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![Page 1: Estimating burden of disease among aging HIV-infected individuals in LMICs Annette H. Sohn, MD TREAT Asia/amfAR – Thailand AIDS 2014.](https://reader035.fdocuments.us/reader035/viewer/2022062314/56649ef05503460f94bfff4f/html5/thumbnails/1.jpg)
Estimating burden of disease among aging HIV-infected individuals in LMICs
Annette H. Sohn, MDTREAT Asia/amfAR – ThailandAIDS 2014
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HIV as a Chronic Disease
• Life expectancy estimates improving with earlier ART and immune recovery1
– Low CD4 the dominant predictor across high- to low-income settings
• With constant treatment expansion in SSA – 2011: 1 in 7 PLHIV >50 years 3.1M2
– 2040: 1 in 4 PLHIV >50 years 9.1M• Prevalence in South Africa 17%3
1. Sabin CA, BMC Medicine, 2013;11:251.2. Hontelez JAC, AIDS, 2012;26:S19-30. SSA=Sub-Saharan Africa3. Hontelez JAC, AIDS, 2011;25:1665-7.
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Aging and mortality, South Africa 2004-12+
• 5,00010,000 patients in 6 cohorts– 610% >50 years old at enrollment– 220% >50 year-olds in care 1
6-2
9
30
-34
35
-39
40
-44
45
-49
50
-54
55
-59
60
-64
65
+
0
0.1
0.2
0.3
0.4
Age, years
5-year cumulative mortality hazard
HIV-negative
HIV-positive
Cornell M, IeDEA Southern Africa. In submission.
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How do HIV and ART modify NCD risk?
• Causes of death increasingly related to non-AIDS events– Veterans’ Aging Cohort Study (VACS): PLHIV
with increases in adjusted incidence of myocardial infarction (81%), end-stage renal disease (43%), and AIDS-related cancers (84%)*
*Althoff K, CROI 2013, #59. Cancers: Lung, liver, anal, oropharyngeal, Hodgkins lymphoma.
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Inflammation↑ Monocyte activation
↑ T-cell activationDyslipidemia
Hypercoagulation
Microbial translocation
HIV-associated fatmetabolic syndromeHIV production
HIV replication
CMVExcess pathogens
Loss of regulatory cells
Co-morbiditiesAging
Slide courtesy of Steve Deeks, University of California, San Francisco.
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NCDs
Cardiovascular
Stroke
Renal
BoneMetabolic
Pulmonary
Cancers
LiverMental, neurologic
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Challenges in Estimating Burden of NCDs in LMICs
• Data sources frequently clinic-based, cross-sectional or short-term– Few registries linking HIV to NCDs
• Risk assessment methods frequently based on Western patient data– Framingham, D:A:D, VACS Index, eGFR
• Lack HIV-negative comparator group– Difficult to separate out impact of HIV, ART
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Cardiovascular Disease
• Incomplete ascertainment of CV events and causes of death for general and HIV-positive populations in LMICs*
• Risk may decrease for some conditions and increase for others after ART– Thailand: metabolic syndrome higher among
ART-experienced (25%) vs. naive (16%) or general population (13%)**
*Hertz JT, PLoS One. 2014 May 9;9(5):e96688.**Jantarapakde J, AIDS Patient Care STDS. 2014 Jun 10. N=580, national study.>3 of: abdominal obesity, hypertriglyceridemia, low HDL, high blood pressure, high fasting plasma glucose (AHA and NHLBI criteria).
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Primary Cardiovascular Diagnoses Among PLHIV, Heart of Soweto Study
Silwa K, Eur Heart J. 2012 Apr;33(7):866-74. N=518
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HypertensionData period
Sample size
HTN rate Reference
KenyaHIV+ only, 66% on ART
2006-2009 12,194 11.2% men, 7.4% women
Bloomfield GS, PLoS One. 2011; 6(7):e22288.*
South AfricaHIV+ only
2004-2011 17,378 29% at ART start, 17% at 24 months
Brennan AT, CROI 2014, #759.*
Asia, regionalHIV+ only, all on ART
2010-2013 5741 21% at last BP50% at any BP
TREAT Asia-TAHOD
Uganda, General survey, 8% HIV+
2011 2278 27% men, 29% women
Chamie G, PLoS One. 2012;7(8): e43400.*
Tanzania and UgandaGeneral survey, 10-11% HIV+
2012-2013 1984 16.5% Tanzania, 25% Uganda
Kapiga SH, CROI 2014, #1016.
