BP† in a Cohort of 24,323 HIV-Positive Pts Without Prior CVD (D:A:D Study) *Reduced by 1 mmol/L. † Reduced by 10 mm Hg. Petoumenos K, et al. HIV Med. 2014;15:595-603. Reducing cholesterol Reducing systolic BP Smoking cessation 6 5 4 3 2 40 45 50 55 60 65 Age (Yrs) RelativeHazardof DevelopingCVD
- 36. clinicaloptions.com 25th Annual CCO HIV and Hepatitis C Symposium Rosuvastatin Effects on Carotid Intimal Thickness and Coronary Calcium Score Inclusion HIV-1 & ≥ 18 yrs On ART > 6 mos & HIV-1 RNA ≤ 1000 cps/mL Fasting LDL-C ≤ 130 mg/dL Heightened immune activation (CD8+CD38+DR + ≥ 19% or hsCRP ≥ 2 μg/mL) No CVD or diabetes No fragility fractures No immunomodulatory, bone tx, or hypolipemics Longenecker T, et al. CROI 2015. Abstract 137. Endpoints Cardiovascular – Carotid IMT (by US) – Coronary artery calcium score (by CT) CVD risk – Systemic & vascular inflammation – Lymphocyte & monocyte activation – Lipids – Insulin resistance – Body composition Rosuvastatin (n = 72) Placeobo (n = 75) SATURN-HIV Design Stratified by: PI vs not Osteopenia vs not CAC vs not Wk 96Wk 48Wk 0
- 37. clinicaloptions.com 25th Annual CCO HIV and Hepatitis C Symposium Rosuvastatin Effects on Carotid Intimal Thickness and Coronary Calcium Score As expected, LDL-C drop was greater in rosuvastatin arm 3 pts (2 on statin) with premature study drug discontinuation Longenecker T, et al. CROI 2015. Abstract 137. Mean Change in CIMT Mean Change in CAC in Those With BL Calcification P < .05 Statin Control 0.4 0.2 0 -0.2 -0.4 P < .05 Statin Control 300 200 100 0
- 38. clinicaloptions.com 25th Annual CCO HIV and Hepatitis C Symposium Randomized Trial of Statin Therapy and Coronary Plaque Progression Randomized 12-mo trial in HIV+ pts on stable ART with LDL-c < 130 and ≥ 1 coronary plaque by CTA – Atorvastatin 20 mg (↑ to 40 mg at 3 mos) (n = 19) vs – Placebo (n = 21) Statin therapy reduced progression of coronary plaques over a yr – Reduced overall plaque volume, including lipid-laden plaques – Plaque volume decreased 4.7% with atorva; increased 18.0% in the placebo arm – Reduced high-risk morphology plaques by 19% in atorva arm (20% increase in placebo arm) Statin therapy safe and well tolerated Lo J, et al. CROI 2015. Abstract 136.
- 39. clinicaloptions.com 25th Annual CCO HIV and Hepatitis C Symposium Contributing Factors to CVD in HIV+ Pts Crowe S. IAS 2014. WESY 0103. Traditional risk factors Traditional risk factors cART toxicitycART toxicity Coinfection with eg CMV Coinfection with eg CMV Monocyte and mϕ activation Monocyte and mϕ activation Other proinflammatory and procoagulant pathways Other proinflammatory and procoagulant pathways Cardiovascular diseaseCardiovascular disease Chronic inflammationChronic inflammation
- 40. Go Online for More CCO Coverage of HIV! Multimedia modules featuring video of expert faculty discussions of controversies and challenging cases Downloadable slidesets for your own study or presentations clinicaloptions.com/hiv
Notas del editor
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- ART, antiretroviral therapy; CMV, cytomegalovirus; CVD, cardiovascular disease. So I’m going to talk about a few different things, and really what I’m trying to do—if I had to give you a sort of abstract—is maybe challenge a little bit or pushback this idea, this concept that our patients are basically walking, ticking cardiovascular time bombs. And I think there is certainly a phenotype of individuals that are at increased risk for cardiovascular disease due to their HIV infection, but I’m not really sure how much that’s operative in the majority of our patients. So that’s sort of giving you a sense of where I’m going to go here. I could easily have come up here saying, “Oh my God, our patients have a lot of inflammation, they have a lot of vulnerable plaque in their coronary arteries, and we’ve got to do everything we can to protect them.” And there’s half a dozen people—who are really respectable and published and think about this—who could come up and do that. I’m going to be a little bit of a foil to that and intentionally try to probe that to see whether or not that’s really true. So I’m going to go over some of the data. I’m going to show you that cardiovascular disease is totally more common in people living with HIV, but we don’t know why. And I’ll go through some of the potential reasons for that. And then talk a little bit about practicalities which are great, that’s good, and it’s highfalutin, but how do we approach risk, and what do we do to prevent people from getting these things?
