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HIV and Aging: a Time for a New Paradigm

HIV and Aging: a Time for a New Paradigm. Amy C. Justice, MD, MSCE, PhD Professor, Yale University Section Chief, General Internal Medicine VA Connecticut Healthcare System. Outline. Epidemiology, demography of aging with HIV Describe Veterans Aging Cohort Study (VACS)

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HIV and Aging: a Time for a New Paradigm

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  1. HIV and Aging: aTime for a New Paradigm Amy C. Justice, MD, MSCE, PhD Professor, Yale University Section Chief, General Internal Medicine VA Connecticut Healthcare System

  2. Outline • Epidemiology, demography of aging with HIV • Describe Veterans Aging Cohort Study (VACS) • HIV Associated Non AIDS (HANA) Conditions • VACS Risk Index • A new approach to comparative effectiveness and personalized medicine

  3. Antiretroviral Therapy in 2011 • Once a day pill well tolerated and achieves viral suppression in 84%* • Median CD4 counts increasing • Viral load declining • AIDS defining events are rare *Gallent JE. et al. Tenofavir DF, Emtricitabine, and Efavirenz vs. Zidovudine, Lamivudine, and Efavirenz for HIV. NEJM 2006 354:251-60.**McKinnell JA. et al ARV Prescribing Patterns in Treatment-Naïve Patients in the United States. AIDS Patient Care and STDs 2010 24:79-85

  4. More People Living with HIV Infection Every Year (+38K/yr*) CDC surveillance data Each year: 56K new infections-18K deaths=38K*

  5. Projected *Data from 2008, onward projected based on 2001-2007 trends (calculated by author), 2001-2007 data from CDC Surveillance Reports 2007. New York and San Francisco data from their Departments of Public Health

  6. >50% of Deaths Attributed to Non-AIDS Events Cumulative Mortality by COD Among Those on cART (1996-2006) ART-CC, CID 2010: 1387-1396

  7. Prevalence and Incidence Are Linked

  8. AIDS Events Increasingly Rare ART-CC, Archives Int Med 2005: 165 416-423

  9. AIDS Events Variably Associated with CD4 and Survival By Median (IQR) CD4 By Relative Hazard of Death ART-CC, CID 2009;48:1138-51

  10. Life Expectancy is not “Normal” Risk-adjusted HIV negative Mean age seroconversion of 33 years Optimal care HIV postive Losina et al CID 2009

  11. Death Rate Disparities by HIV, Race/Ethnicity and Age HIV Epidemiology & Field Services Semiannual Report, NYCDOH. April 2010

  12. Delayed Presentation By Age (NA ACCORD) Altoff K. et al. In press JAIDS

  13. Major Observations • On ART, HIV is a complex chronic disease, not unlike insulin dependent diabetes or cancer in partial remission • Annual new HIV infections exceed deaths; the population on ART is rapidly growing and aging • We need an effective and efficient approach to caring for these individuals

  14. VACS Long Term Objectives Fully characterize treated HIV infection as a model of complex chronic disease with a dominant index condition Use this model, risk stratification, and electronic medical records systems to revolutionize health care

  15. VACS 8 • SUBJECTS: 3,640 HIV infected; 3,640 uninfected • Group matched: age, race/ethnicity, and site • SITES: Manhattan, Bronx, Washington DC, Baltimore, Pittsburgh, Atlanta, Houston, Los Angeles • BASELINE: 2002 (8 years)

  16. VACS Virtual Cohort • Subjects • 40,594 HIV infected Veterans • 81,188 Age, Race, Region Matched 2:1 • Scope • 1998 to present • Baseline • HIV infected patients at initiation of HIV care • Controls selected and followed in same year

  17. Arbitrated Clinical Events in VACS 8 • ART Initiation (Complete, paper in process) • Symptomatic Cirrhosis (Decompensated Liver Disease—paper in press) • Major Cancers (Nearly Complete) • Myocardial Infarction (Underway) • Stroke (Planned) • COPD and Pneumonia (Planned)

