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Rafael E. Campo, MD Professor of Clinical Medicine Division of Infectious Diseases University of Miami School of Medicine Miami, Florida Optimizing Treatment.

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Presentation on theme: "Rafael E. Campo, MD Professor of Clinical Medicine Division of Infectious Diseases University of Miami School of Medicine Miami, Florida Optimizing Treatment."— Presentation transcript:

1 Rafael E. Campo, MD Professor of Clinical Medicine Division of Infectious Diseases University of Miami School of Medicine Miami, Florida Optimizing Treatment and Management of HIV/AIDS in Personas of Advanced Age

2 2 Learning Objectives (CME, CE, CPE) ●At the completion of this educational activity, participants should be able to: - Describe the epidemiology of HIV and common comorbidities in patients of advanced age in the United States - Discuss key efficacy and safety issues associated with initiating and maintaining antiretroviral therapy in HIV-infected patients of advanced age - Explain special considerations/management approaches to HIV-infected patients of advanced age

3 3 Program Overview ●Epidemiologic trends ●HIV screening/testing ●When to start therapy: mortality and prognosis ●Treatment options and response ●Management considerations

4 4 By 2015, Approximately 50% of People Living With HIV Will Be >50 Years of Age Smith G. Senate Committee on Aging. 2005 Available at: http://aging.senate.gov/events/hr141gs.pdf.

5 5 New HIV/AIDS Cases in 2007 by Age at Diagnosis (34 States) Number of New HIV/AIDS Cases 65 Age (years) CDC. HIV/AIDS Surveillance Report, 2007. Available at: http://www.cdc.gov/hiv/topics/surveillance/resources/reports/2007report/default.htm.

6 6 New HIV/AIDS Cases in the US (2007): Gender, Age, and Race/Ethnicity (39 States) Males Number of New HIV/AIDS Cases White (n=10,573) Black (n=14,324) Hispanic/ Latino (n=6871) CDC. HIV/AIDS Surveillance Report, 2007. Available at: http://www.cdc.gov/hiv/topics/surveillance/resources/reports/2007report/default.htm. Years of Age <20 35 to 40 20 to 34 >50 Females Number of New HIV/AIDS Cases White (n=1986) Black (n=7258) Hispanic/ Latino (n=2005) Years of Age <20 35 to 40 20 to 34 >50

7 7 New AIDS Cases in the US (2002): Gender, Age, and Transmission Category Males New AIDS Cases (%) MSM IDU Heterosexual Contact CDC public use data set through year-end 2002. Available at: http://www.cdc.gov/hiv/topics/surveillance/resources/software/apids/index.htm. Females New AIDS Cases (%) IDUHeterosexual Contact Data for transmission categories “other” and “not reported” are not shown. Years of Age 13 to 19 35 to 40 20 to 34>50 Years of Age 13 to 19 35 to 40 20 to 34>50

8 8 Persons Living With HIV/AIDS (34 States) Years of Age <20 35 to 49 20 to 34 >50 Persons Living With HIV/AIDS (%) 2004 (n=475,689) 2005 (n=498,512) 2006 (n=522,489) 2007 (n=551,931) 1.9% 19.6% 56.3% 22.2% 1.9% 18.5% 55.4% 22.2% 1.8% 18.0% 54.0% 26.2% 1.7% 17.8% 52.2% 28.3% CDC. HIV/AIDS Surveillance Report, 2007. Available at: http://www.cdc.gov/hiv/topics/surveillance/resources/reports/2007report/default.htm.

9 9 Persons Living With AIDS (50 States) Persons Living With HIV/AIDS (%) 2004 (n=393,199) 2005 (n=413,077) 2006 (n=433,782) 2007 (n=455,636) 1.1% 12.7% 59.5% 26.7% 1.1% 11.7% 58.2% 29.0% 1.0% 11.1% 56.3% 31.6% 1.0% 10.7% 54.2% 34.1% CDC. HIV/AIDS Surveillance Report, 2007. Available at: http://www.cdc.gov/hiv/topics/surveillance/resources/reports/. Years of Age <20 35 to 49 20 to 34 >50

10 10 Time to AIDS Diagnosis After a Diagnosis of HIV Infection in 2006 (34 States) AIDS Diagnosis After Diagnosis of HIV Infection (%) <20 (n=1622) 20 to 34 (n=13,739) 35 to 49 (n=16,046) >50 (n=5752) CDC. HIV/AIDS Surveillance Report, 2007. Available at: http://www.cdc.gov/hiv/topics/surveillance/resources/reports/. Age at HIV Diagnosis (year) 14.3% 85.7% 26.7% 73.3% 41.0 % 59.0 % 50.6% 49.4% AIDS diagnosis after HIV diagnosis <12 months (overall: 36.0%) <12 months (overall: 36.0%) >12 months (overall: 64%) >12 months (overall: 64%)