- ART, antiretroviral therapy; CMV, cytomegalovirus; CVD, cardiovascular disease. So the data are really clear. No matter how you cut it—and almost no matter where you look—people with HIV get heart attacks and strokes more often than people without HIV.
- AMI, acute myocardial infarction; CVD, cardiovascular disease; RR, relative risk. So here is a really good example from a very powerful study that looked at people in Boston who were attending 2 hospitals, thousands of patients with HIV, and over a million people without HIV and comparing rates of heart attacks. And as you can see—comparing the orange and blue bars—people with HIV had much higher rates of heart attacks in this case than people who didn’t. And as people age, you saw that splay. That more and more we saw excess cardiovascular disease in people with HIV compared to HIV negative. No debate here. I am telling you this is definitely the case. I’ll come back to the study. Let’s just call it the Boston Hospital study for reference.
- We have study from the MACS cohort, really important data. This shows in men—because MACS enrolls only men—with HIV and without HIV if you do really rigorous testing to see what the burden of coronary artery disease is you can see here that if you’re looking at vulnerable plaques (this is the plaque that’s not calcified, that’s softer, that’s more amenable to rupture and cause blockage and occlusion). We see, again, that if you compare HIV positive and HIV negative as people get older we see a little bit more vulnerable plaque in people with HIV. So comparing HIV positive and HIV negative, this is the kind of thing you see.
- So this leads to lots of concern. And there’s stuff in the literature and stuff in the media. And certainly my patients who wait in the waiting room—because I’m running behind—and open up a magazine see lots of stuff that says you’re going to get a heart attack, and what are you going to do about it? And people think about accelerated aging and excessive aging, and these are major concerns. And I think that’s a problem.
- ART, antiretroviral therapy; CMV, cytomegalovirus; CVD, cardiovascular disease. So we know that cardiovascular disease is clearly more common in people with HIV. What we don’t understand is why.
- ART, antiretroviral therapy; CMV, cytomegalovirus; CVD, cardiovascular disease. And so what are the possibilities? Well it could be—and this is what I’ll kind of present to you—is that for one thing we do know that people living with HIV have more risk factors for cardiovascular disease, and that’s a no brainer. So we talked before on the panel about confounding and choose your confounders. In HIV and cardiovascular disease, the confounding is somewhat obvious, but I’ll also describe some less obvious confounding. So we know that smoking and other risk factors are more prevalent in people with HIV. And then, there’s this whole issue of what’s the role of the virus itself? We know that the virus (in some of the studies that have been done) can in some people be somewhat proinflammatory. That we see markers of inflammation and immune activation that are increased in people—some people with HIV—and is that a driver? So let’s talk a little bit about that. And then, what about the role of ART? And we’ve gone back and forth about abacavir, for instance, and we can talk a little bit more about that.
- AMI, acute myocardial infarction; CVD, cardiovascular disease; RR, relative risk. So back to the Boston study. So the Boston Hospital study shows this difference. This difference is key, and this difference is really what most of my talk is about. I want to understand this difference. So if there’s all these confounders, if I’m telling you there’s more people who smoke than people in the blue bars, and there’s more people who do crack cocaine, and there’s more people who may be African American and who have like lower HDL and stuff like that. It makes sense that there’s going to be a difference.
