1. SNAEs and aging: contribution of ART versus lifestyle factors Dominique Costagliola Institut Pierre Louis d’Epidémiologie et de Santé Publique, UMR-S 1136, INSERM et Sorbonne Universités, UPMC Univ Paris 06

2. Disclosures I have received travel grants, consultancy fees, honoraria and study grants from: – Bristol-Myers-Squibb –Gilead Sciences –Janssen-Cilag –Merck-Sharp & Dohme-Chibret –ViiV Healthcare

3. Ageing in the HIV population COHERE in EUROCOORD Median age 31 35 38 41 43 45 (years)

4. Ageing in the HIV population

5. Myocardial Infarction

6. Relative risks of MI HIV+ versus General Population Islam et al, HIV Medicine 2012 Results confirmed in Freiberg et al, JAMA Internal Med 2013 and Silverberg et al, JAIDS 2014

7. Risk factors for MI in HIV infected individuals HDL- chol mmol/L : OR = 0.67 (95% CI, 0.12-1.12) BMI < 21 kg/m 2 : OR = 1.62 (95% CI, 1.10-2.37) Lang et al, Clin Infect Dis 2012 Smoking No Smoking Yes Family History of CAD No Family History of CAD Yes Hypertension No Hypertension Yes Hypercholesterolemia No Hypercholesterolemia Yes HDL cholesterol level, mmol/L Diabetes No Diabetes Yes BMI< 21 kg/m 2 BMI 21-23 kg/m 2 BMI 24-26 kg/m 2 BM1 ≥ 27 kg/m 2 Cocaine and/or IDU No

8. Risk factors for MI in HIV infected individuals VL > 50 copies/mL OR = 1.51 (95% CI, 1.09-2.10) CD4 Nadir (log 2 ) : OR = 0.90 (95% CI, 0.83-0.97) CD8 > 1150 cells /mm 3 : OR = 1.48 (95% CI, 1.01-2,.18) VL ≤ 50 copies/mL VL > 50 copies/mL CD4 T cell Nadir (log2) CD8 T cell ≤ 760/mm 3 CD8 T cell 761-1150/mm 3 CD8 T cell >1150/mm 3 10 year PI exposure Lang et al, Clin Infect Dis 2012 Result on nadir also seen in Silverberg et al, JAIDS 2014

9. Effect of cART Consistent association of cumulative exposure to older PI with the risk of MI –Mary-Krause et al AIDS 2003; Friis-Møller et al, NEJM 2003; Friis-Møller et al, NEJM 2007; Lang et al, Arch Intern Med 2010; Worm, JID 2010 –No association found for atazanavir in DAD ( D’Arminio Monforte et al, AIDS 2013 ) but was cumulative exposure long enough? –No data on Darunavir Conflicting results on abacavir No data on integrase inhibitors

10. Non-AIDS defining cancers

11. Relative risks of non-AIDS defining cancers in the cART era HIV+ vs General Population CancerNb studySIR (95% CI)Heterogeneity HL (EBV)619 (13-27)<0.001 Anus (HPV)547 (22-100)<0.001 Liver (HBV/HCV)57.5 (4.2-14)<0.001 Lung63.5 (2.6-4.6)<0.001 Breast60.6 (0.5-0.8)0.003 Prostate50.6 (0.4-0.7)0.08 Shiels et al. JAIDS 2009; 52:611-22.

12. The role of immunodeficiency in the risk of NADC Guiguet M et al. Lancet oncology 2009; 10:1152–59.

13. Frequent non-AIDS defining cancers Hodgkin IRR (95%CI) N=149 Lung* IRR (95%CI) N=207 Liver  IRR (95%CI) N=119 Last CD4 >500 350-500 200-350 100-200 50 -100 <50 1.0 1.2 (0.7-2.2) 2.2 (1.3-3.8) 4.8 (2.8-8.3) 7.7 (3.9-15.2) 5.4 (2.4-12.1) 1.0 2.2 (1.3-3.6) 3.4 (2.1-5.5) 4.8 (2.8-8.0) 4.9 (2.3-10.2) 8.5 (4.3-16.7) 1.0 2.0 (0.9-4.5) 4.1 (2.0-8.2) 7.3 (3.5-15.3) 6.6 (2.4-17.6) 7.6 (2.7-20.8) Model adjusted on age, sex and risk, and migration from SubSaharan Africa * Independent of smoking or + independent of HBV/HCV infection in sensitivity analyses

14. Anal cancer Anus IRR (95%CI) N=74 Time with CD4<200 (per year) 1.3 (1.2-1.5) Time with HIV-RNA > 100,000 copies/mL (per year) 1.2 (1.1-1.4) Model adjusted on age, sex and risk, and migration from SubSaharan Africa

15. What is the risk in people with CD4 > 500/mm 3 ?

16. Risk when current CD4 >=500/mm3 Kaiser permanenteHLAnalLungLiver RR in HIV+ with recent CD4 >= 500/mm 3 compared with HIV- 13.5 (7.2–25.1) 33.8 (17.8–64.3) 1.2 (0.7–1.9)1.0 (0.4–2.4) Silverberg et al, Cancer Epidemiol biomarkers Prev 2011 Hleyhel et al, AIDS 2014 FHDH ANRS CO4 HLAnalLungLiver SIR in HIV+ with recent CD4 >= 500/mm 3 for more than 2 years compared with HIV- 9.4 (7.9-16.8) -0.9 (0.6-1.3)2.4 (1.4-4.1) Age, sex and race adjusted Age and sex adjusted

