Overview of Ageing: a

How Can We Optimize Care in the Context of Multimorbidity?

Amy C. Justice, MD, PhDProfessor, Yale University

Schools of Medicine and Public HealthSection Chief, General Internal Medicine

VA Connecticut Healthcare System

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*)

http://www.cdc.gov/hiv/topics/surveillance/resources/slides/index.htm

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

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

17%19%

21% 22%25%

27% 27% 29%33%

35%37%

39%41%

44%45%

47%50%

Projected Proportion of those Living With HIV in United States 50+ Years*

2001-2017

NY City

US VA in 2003

As of 2008:San Francisco

*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

Projected

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

Lindau ST, et al. NEJM. 2007;357:762-774.

Pro

port

ion

repo

rtin

g se

x in

last

12

mon

ths

57-64 65-74 75-850.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

83.7

67.0

38.5

61.6

39.5

16.7

Men Women

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.

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 20070

50

100

150

200

250

300

350

400

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

40% 41% 39%41% 42%

44%42%

45% 46% 47% 48%

30%32% 34%

36% 36%38%

41% 39% 41% 39% 39%

269277 275

284293

313296

312323

333 336

203211

246261

234

272 274261

272 273 266

<50 years ≥50 years <50 years ≥50 years

Year

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350

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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

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

Death Rate Disparities by HIV, Race/Ethnicity and Age

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– 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. 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 2010:152:69-77Eddy 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)

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

An index composed of routinely collected laboratory values that accurately predicts all cause mortality among those with HIV infection

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+)

31

Validated in Cross Cohort Collaborations

• 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

34

Composite Biomarkers

34

AGE * AST PLT * sqrt(ALT )

FIB 4 =

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

Index ScoreRestricted VACS

Age (years) <50 0 050 to 64 23 12> 65 44 27

CD4 > 500 0 0cells/mm3 350 to 499 10 6

200 to 349 10 6100 to 199 19 1050 to 99 40 28< 50 46 29

HIV-1 RNA < 500 0 0copies/ml 500 to 1x105 11 7

> 1x105 25 14

Hemoglobin > 14 0g/dL 12 to 13.9 10

10 to 11.9 22< 10 38

FIB-4 < 1.45 01.45 to 3.25 6> 3.25 25

eGFR mL/min > 60 045 to 59.9 630 to 44.9 8< 30 26

Hepatitis C Infection 5

Age

HIV SpecificBiomarkers

Biomarkers of General Organ System Injury

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

VACS Index Thresholds and Weights

36

0%

20%

40%

60%

80%

100%

0 20 40 60 80 100Risk Score

Mo

rta

lity

Justice AC. HIV and Aging: Time for a New Paradigm. Curr HIV/AIDS Rep. 2010 May;7(2):69-76

y = 0.0091x - 0.0318

R2 = 0.9916

0%

20%

40%

60%

80%

100%

0 20 40 60 80 100Risk Score

Mo

rta

lity

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

VACS Index Highly Predictive of Long Term (5 Year) All Cause Mortality

Individual Scores

Aggregated Scores

Discrimination of VACS vs. Restricted Index

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

Subgroup VACS IndexC-stat

Restricted IndexC-stat

p-value**

Overall 0.80 0.75 <0.0001MaleFemale

0.810.81

0.750.77

<0.001<0.001

WhiteBlackHispanic

0.790.810.90

0.740.760.78

<0.001<0.001<0.001

Age<50>= 50

0.810.74

0.750.69

<0.001<0.0001

HIV-1 RNA<500>=500

0.770.78

0.680.74

<0.0001<0.0001

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)

39

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

eGFR

Age

HIV-1 RNA

Hemoglobin

FIB-4

CD4 count

Rest. index

VACS index

0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50

IL-6sCD14d-Dimer

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%

• 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%)

Case Continued

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

• 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).

Veterans Aging Cohort Study