- CVD, cardiovascular disease. So how much of this difference—this differential that I think is really key for us to understand—is driven by HIV and HIV-related factors vs traditional factors? So one thing it’s clearly there, higher risk, and we have to understand that. What I don’t understand is the risk, you know, built upon the traditional factors how much is this excess risk due to HIV-related factors big, or how much of it is kind of little? And the size of his difference is what I’m very interested in. Because then I can tell that patient that you know what the majority of your burden for cardiovascular disease is mutable. We can change this; we can work on this. But if it’s really being driven by a retrovirus that’s replicating at very low level or whose very presence is eliciting an inflammatory response that I can’t do anything about that’s a very different story. Because right now we don’t know, and now a lot of my patients are worried. And my gut feeling is that they’re overly worried. And I think that a lot of what we’re seeing is explained by things that have nothing to do with HIV. So not necessarily a popular opinion.
- So let’s go back to the Boston study, the Boston Hospital study. I searched in the PDF for the word “smoking.” And you find it very rarely and only basically to say we don’t have smoking data. So it’s very hard to compare when you don’t have smoking. Because if you take out smoking, how much of that difference is left? And again, I’m not saying it’s going to obliterate that difference, but that difference is what we have to understand when we look at these data. Because those are scary differences. But we have to put it in context.
- CAC, coronary artery calcium; CAD, cardiovascular disease; CT, computed tomography; PR, prevalence ratio Even in the coronary artery study from the MACS, I really like that study, and I think it shows us a few different things. But one thing it taught me is the way that people analyze these studies. Again, choose your confounders. In this case, this is the Annals of Internal Medicine—great journal—they showed 2 different models: one looking at adjusting for the confounders (what they call minimally). Minimally is what most people do. You take 5 or 6 traditional cardiovascular risk factors, and you “adjust for them statistically” and see if the differences that you’re seeing between the 2 populations still holds up. So they did that and significant results. Then they said, “You know what we did?” We did an additional adjustment even beyond those factors to add other factors. And what you generally see is an attenuation of the strength of the association. That’s very important to me because it shows that as you continue to add on confounders the association between these things weakens. It concerns me because what if you added on even more confounders, including those that are kind of hard to measure, which I’ll talk about in a second.
- ART, antiretroviral therapy; CVD, cardiovascular disease; MI, myocardial infarction. Let’s look at some of the data. So these are nice data from the Kaiser Permanente group. So I always qualify because some of the studies I show you, it depends where they’re done. So like the D:A:D, we talk about D:A:D, and it’s done in Europe. And Europe is different than the United States, so I always qualify that the Kaiser Permanente they are done in California, and that may be different, especially if I’m talking to people in New York because people in California may be somewhat different. But these are Kaiser Permanente data, and they’re looking at people, of course, who are members who are positive and negative. And over time what’s been seen is that the rates of cardiovascular disease—whether MI or stroke—have been coming down in people with HIV and approximating those people who are HIV negative. So again, the fear factor that our patients and we have regarding cardiovascular disease is not always borne out completely by the data or can be explained by very, very traditional and explainable things. And that’s basically the bottom line here. So over time, we see this equilibration, and the investigators point out reasonably that this might be more aggressive prevention, so we’re using statins more, we’re treating people earlier with HIV therapies, and I think that is protective against heart disease in people with HIV. So there’s lots of reasons that can be explained that it’s going down.
- CVD, cardiovascular disease. These are data from New York. These are mortality data, so this is looking at death rates among New Yorkers. So many of you eventually will contribute to this database if you don’t move away. So there is this database of mortality in New York City, and it was compared against sort of national data and also looking at people with HIV and the HIV registry. And what you can kind of see maybe (maybe you see better than I do) is that generally over time what we’re seeing is that cardiovascular disease, as a cause of death, has gone down, including among people with HIV. Now, the proportion of people with HIV who are dying of cardiovascular disease has increased because they’re not dying of cryptococcal meningitis or PCP, thanks to you. So if you’re not going to die from that, you’ve got to die of something, right? And cardiovascular disease starts to rise up along with malignancy, and that’s what you see. But overall, what we’re seeing is a decreased rate of cardiovascular disease among people living with HIV, not an increased rate. You got it.
- BP, blood pressure; CVD, cardiovascular disease; HDL, high density lipoprotein; TC, total cholesterol. When we look at cardiovascular risk factors—these are data from the D:A:D, but I think they were operative for us too—the majority of the drivers are not HIV related. So whether you’re talking about basically abacavir or boosted PIs (PIs in general), it’s the traditional things that we see are really driving this, including increasingly understanding kidney disease, which is very prevalent, especially in the United States, much more so than in the D:A:D cohort is a major driver.
