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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

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

  • 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
antiretroviral therapy in 2011
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

more people living with hiv infection every year 38k yr
More People Living with HIV Infection Every Year (+38K/yr*)

CDC surveillance data

Each year: 56K new infections-18K deaths=38K*



*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

50 of deaths attributed to non aids events
>50% of Deaths Attributed to Non-AIDS Events

Cumulative Mortality by COD Among Those on cART (1996-2006) ART-CC, CID 2010: 1387-1396

aids events increasingly rare
AIDS Events Increasingly Rare

ART-CC, Archives Int Med 2005: 165 416-423

aids events variably associated with cd4 and survival
AIDS Events Variably Associated with CD4 and Survival

By Median (IQR) CD4

By Relative Hazard of Death

ART-CC, CID 2009;48:1138-51


Life Expectancy is not “Normal”

Risk-adjusted HIV negative

Mean age seroconversion of 33 years

Optimal care HIV postive

Losina et al CID 2009

death rate disparities by hiv race ethnicity and age
Death Rate Disparities by HIV, Race/Ethnicity and Age

HIV Epidemiology & Field Services Semiannual Report, NYCDOH. April 2010

delayed presentation by age na accord
Delayed Presentation By Age (NA ACCORD)

Altoff K. et al. In press JAIDS

major observations
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
vacs long term objectives

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



  • 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)
vacs virtual cohort
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
arbitrated clinical events in vacs 8
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)
definition h iv a ssociated n on a ids conditions hana
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

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

fragility fractures hiv n 125 259
Fragility Fractures HIV+/- (n= 125,259)

Womack J. et al. PLoS ONE February 2011 | Volume 6 | Issue 2 | e17217

possible hana
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
general observations on hana
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
  • 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
veterans aging cohort study risk index vacs index

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.

rationale for multivariable risk index
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.

veterans aging cohort study risk index vacs index1
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
composite biomarkers


FIB 4 =

PLT * sqrt(ALT )



eGFR =

186.3 * CREAT




0.742 if female, 1 if male


1.21 if black, 1 otherwise

Composite Biomarkers



VACS Index Thresholds and Weights


HIV Specific


Biomarkers of General

Organ System Injury

Tate J. et al. IDSA 2010 Vancouver, BC October 21-24th. Poster 1136

fib 4 values by age alt and ast platelets 100k
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


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

discrimination of vacs vs restricted index
Discrimination of VACS vs. Restricted Index

Justice AC. et al. A Prognostic Index for those Aging with HIV. CROI 2011 Poster # 793

calibration of vacs vs restricted index 5 year mortality
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

the holy grail surrogate endpoint
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
vacs index correlated with biomarkers of inflammation
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

vacs index summary
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
why is this important
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
example framingham index
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

framingham risk assessment
Framingham Risk Assessment

Results View:

uses of framingham index
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

case example
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.

in development interpretation
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.

counseling hypothetical
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
examples of advice liver disease
Examples of Advice: Liver Disease

Because you appear to have liver injury and have HCV infection, there are a number of things you can do to reduce you VACS Index Score…

  • Review all your medications with your provider to identify any potentially liver toxic medications
  • Cut down or abstain from alcohol
  • Make sure not to skip doses of your ARVs
  • Talk to your provider about taking medications to treat you HCV infection
future work
Future Work
  • Informatics: Develop information tool that calculates index, counsels on risk, identifies modifiable risk, and suggests patient action
  • Observational Analyses: estimate likely effect size for potential interventions: eg, alcohol cessation, HCV treatment, adherence, etc.
  • RCT: strategy trial among those with abnormal FIB 4 who drink alcohol

Veterans Aging Cohort Study

  • PI and Co-PI: AC Justice, DA Fiellin
  • Scientific Officer (NIAAA): K Bryant
  • Participating VA Medical Centers: Atlanta (D. Rimland), Baltimore (KA Oursler, R Titanji), Bronx (S Brown, S Garrison), Houston (M Rodriguez-Barradas, N Masozera), Los Angeles (M Goetz, D Leaf), Manhattan-Brooklyn (M Simberkoff, D Blumenthal, H Leaf, J Leung), Pittsburgh (A Butt, E Hoffman), and Washington DC (C Gibert, R Peck)
  • Core Faculty: K Akgun, S Braithwaite, C Brandt, K Bryant, R Cook, K Crothers, J Chang, S Crystal, N Day, R Dubrow, M Duggal, J Erdos, M Freiberg, M Gaziano, M Gerschenson, A Gordon, J Goulet, N Kim, M Kozal, K Kraemer, V LoRe, S Maisto, K Mattocks, P Miller, P O’Connor, C Parikh, C Rinaldo, J Samet
  • Staff: H Bathulapalli, T Bohan, D Cohen, A Consorte, P Cunningham, A Dinh, C Frank, K Gordon, J Huston, F Kidwai, F Levin, K McGinnis, L Park, C Rogina, J Rogers, L Sacchetti, M Skanderson, J Tate, E Williams
  • Major Collaborators: VA Public Health Strategic Healthcare Group, VA Pharmacy Benefits Management, Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), Yale Center for Interdisciplinary Research on AIDS (CIRA), Center for Health Equity Research and Promotion (CHERP), ART-CC, NA-ACCORD, HIV-Causal
  • Major Funding by: National Institutes of Health: NIAAA (U10-AA13566), NIA (R01-AG029154), NHLBI (R01-HL095136; R01-HL090342; RCI-HL100347) , NIAID (U01-A1069918), NIMH (P30-MH062294), and the Veterans Health Administration Office of Research and Development (VA REA 08-266) and Office of Academic Affiliations (Medical Informatics Fellowship).