Overview of Ageing: a How Can We Optimize Care in the Context of Multimorbidity? Amy C. Justice, MD, PhD Professor, Yale University Schools of Medicine and Public Health Section Chief, General Internal Medicine VA Connecticut Healthcare System

Everyone with access to ART and those who contract HIV at older ages. Who is Ageing with HIV? Everyone with access to ART and those who contract HIV at older ages.

In US: More People Living with HIV Infection Every Year (+38K/yr*) Each year: 56K new infections-18K deaths=38K* http://www.cdc.gov/hiv/topics/surveillance/resources/slides/index.htm

Projected For years 2001-2003, data is based on 33 states and U.S. dependent areas with confidential name-based HIV infection reporting, Centers for Disease Control: HIV/AIDS Surveillance Report, 2005. For years 2004-2007, data is based on 34 states and 5 U.S. dependent areas with confidential name-based HIV infection reporting, Centers for Disease Control: HIV/AIDS Surveillance Report, 2007 *Data from 2009, onward projected based on 2001-20078 trends (calculated by author), 2001-20078 data from CDC Surveillance Reports 2009. New York and San Francisco data from Departments of Public Health

In New York City HIV Epidemiology & Field Services Semiannual Report, NYCDOH. April 2010

Africa is No Exception An estimated 14% of adults with HIV infection in Sub Saharan Africa are >50 years AIDS is leading cause of death among >50 yrs. in Nyanza Providence, Western Kenya Negin J. Bull World Health Organ 2010 Nov 1;88(11):847-853

Projected HIV Prevalence by Age in Hlabisa Sub-district of KwaZulu-Natal, South Africa Hontelez J. Ageing with HIV in South Africa. AIDS 2011 25:1665-73

Sex is Not Only for the Young Proportion reporting sex in last 12 months Based on ACRIA brochure, HIV and Older Adults (first three bullets) The first three bullets seem to be conflicting, but I rechecked the book from which the stats came (HIV/AIDS in Older Adults) and they were listed as such Lindau ST, et al. NEJM. 2007;357:762-774.

Sexual Risks Among Older Adults Newly single (widowed/divorced) status Ratio of men to women increasingly skewed Less likely to use condoms Postmenopausal women--pregnancy no longer possible Men may have erectile dysfunction complicating condom use Lower estrogen leads to vaginal dryness and likely increases risk of viral transmission

Among HIV+ on ART, What Drives Morbidity and Mortality? Multi morbidity define as co occurrence of health conditions that cannot be cured and likely interact, but require ongoing monitoring and treatment.

Delayed Presentation By Age (NA ACCORD) Altoff K. et al. JAIDS 2011

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

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

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

Death Rate Disparities by HIV, Race/Ethnicity and Age Per capita rate of HIV among persons 50+: AA 12x as likely as whites Latinos 5x as likely as whites In 2001, African American women made up: 11% of women over 50 More than 65% of all HIV infections among all older women in the U.S. HIV Epidemiology & Field Services Semiannual Report, NYCDOH. April 2010

Strategies for Management of ART (SMART) *More AIDS and “Non-AIDS” Events Among Rx. Sparing Arm (HR 1.7 in SMART) NEJM 2006;355:2283-96

HIV Associated Non AIDS(HANA) Conditions 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 Not necessarily closely tied to CD4 count

Premature or Accentuated Aging??? Some studies suggest HANA conditions occur 20-30 years earlier than expected among HIV+ Most are not adjusted for differences in the underlying age distribution Others are not adjusted for differences in established risk factors (smoking, alcohol, drug use, or hepatitis C co-infection)

Premature or Accentuated Cancer? A. Premature cancer : cancer occurs earlier among those with HIV than uninfected comparators. B. Accentuated risk: cancer could occur at the same ages but more often than among comparators. Shiels MS. Ann Intern Med 2010:153:452-460.

Multimorbidity in HIV In North America and Europe In Africa HCV co infection, alcohol, tobacco, and opioid abuse In Africa Tuberculosis, malaria, obstructive lung disease (smoke inhalation) and alcohol abuse Among all those ageing: HANA conditions Vascular disease, liver disease, renal disease, osteoporosis, and specific cancers

Justice AC. HIV and Aging: time for a new paradigm Justice AC. HIV and Aging: time for a new paradigm. Curr HIV/AIDS Rep 2010: &:69-76

What are the Implications of Multimorbidity?

In the US General Population Screening and Treatment Guidelines do not consider it (RCTs exclude multimorbidity) 50% of >65 years have >3 comorbid conditions A disconnect between healthcare focusing on individual patient vs. individual disease Multimorbidity represents the next frontier in the evolution of Evidence Based Medicine Campbell-Scherer D. Multimorbidity: a challenge for EBM. Evid Based Med 2010: 15:165-166

Guidelines do not Consider Harms from polypharmacy Interactions with substance use or depression Hepatitis B or C Social issues which compete with ability to adhere to complex treatment regimens

Guideline Overload Considered guidelines for 10 chronic diseases to a panel of 2500 with age, sex, and chronic disease prevalence matched to US Did not allow for new patients Estimated MD time required assuming All stable (3.5 hours/day) Some active disease (10.6 hours/day) Did not allow for new problems Ostbye T, Ann Fam Med 2005;3:209-14