- ART, antiretroviral therapy; HTN, hypertension. Steve Deeks and others have really conceptualized this in a way that I like in thinking about what are the different contributors. And the whole thing of well untreated HIV causes this axis of evil. So untreated HIV leads to replication, replication leads to immune activation, immune activation leads to the secretion of IL-6 and CRP and other things that outside of HIV we know can cause bad things to happen to our organ systems. There may be also breakdown of the gut, and that’s where I think is one of most compelling sort of things that may be going on with HIV where we have loss of integrity and microbial translocation that elicits its own responses, and we know in general health that’s not a good thing. And then there’s the sort of ART effect, and what happens once you reduce that immune activation there’s still some residual stuff going on that isn’t completely corrected. Add on the traditional risk factors, and you’ve got a prescription for disaster. Again, this makes sense as thinking about this if you take it from the bottom up. Here’s the problem: What are the causes? It doesn’t really help us understand completely does this happen to everyone? What is going on here? Really it’s very hard to find good data, and it’s very hard to find data that are robust and that use an appropriate control group. And I would actually say to you it’s almost impossible to find appropriate control group. Even within the MACS cohort—large, several thousand cohort of men, men who have sex with men, living in the same cities—there’s differences between the men who are positive and the men who are negative demographically, and I would say in other life experiences. In the VA, the same sort of thing. So we see that even hepatitis C, some race, some smoking are different between people with HIV. The neurologists have seen this because when they look at controls and they look at HIV-positive people and they try to look at neurocognitive outcomes, they realize they have to correct for head trauma. Because more people with HIV have had head trauma than controls. So unless we get a large cohort of identical twins—where one person is positive and one person is negative—I think it’s going to be very challenging to come up with appropriate controls to answer some of these very, very, very specific questions.
- ART, antiretroviral therapy; HCV, hepatitis C virus. In this study, it helps us to get a little bit better sense of it; it’s a little bit confusing the way this is done. But in the orange boxes, what you see is for different markers of immune activation/inflammation—comparing HIV-positive people who are suppressed on their HIV therapy relative to people who are not on HIV therapy but are infected—you can see by and large that there’s less inflammation when you’re on HIV therapy. The blue boxes show pretty different sort of curve or a line; these are HIV suppressed people relative to uninfected people. And here I’d say by and large there are some outliers but very different sort of story here. For me, that’s what I’m trying to understand. Again, I think for suppressed patients whose virus is under control how much excess risk they have is something that is sort of like sand through your fingers; it’s very hard to understand and grasp.
- CVD, cardiovascular disease; NADM, non-AIDS-defining malignancies; PY, patient-years; PYFU, patient-years of follow-up. And we’ve seen data like this. Again, your first knee-jerk response when you see things like this is like, “Oh my God.” So here are data from SMART and ESPRIT, and you’ve seen some of this before that shows look at this cardiovascular disease. If you look at IL-6 levels in people in the study and look for risk of bad things happening to them, what happens over time? And not surprisingly, people who have higher levels of these inflammatory markers, including IL-6, have higher risk of cardiovascular disease. Let’s do this. As you’re walking out, we’re going to draw a little bit of blood, and we’re going to check IL-6 levels. And we’re going to follow all of you for the next 15 years for that mortality registry. Those of you who have higher IL-6 levels—regardless of your HIV status—you’re going to likely have worse outcomes than those of us who have lower IL-6 levels. So this is not specific to HIV. I think that there’s going to always be a curve (some sort of bell-shaped curve) where people have higher levels of inflammatory markers due to your lifestyle, due to bad teeth, due to bad genetics are going to have worse outcomes. This doesn’t tell us what is causing the IL-6 level to be the way it is.
- oxLDL, oxidized LDL. Again, this whole concept—I think it’s really important to understand this idea that there’s monocytes, and the monocytes are activated in HIV. There’s some really great work coming out from Peter Hunt in California that show us that the monocyte may be the active cell here, and this makes a lot of sense. But again, we saw this back 15 years ago, didn’t we, when we were talking about adipocytes. Many of us were worried about lipodystrophy, and you can see diagrams that are as elegant as this one that showed us that fat cells were active, protease inhibitors acted on the fat cells, or NRTIs (the thiamine analogue) acting on the fat cells in all sorts of ways. But yet not every single patient who came in who started on a PI had VAT (visceral adipose tissue) that exploded and came in with a big belly. Some did and that’s a phenotype that’s important to identify. I would pose it to you that there are some people who don’t handle HIV as well whose immune system is activated, who do have inflammatory markers that are elevated and get cardiovascular disease. I again just don’t know if it’s a lot or a little. And I think there’s a specific phenotype that will get this, but it’s not the vast majority.