11 11 Survival After AIDS Diagnosis (1998-2005) Proportion Surviving 0 12 24 36 48 60 72 84 96 108 Months After AIDS Diagnosis <13 13-24 25-34 35-44 45-54 >55 Age at Time of Diagnosis CDC. HIV/AIDS Surveillance Report, 2007. Available at: http://www.cdc.gov/hiv/topics/surveillance/resources/reports/2007report/default.htm.

12 12 Issues Specific to Older Persons With HIV Disease ●Unprotected sex - No concern about pregnancy - “I’m too old to catch HIV” ●Delay in testing ●Limited incomes ●Immune reconstitution ●Comorbid illnesses ●Polypharmacy ●Insufficient data on drug interactions in older population Luther VP, et al. Clin Geriatr Med. 2007;23:567-583. Illa L, et al. AIDS Behav. 2008;12:935-942.

13 13 Program Overview ●Epidemiologic trends ●HIV screening/testing ●When to start therapy: mortality and prognosis ●Treatment options and treatment response ●Management considerations

14 14 CDC: Estimated Prevalence of Undiagnosed HIV Infection in the United States (2006) Undiagnosed HIV (%) Undiagnosed HIV Infection Age Group (y) 13-24 25-3435-4445-54>55 28.4% 47.8% 19.4% 16.1% 19.1% ●Estimated persons living with undiagnosed HIV infection in the United States at the end of 2006 (n=232,700) - Overall incidence: 21% ●Undiagnosed prevalence rates (per 100,000 population) - Overall: 94.2 - Age (years) 13-24: 45.4 25-34: 122.9 35-44: 174.3 45-54: 126.6 >55: 42.5 Campsmith ML, et al. JAIDS. 2009;Oct 15. [Epub ahead of print].

15 15 National HIV Behavioral Surveillance: Unrecognized HIV Infection ●Cross-sectional study - 5-city data collection system - Men who have sex with men - 83% participation rate ●Participants tested for HIV infection - Surveyed about knowledge of their HIV status Age Group (years) Prevalence (%) 79% Unrecognized Infection 18-2425-2930-3940-49>50 70% 49% 30% 34% Branson BM, et al. MMWR Recomm Rep. 2006;55(RR-14):1-17.

16 16 Factors Associated With Late or Missed Diagnosis of HIV Infection in Older Adults ●Routine screening uncommon in this age group ●Poor awareness of HIV risk factors (including safe sex practices) - Lack of HIV prevention education targeting older adults ●Health care provider belief that older adults are not sexually active ●Failure of some health care providers to consider HIV infection in this patient population ●Confusion about HIV-specific or opportunistic infection symptoms with symptoms of other diseases Luther VP, et al. Clin Geriatr Med. 2007;23:567-583. Illa L, et al. AIDS Behav. 2008;12:935-942.

17 17 Sexual Activity and HIV Risk in Older Adults ●Use of erectile dysfunction drugs contributes to increased rates of sexual activity ●Menopause - No risk for pregnancy=no need for condom ●Vaginal dryness due to estrogen depletion leads to greater likelihood of trauma and increased risk of HIV acquisition Luther VP, et al. Clin Geriatr Med. 2007;23:567-583. Illa L, et al. AIDS Behav. 2008;12:935-942.

18 18 Project ROADMAP: Sexual Risk Behaviors of Older HIV-Positive Patients ●Sexually active, HIV-positive men and women ●Baseline demographics - Age (years): 51 (45-71) - Race Black (82%), Hispanic (12%), white (5%) - On HAART: 92% - Transmission through heterosexual contact: 94% - Age at HIV diagnosis Mean: 39.7 years >45 years of age: 25% Illa L, et al. AIDS Behav. 2008;12:935-942. ROADMAP: Re-educating Older Adults in Maintaining AIDS Prevention (UM/JMH). Exploratory Findings Men (n=125) Women (n=85) Sexual preference (%) Heterosexual Homosexual Bisexual 84 8 94 1 5 >1 sexual partner (%)4614 Vaginal sex87100 Anal sex205 Number of sexual acts in past 6 months With only women (%) With only men (%) Both (%) 6 85.6 12.0 2.0 7 --

19 19 Project ROADMAP: Sexual Risk Behaviors of Older HIV-Positive Patients ●Approximately 20% of sexually active participants reported not using condoms consistently ●60% reported having anal or vaginal sex at least once with HIV negative/unknown serostatus partners - Of these, 17.3% reported not using condoms ●Conclusion: interventions are needed to help older patients engage in safer sexual practices Illa L, et al. AIDS Behav. 2008;12:935-942. ROADMAP: Re-educating Older Adults in Maintaining AIDS Prevention (UM/JMH).