*HTN defined as SBP >140, DBP >90.
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Yanik EL, Clin Infect Dis, 2013 Sep;57(5):756-64. CNICS=Centers for AIDS Research Network of Integrated Clinical Systems
Incidence of First Cancer after ART CNICS, 1996–2011
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Age
-sta
ndar
dize
d ra
te, c
ases
per
100
,000
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Incidence of KS on ARTSetting Data period Sample size Incidence per
100,000 PYReference
Caribbean, Central/South AmericaCCASAnet
2007-2009 3372;8080 PY
450 Fink VI, J Acquir Immune Defic Syndr, 2011 Apr 15;56(5):467-73.
East Africa IeDEA
2008-2011 98,024; 144,182 PY
201 in Uganda 270 in Kenya
Martin J, Infect Agent Cancer, 2012;7S1:O19.
IeDEA South Africa
2004-2010 17,516; 30,352 PY
138 Bohlius J, Int J Cancer, 2014 Apr 12.
IeDEA Southern Africa
2004-2010 173,245; 316,787 PY
173 In submission
US, CNICS 1996-2011 11,485;46,318 PY
304 Yanik EL, Clin Infect Dis, 2013 Sep;57(5):756-64.
Adapted from Semeere AS (Curr Opin Oncol 2012;24:522-30) and Rohner E (in submission).
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Hepatic Decompensation and Death in HIV-HCV vs. HCV Patients
VACS-VC: Standardized cumulative incidence of decompensation higher among co-infected (7.4%) vs. mono-infected (4.8%) patients at 10 years – even if no/minimal fibrosisLo Re V 3rd, Ann Intern Med. 2014 Mar 18;160(6):369-79.
French National Hospital Database: Overall mortality higher for co-infected (7.5%) vs. monoinfected (2.8%) patients; No difference among those with HIV-HBV.Mallet V, CROI 2014, #690.
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Liver Disease
• Zambia: 8.5% of patients entering HIV care with fibrosis by FIB-4 and APRI (N=35,551)1
• Thailand: 11% of HBV/HCV-negative ART patients with liver stiffness by FibroScan® (N=585)2
– 21% >50 years old; median time on ART 11 years
• TREAT Asia HCV treatment eligibility study3
– Viral load (N=184): 83% detectable HCV, median (IQR) 1,954,051 (482,000-4,332,188) IU/mL
– FibroScan® (N=120): 33% F1, 22.5% F2, 24% F3, 20% F4
1. Vinikoor MJ, CROI 2014, #790. Significant fibrosis defined as FIB-4 >3.25 or APRI >1.5.2. Avihingsanon A, CROI 2014, #786. Abnormal result >7.2kPa.3. Durier N, AIDS 2014, TU11263LB. Metavir fibrosis scores: F1-mild, 2-moderate, 3-severe, 4 cirrhosis.
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Summary
• Improved diagnostic capacity and reporting systems in LMICs are needed to reliably estimate NCD burden – Service integration with HIV infrastructure?– National health surveys, regional cohort studies,
cancer registries
• Risk factor data can help distinguish HIV- and non-HIV-related outcomes and target screening recommendations– Traditional NCD and HIV-specific exposures
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Acknowledgements
• Amy Justice, VA Connecticut Healthcare System• Jintanat Ananworanich, MHRP• Paolo Miotti, NIH OAR• IeDEA Southern Africa – Julia Bohlius, Morna
Cornell, Gilles Wandeler, Mary-Ann Davies, Matthias Egger
• Kirby Institute – David Boettiger, Awachana Jiamsakul, Matthew Law