- The microbial translocation thing is one of the parts that I find most fascinating, as I mentioned, and I think has to be teased out further. We’re just starting to understand this. You know that HIV is a gut-associated virus, and it was one of the first identified symptoms of acute HIV, and later on chronic HIV was loss of gut integrity and diarrhea, gay bowel syndrome for those of you who remember. And we’re understanding more and more that the lymphoid tissue is important in the gut, and that this breakdown of gut integrity may lead to proinflammatory changes, again, in some people, maybe not all. This is going to be something that you’re going to hear more and more about.
- ART, antiretroviral therapy; LPS, lipopolysaccharide . And there’s some evidence, again, looking at different types of people—those who are suppressed vs who are not suppressed, looking at uninfected—showing that there may be markers of microbial translocation that is higher in aggregate in people with HIV, even when they’re suppressed. But again, what I love about this slide is it shows that point, but it also shows the dots are all over the place. While the lines are different, this gets back down to the phenotype. Why are some people at the very, very bottom regardless of uncontrolled HIV? And why are some people outliers at the top?
- ABC, abacavir; ART, antiretroviral therapy. So abacavir and cardiovascular disease and NA-ACCORD. Just to put some context into this and why we mention NA-ACCORD. We mention NA-ACCORD for 2 reasons. One is Joel showed really nicely that there is this equipoise; that some studies show that there’s association with abacavir. And then we had other studies, including the FDA analysis, that didn’t really show that there was an effect. In fact, some cohort studies didn’t show that there was an association between abacavir and cardiovascular disease. So people are very hopeful that the NA-ACCORD, which is a very robust, American and Canadian based study (so more real life to us) would address this question, and we knew that they were going to do it. So that was one thing, and this was going to be sort of the tiebreaker. Then, it was presented at CROI, which makes it even more important, because if you just publish your data, no one sees it. But if you get to present it at a big conference where everyone is, it gets much more attention. Unfortunately, I think that the results were a little half-baked, and I don’t mean it in like sort of a crazy way. I mean like it wasn’t soup yet; it wasn’t completely there. What we saw was that they probably didn’t help us understand one way or another whether or not the needle should go more towards the yes or no, and it enriched more of the “I’m not sure” group. So you’re perfectly right where everyone else is. The reason for that is that they cut the data a few different ways that shows a few things. One thing that is not on this slide—and again, was a point that was made before—is that when you look at the people in NA-ACCORD who got abacavir it was incredibly enriched with people with cardiovascular disease risks and other risks (risks for AIDS progression). So more smokers, more people with renal disease, African Americans, people with hypertension, people with hepatitis C and low CD4 cell counts were more likely to get abacavir. Talk about confounding. There may be statisticians in the room who understand this much better than I do. But how you really can adjust completely for some of this, I think, is a challenge.
- ABC, abacavir; eGFR, estimated glomerular filtration rate; MI, myocardial infarction. Those are just the things that we know about that we measure. There may be things we don’t measure or don’t know about that can also be a confounder that wouldn’t be taken into account. So it shows that this is really ripe for a randomized clinical trial, but no one is going to do that. So not to get into the details of this, but the study was analyzed in a few different ways. One basically replicating the original D:A:D methodology and found very, very similar results. And then, looking at a full study population, and then, only those who were treatment naive and then initiated ART during the study, with abacavir or not. And the data were kind of a little bit all over the place and had some limitations in their ability to adjust for things over time. So I don’t think the NA-ACCORD data really have helped us understand this completely. I think that there’s more analyses that will come out of this that will probably help a little bit. What I was actually struck by more than anything else was in this analysis they did look at these various covariates and risk factors, and kidney disease was way, way, way out there as a factor burying any effect of abacavir. So having even moderate kidney dysfunction—in the 30-60 creatinine clearance range—puts you at much higher risk for cardiovascular disease then whether or not you took abacavir. And that’s demonstrated here. You might not be able to see it as clearly, but the far right lines, that’s GFR. And I don’t think we’ve appreciated that as much as we need to. If you want to look for people who are at increased risk for cardiovascular disease, look at their creatinine clearance.