Multimorbidity is a Game Changer Increases treatment benefit if condition interacts with other conditions (e.g. HCV) Decreases time to benefit from screening (e.g. cancer screening) Increases risk of toxicity Creates competing demands: there isn’t time to address HIV and primary care guidelines and adequately care for active problems

We Need a New Paradigm and a New Approach to Measuring Disease to Guide Us

We Need to Prioritize Synergies Hypertension causes cardiovascular disease, stroke, and renal disease Smoking increases risk of cardio- vascular disease, stroke, lung disease, and cancer Alcohol causes microbial translocation, elevates bp, speeds HCV progression, causes liver cirrhosis and cancer, impedes adherence, and may substantially contribute to vascular disease

And to Tailor Screening and Treatment to Individual Risk Use prediction tools to estimate net benefit Rather than relative benefit Account for treatment disutilities Requires two inputs: Accurate estimation of risk Risk reduction associated with interventions Hayward RA. et al. Optimizing Statin Treatment for Primary Prevention of CAD. Ann Int Med 2010:152:69-77 Eddy DM. et al. Individualized Guidelines: The Potential for Increasing Quality and Reducing Costs Ann Intern Med 2011;154:627-634.

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 Justice, AC. et. al, HIV Med. 2010 Feb;11(2):143-51. Epub 2009 Sep 14.

The Veterans Aging Cohort Study (VACS) Well characterized NIAAA cohort >40,000 HIV+ matched to >80,000 HIV- Matched on age, race/ethnicity, region All HIV+ entering care since 1998 Controls had to be seen in VA in same year ~10 yrs. of longitudinal data Clinically arbitrated endpoints for MI, stroke, cancer, pneumonia, and cirrhosis Nested in-depth cohort of >7,000 (half HIV+)

Validated in Cross Cohort Collaborations ART-CC: Largely European, 19 cohorts NA-ACCORD: North American, 21 cohorts VA mortality rates are somewhat higher and population is older and more likely to be male Associations with outcomes very consistent

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

Composite Biomarkers AGE * AST FIB 4 = PLT * sqrt(ALT ) eGFR = 186.3 * CREAT -1.154 * AGE -0.203 * FEM_VAL * BLACK_VAL FEM_VAL = 0.742 if female, 1 if male BLACK_VAL = 1.21 if black, 1 otherwise 34

VACS Index Thresholds and Weights Index Score Restricted VACS Age (years) <50 50 to 64 23 12 > 65 44 27 CD4 > 500 cells/mm3 350 to 499 10 6 200 to 349 100 to 199 19 50 to 99 40 28 < 50 46 29 HIV-1 RNA < 500 copies/ml 500 to 1x105 11 7 > 1x105 25 14 Hemoglobin > 14 g/dL 12 to 13.9 10 to 11.9 22 < 10 38 FIB-4 < 1.45 1.45 to 3.25 > 3.25 eGFR mL/min > 60 45 to 59.9 30 to 44.9 8 < 30 26 Hepatitis C Infection 5 Age HIV Specific Biomarkers Biomarkers of General Organ System Injury Tate J. et al. IDSA 2010 Vancouver, BC October 21-24th. Poster 1136

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 Subgroup VACS Index C-stat Restricted Index p-value** Overall 0.80 0.75 <0.0001 Male Female 0.81 0.77 <0.001 White Black Hispanic 0.79 0.90 0.74 0.76 0.78 Age <50 >= 50 0.69 HIV-1 RNA <500 >=500 0.68 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) Justice AC. et al. A Prognostic Index for those Aging with HIV. CROI 2011 Poster # 793

VACS Index Response to 1st Year of cART (+/- 80% adherence) Notice greater discrimination with VACS index Solid lines indicate >80% adherence Tate J. et al. IDSA 2010 Vancouver, BC October 21-24th. Poster 1136

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 Vs. Restricted Index Summary More accurately predicts mortality among patients in North America and Europe More responsive to antiretroviral treatment More strongly correlated with markers of hyper-coagulability, microbial translocation, and inflammation

Why Should Clinicians Care? Uses lab tests currently part of routine care Identifies modifiable risk at lower test thresholds Incorporates age, and effects of HANA and toxicity Computation easy, can be included in lab reports and available through websites/apps Offers approach that incorporates multifaceted HIV effects, multimorbidity, and toxicity

Case HIV+ 45 yr old man. After 1 yr. of ART, CD4 count is 500 cells/mm3, HIV-1 RNA undetectable. HCV+ and has a FIB-4 >3.25. Restricted Index Score=0 Expected 5 yr mortality 2% VACS Index Score=30 (5 pts HCV ;25 pts FIB-4) Expected 5 yr mortality 12%

Case Continued Just as Framingham charts CVD risk over time the VACS Index can chart overall health over time For this patient, we would target sources of liver injury: HCV, alcohol, toxic medications, and obesity If we achieve a SVR and his FIB-4 normalizes score drops to 0; new 5 yr mortality 2% If we decrease his FIB-4 from “high” to “moderate” his score would drop to 11; new 5 yr mortality 3-fold lower (from 12% to 4%)

Future Work Informatics: tools to calculate index, counsel on risk, identify modifiable risk, and suggest patient and provider action Observational Analyses: estimate likely effect size for potential interventions: eg, alcohol cessation, HCV treatment, adherence, etc. RCT: compare VACS Index guided management to usual care among multimorbid HIV+ patients Possible outcomes: hospitalization, MICU admission, nursing home placement, or death

National VACS Project Team 2010

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).