  18. HIV Associated Non AIDS Conditions (HANA)

  19. Non AIDS Events Are Associated with HIV Disease Progression* *More AIDS and “Non-AIDS” Events Among Rx. Sparing Arm (HR 1.7 in SMART) NEJM 2006;355:2283-96

  20. Definition: HIV Associated Non AIDS Conditions (HANA) • After adjustment for established risk factors, association with HIV remains • Compare to demographically and behaviorally similar uninfected controls • Weaker (<2 fold) associations may be due to inadequate adjustment for risk factors • May be due to HIV, ART or both

  21. Freiberg M.S. et al. HIV is Associated with Clinically Confirmed MI. CROI 2011 Abstract# W-176

  22. Fragility Fractures HIV+/- (n= 125,259) Womack J. et al. PLoS ONE February 2011 | Volume 6 | Issue 2 | e17217

  23. Possible HANA • Targeted Disease • Vascular: Myocardial Infarction, Thrombosis, and Stroke • Bone: Osteoporosis and Avascular Necrosis • Cancer: “infectious” e.g. Anal and “non infectious” e.g. Lung • Lung: pneumonia and COPD • Neurological: Peripheral neuropathy, ?dementia • General Organ Injury • Liver Fibrosis: risk of, progression to, cirrhosis and hepatoma • Hematologic Disease: anemia, thrombocytopenia • Decreased Renal Function: most is not HIVAN

  24. General Observations on HANA • Multiple interacting HIV and non HIV causes • HIV typically not the most influential risk factor • Incidence of event different from relative risk • Adjusted relative risk HIV+/- highly variable • Association with CD4 variable • Degree to which these occur “prematurely” difficult to quantify • Competing risk of death is changing and unmasking risk associated with HIV

  25. Warning! • All these conditions have multiple, interacting, causes among HIV+/- • The mix of causes driving these events among HIV+ may differ from HIV- • Until we understand this mix, we must focus on what drives health outcomes in our patients

  26. An index composed of routinely collected laboratory values that accurately predicts all cause mortality among those with HIV infection Veterans Aging Cohort Study Risk Index (VACS Index) Justice, AC. et. al, HIV Med. 2010 Feb;11(2):143-51. Epub 2009 Sep 14.

  27. Rationale for Multivariable Risk Index • A single, summary measure of disease • Identifies important thresholds for lab tests • Resolves conflicting results • Informs prioritization • Has major statistical advantages • Decreased measurement error • Each person has a measurable outcome at any time point Justice AC. HIV and aging: time for a new paradigm. Curr HIV/AIDS Rep. 2010 May;7(2):69-76.

  28. Veterans Aging Cohort Study Risk Index (VACS Index) • Composed of age and laboratory tests currently recommended for clinical management • HIV Biomarkers: HIV-1 RNA and CD4 Count • “non HIV Biomarkers”: Hemoglobin, hepatitis C, composite markers for liver and renal injury • Developed in US veterans, validated in Europe and North America

  29. AGE * AST FIB 4 = PLT * sqrt(ALT ) -1.154 -0.203 eGFR = 186.3 * CREAT * AGE * FEM_VAL * BLACK_VAL FEM_VAL = 0.742 if female, 1 if male BLACK_VAL = 1.21 if black, 1 otherwise Composite Biomarkers 32

  30. VACS Index Thresholds and Weights Age HIV Specific Biomarkers Biomarkers of General Organ System Injury Tate J. et al. IDSA 2010 Vancouver, BC October 21-24th. Poster 1136