- CVD, cardiovascular disease; eGFR, estimated glomerular filtration rate. D:A:D showed the same sort of thing in a Kaplan-Meier curve showing risk of development of cardiovascular disease based upon stratification by creatinine clearance estimation.
- CNS, central nervous system; CVD, cardiovascular disease. So I alluded to this a few times, and I don’t want to get deep into the weeds on this, but I do think that there’s a measured confounding, and I do think there’s difference between people largely who are living with HIV and those who are not living with HIV, even among similar populations of gay men or injection drug users or women. And I think a lot of this has to do with some of the things that may be sort of wedded to living with HIV. And I think this includes stress and depression. I think it includes discrimination. And there’s a growing body of evidence that is also flawed—like some of the data that I’ve talked about with some of the same methodologic sort of limitations—that shows that living in America in certain ways can be very tough for people. And that’s why I like to say when there’s a European cohort vs American cohort because I think living in Berlin is different than living in Baltimore, and especially if you’re black. So I think there’s lots of things that affect people’s health that we don’t measure very well. Poverty is clearly associated with higher levels of cortisol; having a traumatic or dangerous childhood has ramifications for your health that is lasting and that we have a hard time measuring or understanding. So there’s growing data regarding this. There has been pretty good analyses looking at self-reported experiences in discrimination in cardiovascular disease by Tené Lewis at Yale that shows that there is an association, as one would expect. Again, there’s some confounding here that we have to think about, but there is that.
- CVD, cardiovascular disease.
- FRS, Framingham risk score; SE, standard error. And there’s even some data—and I’m not showing this so that you can read from the back of the room—within HIV (and this is from the WHIS cohort) that showed when you look at different variables that are associated with coronary risk and cardiovascular disease, chronic depression was one of the greatest, even more so than HIV status. So chronic depressive symptoms and Framingham coronary risk in positive and negative women (and we see this depressive symptomatology) has an effect on people and their well-being, which I don’t think would be too surprising to most of us.
- AMI, acute myocardial infarction; CVD, cardiovascular disease; MDD, major depressive disorder. There are other data from the VA (that I’m not going to go over) that showed the same sort of thing. Again, depressive symptoms and acute MI are linked in people with more dysthymia or at more at risk for having cardiovascular disease.
- ART, antiretroviral therapy; CMV, cytomegalovirus; CVD, cardiovascular disease. And so, putting it all together I just think that it’s very, very multifaceted—there’s lots of factors. And just to blame it all on HIV and immune activation and inflammation I think doesn’t explain the picture and I think doesn’t complete it the way that it needs to be completed. So I think this is very, very unclear. I think we have to have more analysis and more thought about this and include more of the things that aren’t measured typically in some of our studies. As we correct for those, my prediction is the fingers will get closer together rather than further apart when we think about what’s above and beyond traditional risk factors that is driving cardiovascular disease in our patients.
- ACC, American College of Cardiology; AHA, American Heart Association; CVD, cardiovascular disease. So the data show that pretty much whether or not you’re looking at Framingham risk or the American College of Cardiology risk calculator, look at a cohort of people and you look at the actual heart attacks that occur or cardiovascular disease that occurs, and what you would predict based upon the data available that could be fed into the calculator—pretty much the calculators undercall these events. So that’s pretty important because it means that when we do these calculators, we might be ball parking a little bit low for our patients. Some people could look at this and say, “Well there you go, that’s your fingers, that’s the excess risk that occurs above and beyond.” It could be, although there are some other analyses that show if you even use this in HIV-negative people, let’s say in the VA, you underanalyze it. We’ve seen that for bone and we’ve seen that some for cardiovascular risk calculators. But overall, I think it’s fair to say that our risk calculators for our population probably underestimate risk to some degree. And so there’s a little bit of a fudge factor that we have to think about. A question that comes up all of the time is well what are you using? I used to use the Framingham risk; it’s so easy, and basically it’s driven a lot by the major things we care about. What about the new risk calculator? I would suggest people start to adopt it. So I know it’s been a little controversial, and some of you may be primary care providers and know a lot, lot more than I know about this or ever will know about this. But from what I understand and from what I can appreciate, what I like about the new calculator is it really is looking at cardiovascular risk totality rather than just MI. I like that it’s kind of thinking about things with more factors plugged into it. As you know—so those of you who are not familiar with it—it looks at a risk of 7.5% in the next 10 years of having a cardiovascular disease event as significant. And significant enough to motivate you to do an intervention like a statin. So it kind of lowers the bar for statin initiation, especially in higher-risk people. And that—if you buy into the statin thing—makes sense. So I kind of like it better. It’s a little bit more cumbersome to use, but you can do it on your phone or you can do it online. And I think it actually works probably a little bit better, and it’s more appropriate for our population. But I understand there’s some controversy about it, and some people may not like it as much. But I think it probably is appropriate.
