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SNAEs and aging: contribution of ART versus lifestyle factors

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 . Disclosures.

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SNAEs and aging: contribution of ART versus lifestyle factors

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  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 Median age 31 35 38 41 43 45 (years) COHERE in EUROCOORD

  4. Ageing in the HIV population

  5. Myocardial Infarction

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

  7. Riskfactors for MI in HIV infectedindividuals Smoking No Smoking Yes FamilyHistory of CAD No FamilyHistory of CAD Yes Hypertension No Hypertension Yes Hypercholesterolemia No HypercholesterolemiaYes HDL cholesterollevel, mmol/L Diabetes No DiabetesYes BMI< 21 kg/m2 BMI 21-23 kg/m2 BMI 24-26 kg/m2 BM1 ≥ 27 kg/m2 Cocaine and/or IDU No Cocaine and/or IDU No HDL- cholmmol/L : OR = 0.67 (95% CI, 0.12-1.12) BMI< 21 kg/m2 : OR = 1.62 (95% CI, 1.10-2.37) Lang et al, Clin Infect Dis 2012

  8. Riskfactors for MI in HIV infectedindividuals VL ≤ 50 copies/mL VL > 50 copies/mL CD4 Tcell Nadir (log2) CD8 Tcell ≤ 760/mm3 CD8 Tcell 761-1150/mm3 CD8 Tcell >1150/mm3 10 year PI exposure VL > 50 copies/mL OR = 1.51 (95% CI, 1.09-2.10) CD4 Nadir (log2) : OR = 0.90 (95% CI, 0.83-0.97) CD8 > 1150 cells /mm3 : OR = 1.48 (95% CI, 1.01-2,.18) Result on nadir also seen in Silverberg et al, JAIDS 2014 Lang et al, Clin Infect Dis 2012

  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-Mølleret al, NEJM 2007; Lang et al, Arch Intern Med 2010; Worm, JID 2010 • No association found for atazanavir in DAD (D’ArminioMonforte 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 cARTera HIV+ vs General Population 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 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. What is the risk in people with CD4 > 500/mm3?

  15. Risk when current CD4 >=500/mm3 Age, sex and race adjusted Ageand sexadjusted Silverberg et al, Cancer Epidemiol biomarkers Prev 2011 Hleyhel et al, AIDS 2014

  16. 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 ClinOncol 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

  17. 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

  18. Fractures and Low BMD

  19. Relative risks of fractureHIV+ versus General Population AdaptedfromMallon, Curr Opin HIV AIDS 2014

  20. Low BMD and fractures risk factors • Low BMI, Africanethnicity, 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; McComsey 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)

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

  22. Age (yrs) at onset of cancer of AIDS patients and uninfected individuals A Justice, CROI 2012 Shielset al, Ann Intern Med 2010

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

  24. Age (yrs) at onset of cancer of AIDS patients and age matched uninfected individuals Looked at 26 different cancer diagnoses, no difference (p>0.05) for 18. Differences for remaining cancers were <5 years. Shielset al, Ann Intern Med 2010

  25. Age (yrs) at Diagnosis in VACS Mainly male population A Justice, CROI 2012

  26. Age at cancer diagnosis among HIV-infected patients and the general population in France between 1997 and 2009 Hleyhel M et al, AIDS 2014 FHDH ANRS CO4

  27. 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) Lang S et al, AIDS 2010 FHDH ANRS CO4

  28. 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 cARTmight 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

  29. 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

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