17. The role of smoking Several studies have suggested that HIV infection is associated with lung cancer after adjusting for cigarette smoking –Chaturvedi et al, AIDS 2007; Engels et al, J Clin Oncol 2006; Kirk et al, Clin Infect Dis 2007; Helleberg et al, AIDS 2014 A recent study (Helleberg et al, AIDS 2014) looked at the impact of smoking and HIV on the risk of cancer among HIV-infected individuals compared to the background population: –the risk of cancer is increased in HIV patients compared to the background population Smoking-related cancers IRR 2.8 (1.6-4.9) Virological cancers IRR 11.5 (6.5-20.5) –adjusted for sex, age and smoking status –In absence of smoking, the increase in risk is confined to cancers related to viral infections –whereas the risk of other cancers is not elevated and does not seem to be associated with immune deficiency

18. Effect of cART Inconsistent evidence of a deleterious effect of PI exposure on the risk of anal cancer or of efavirenz exposure on the risk of Hodgkin disease –Chao et al, AIDS 2012; Bruyand et al, CROI 2013; Mbang et al, CROI 2013; Powles et al, J Clin Oncol, 2009

19. Fractures and Low BMD

20. Relative risks of fracture HIV+ versus General Population Adapted from Mallon, Curr Opin HIV AIDS 2014

21. Low BMD and fractures risk factors Low BMI, African ethnicity, current smoking HIV infection independently associated with lower BMD at femoral neck, total hip and lumbar spine after adjustment for demographic/lifestyle factors and BMI –Cotter et al, AIDS 2014 Effect of initiating cART on BMD decline up to 4%, mainly in the first year –Duvivier et al, AIDS 2009; van Vonderen et al, AIDS 2009; Stellbrink et al, CID 2010; Mc Comsey et al JID 2011 Greater losses in BMD with use of tenofovir and protease inhibitors –less so with raltegravir (Brown T et al, CROI 2014,Bloch et al, HIV Med 2014) Association of low BMD with the risk of fractures in HIV infected individuals (Battalora et al, Antiviral Therapy, 2013)

22. Accelerated aging Are SNAEs occurring at an earlier age in HIV patients?

23. Age (yrs) at onset of cancer of AIDS patients and uninfected individuals CancerAIDSGPObserved difference (Years) Rectal4669-23 Anal5062-12 Larynx4865-17 Lung5070-20 Ovarian4263-21 Testicular3534+1 Hodgkin lymphoma 4237+5 Myeloma4770-23 Shiels et al, Ann Intern Med 2010 A Justice, CROI 2012

24. A Difference in age distribution FHDH ANRS CO4 and the population in France

25. Age (yrs) at onset of cancer of AIDS patients and age matched uninfected individuals CancerAIDSGPObserved Difference (Years) Age Adjusted GP Real Difference (Years Rectal4669-2351-5 Anal4262-2045-3 Larynx4865-1752-4 Lung5070-2054-4 Ovarian4263-2146-4 Testicular3534+138-3 Hodgkin lymphoma 4237+540+2 Myeloma4770-2352-5 Shiels et al, Ann Intern Med 2010 Looked at 26 different cancer diagnoses, no difference (p>0.05) for 18. Differences for remaining cancers were <5 years.

26. Age (yrs) at Diagnosis in VACS Comorbid DiseaseHIV+HIV-Difference (Years) Lung Cancer5759-2 MI56 0 Renal Failure (eGFR<45) 5963-4 Fragility Fracture5352+1 Liver Cirrhosis5758 A Justice, CROI 2012 Mainly male population

27. Observed age HIV+ (a) Observed age General population (b) Observed difference (years) (b-a) Expected age General population (c) Real difference (years) (c-a) P-value Lung 49 (43-57) 68 (58-73) -18.3 52.5 (47.5-62.5) -3.3 <10 -4 Hodgkin 42 (36-48) 38 (28-58) +4.1 42.5 (32.5-47.5) -0.9 0.04 Liver 47 (43-54) 73 (63-78) -25.1 57.5 (52.5-62.5) -10.1 10 -4 Anus 46 (39-51) 68 (58-78) -21.9 47.5 (42.5-57.5) -1.9 0.12 Age at cancer diagnosis among HIV-infected patients and the general population in France between 1997 and 2009 Hleyhel M et al, AIDS 2014FHDH ANRS CO4

28. Age at myocardial infarction diagnosis among HIV- infected patients and the general population in France between 2000 and 2006 Men SMR = 1.4 (IC 95%, 1.3-1.6) Women SMR = 2.7 (IC 95%, 1.8-3.9) Median age (IQR) (years) Men HIV+47.2 (42.3-53.9) Expected age GP 47.5 (42.5-57.5) Women HIV+42.5 (40.4-46.8) Expected age GP 47.5 (42.5-55.0) Lang S et al, AIDS 2010 FHDH ANRS CO4

29. Accelerated or Accentuated Shiels et al, Ann Int Med 2010 Risk Factor Risk factor and accelerated aging

30. Conclusions Even in the absence of excess risk, the number of HIV-infected individuals with several SNAEs will increase because of aging, raising issues on the optimal management of multimorbidity and multidrug exposures. The risk of age-associated SNAEs is higher in HIV infected patients This is partly explained by a higher prevalence of traditional risk factors An effect of some ART has been shown for MI, and bone diseases The risk of some SNAEs for an individual with CD4 cell count recovery under cART might not be elevated The effect of HIV infection on age at diagnosis of common SNAEs is not uniform –It depends on comorbidities, sex and other risk factors

31. Acknowlegments Members of my team –Clinical Epidemiology of HIV infection: Therapeutic strategies and comorbidities at the Pierre Louis Institute –S Grabar, M Hleyhel, S Lang, M Mary-Krause Amy Justice Patrick Mallon