- ART, antiretroviral therapy; CMV, cytomegalovirus; CVD, cardiovascular disease.
- BP, blood pressure; CVD, cardiovascular disease. I think that for most of our patients, we know that just traditional approaches to cardiovascular disease risk makes sense, and there’s modeling like this that showed just doing the big ticket items—getting people to stop smoking. I don’t know (and this is something that again has not been studied) what smoking marijuana does. It’s not collected in most of these studies. Cocaine and crack use is not collected in most of these studies—again, unmeasured confounders. One of the studies that found an association between abacavir and cardiovascular disease became null once they corrected for substance abuse. So again, it would be nice to look at those things. But lowering LDL makes sense, and I think that is part of it but only after some of these other things have been tried. I don’t think I would use statins willy nilly in people who don’t have a good indication for it.
- ART, antiretroviral therapy; CT, computed tomography; CVD, cardiovascular disease; hsCRP, high-sensitivity C-reactive protein; IMT, intima media thickness; LDL-C, low density lipoprotein cholesterol; tx, treatment. This has been looked at a little bit in a couple of studies; they’re small, but this is what we’ve got. It’s tantalizing. In one study that was just presented at CROI looking at rosuvastatin vs placebo, only about 150 people in this study. And these were not people who needed to be on a statin for a different reason.
- BL, baseline; CAC, coronary artery calcium score; CIMT, carotid intima media thickness; LDL-C, low density lipoprotein cholesterol. When you look at change in carotid intimal thickness, which is a marker of burden of cardiovascular disease, there was a modest but a statistical difference between the 2 arms showing rosuvastatin did have a benefit. When you look at calcification of coronary arteries, there wasn’t a difference between the 2 arms. Only if you looked at the people who had some calcification to start with did we see that a statin was beneficial in that it seemed to arrest progression.
- ART, antiretroviral therapy; CTA, computed tomography angiography LDL-c, low density lipoprotein cholesterol. Another study found the same sort of thing; again, very small, people who didn’t need to be on a statin for typical reasons for indication. It’s the people who started with coronary artery plaques that we saw that a statin—in this case, atorvastatin—was able to decrease the volume of the plaque or progression compared to some progression in the controls who didn’t get the statin. So statin may be very beneficial for people who already have the thing that we’re worried about. Whether or not it’s going to prevent these things is unclear. The AIDS Clinical Trials Group is launching a very ambitious, very important study that’s going to look at giving pitavastatin vs placebo to people with HIV who do not have an indication for a statin and follow actual clinical outcomes. So I think that will address the question, and there’ll be a lot of subsidiary studies that will help us understand more about the benefits of this kind of approach in the antiinflammatory properties.
- CVD, cardiovascular disease. So I’m going to end with this. So we’ve seen this before, and it’s sort of like the Deeks’ thing where we have the virus, we have traditional risk factors, we have ART, maybe coinfections, which I didn’t talk about because we’re still not sure about what that means. And this all goes down this common pathway, this pathogenic pathway. I like thinking about it this way, but what this doesn’t give us is what’s the relative contributions. And maybe it’s sort of traditional risk factors play a bigger role, and maybe there is (for purposes of argument) something going on with the virus in that it elicits this response. But ART isn’t really part of it. So again, I think we have to think about this in proportionality that these typical ways of thinking about things don’t provide us, and that’s something I hope you all will continue to think about too.