  31. FIB 4 Values by Age, ALT, and AST(Platelets 100k) FIB 4 >3.25 is worth 25 points, 1.45-3.25 is worth 6 points

  32. VACS Index Highly Predictive of Long Term (5 Year) All Cause Mortality Aggregated Scores Individual Scores Justice, AC. et. al, HIV Med. 2010 Feb;11(2):143-51. Epub 2009 Sep 14. Justice AC. HIV and Aging: Time for a New Paradigm. Curr HIV/AIDS Rep. 2010 May;7(2):69-76

  33. Discrimination of VACS vs. Restricted Index Justice AC. et al. A Prognostic Index for those Aging with HIV. CROI 2011 Poster # 793

  34. Calibration of VACS vs. Restricted Index (5 Year Mortality) Justice AC. et al. A Prognostic Index for those Aging with HIV. CROI 2011 Poster # 793

  35. The Holy Grail: Surrogate Endpoint • Must be an accurate predictor of target outcome • Respond to changes in risk of the outcome due to treatment • Detect differences in outcome due to treatment among different treatment arms

  36. VACS Index Response to 1st Year of cART (+/- 80% adherence) Solid lines indicate >80% adherence

  37. VACS Index Correlated with Biomarkers of Inflammation Justice AC et al,“Biomarkers of Inflammation, Coagulation, and Monocyte Activation are Strongly Associated with the VACS Index among Veterans on cART” CROI 2011 Poster # 796

  38. VACS Index Summary • Is associated with markers of inflammation • Accurately predicts mortality among HIV patients in the US and Europe • Responds to changes in risk associated with ART initiation • Will likely prove a more reliable surrogate endpoint than any single biomarker

  39. Why Is This Important? • Uses lab tests currently part of routine care • Identifies modifiable risk at earlier thresholds • Incorporates age, and effects of HANA and toxicity • Computation easy, can be included in lab reports and available through websites/apps • Offers approach to personalizing and prioritizing care that goes beyond CD4 count and HIV-1 RNA

  40. Example: Framingham Index • Assigns points based on 6 factors (5 modifiable) • Estimates risk of MI or death over the next 5-10 years ranging from 1% to >56% • Assumes that change in risk due to smoking cessation is same as never having smoked, etc. D’Agostino RB. Et al. Validation of the Framingham Coronary Heart Disease Prediction Scores: Results of a Multiple Ethnic Groups Investigation. JAMA 2001;286:180-187

  41. Framingham Risk Assessment Results View: http://hp2010.nhlbihin.net/atpiii/calculator.asp?usertype=prof

  42. Uses of Framingham Index • Assesses relative importance of CHD risk for individual patients • Quantifies absolute level of CHD risk for individual patients • Allows clinicians and patients to match the level of treatment to the level of risk • CHD guidelines are based on these estimates D’Agostino RB. Et al. Validation of the Framingham Coronary Heart Disease Prediction Scores: Results of a Multiple Ethnic Groups Investigation. JAMA 2001;286:180-187

  43. Case Example 50 year old, HIV infected male on ART with an HIV-1 RNA<500, CD4 count 500, normal hemoglobin, creatinine, AST, ALT, and platelets. HCV negative. score 8; expected mortality* 4% • CD4 count 400 cells/mm3, score 18; expected mortality* 9% • Hemoglobin 12-13.9 g/dL, score 28; expected mortality* 15% • Hemoglobin 10-11.9 g/dL, score 40; expected mortality* 24% *In all cases referring to estimated 5 year mortality risk.

  44. Risk and Revolution of Care

  45. In Development: Interpretation Your score is XX. Among 100 veterans in VA care with HIV infection with this score, we would expect that YY would be alive at five years and ZZ would have died. The figures in grey represent those expected to live 5 years and the figures in black represent those expected to have died.

  46. Counseling (Hypothetical) • Based on your drinking pattern and use of tobacco, you could reduce your 5 year risk of mortality to XX if you stopped both • If you stop smoking, your risk will be YY and if you stop drinking your risk will be XX • Websites where you can learn more about • How to stop drinking include XX • How to stop smoking include XX • If you would like to help us improve this site click here

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