20 20 Sexual Behaviors in 3 Subgroups of HIV-Positive Patients >50 Years of Age Irregular Condom Use in Sexually Active (%) % Sexually Active in Past 3 Months (n)Overall With Serodiscordant Partner Factors Associated With Irregular Condom Use Gay/bisexual men (n=136) 36 (n=49)3729Lower HIV knowledge Better cognitive functioning Lower annual income Heterosexual men (n=57) 72 (n=41)2717Increased loneliness Heterosexual women (n=97) 21 (n=20)3515Lower HIV knowledge Lovejoy TI, et al. AIDS Behav. 2008;12:943-956.

21 21 HCSUS and VACS 3: Symptom Expression in Older HIV Patients ●Cross-sectional studies - HCSUS (n=2864) - VACS 3 (n=867) ●Patients 50 years of age - HCSUS 4.6 versus 3.8 (P<0.05) - VACS 3 10.3 versus 9.5 (P<0.05) ●Reports of fewer symptoms may hinder identification of HIV Zingmond DS, et al. JAIDS. 2003;33:S84-S92. Baseline Characteristics (>50 Years of Age) HCSUS (n=286) VACS 3 (n=385) Male (%)84100 Race White Black Hispanic 48 41 10 34 52 14 CD4 (cells/mm 3 )270389 HIV exposure (%) MSM IDU Heterosexual contact 39 23 17 40 36 22 Current ARV use (%)8588

22 22 HCSUS and VACS 3: Differences in Symptom Expression in Older HIV Patients HCSUS Multivariate Odds Ratio Peripheral Neuropathy Headache DiarrheaDown/ Blue Feeling White Oral Patches 1.90 (1.39-2.61) 0.62 (0.46-0.84) 0.65 (0.45-0.94) 0.63 (0.41-0.96) 0.69 (0.54-0.89) Zingmond DS, et al. JAIDS. 2003;33:S84-S92. Adjusted for gender, income, current homelessness, drug dependance, heavy alcohol use, exposure risk factor, ART use, CD4 nadir, history of AIDS illness. Likelihood in >50 versus <50 years of age More Less VACS 3 Multivariate Odds Ratio Peripheral Neuropathy Headache Weight Loss Hair Changes 1.39 (1.01-1.91) 1.46 (1.06-2.01) 1.41 (1.02-1.97) 0.57 (0.42-0.78) Likelihood in >50 versus <50 years of age More Less

23 23 CDC Recommendations for HIV Testing in Healthcare Settings ●Routine voluntary testing for patients ages 13 to 64 years in healthcare settings - Not based on patient risk ●Opt-out testing ●No separate consent for HIV ●Pretest counseling not required ●Repeat HIV testing left to discretion of provider - Based on patient risk Branson BM, et al. MMWR Recomm Rep. 2006;55(RR-14):1-17.

24 24 Cost-Effectiveness of Screening the General Population for HIV Dollars per Quality-Adjusted Life-Year Gained Screening Once Screening Every 5 Years Screening Every 3 Years Paltiel AD, et al. Ann Intern Med. 2006;145:797-806. Not Cost Effective Cost Effective $30,800 $60,700 $32,300 $55,500 HIV Prevalence 1.0% 0.1%

25 25 Cost Effectiveness of HIV Screening in People >55 Years of Age: Stream-Lined Counseling 55 60 65 70 75 Age (years) With a Sexual Partner at Risk Sanders GD, et al. Ann Intern Med. 2008;148:889-903. Without a Partner at Risk HIV Prevalence 1.0% 0.5% 0.1% Dollars per Quality-Adjusted Life-Year Gained Not Cost Effective Cost Effective 55 60 65 70 75 Age (years) HIV Prevalence 1.0% 0.5% 0.1% Dollars per Quality-Adjusted Life-Year Gained Not Cost Effective Cost Effective

26 26 Recommended Strategies to Increase HIV Testing ●All primary care settings ●Emergency departments, in-patient services, and urgent care clinics ●Public health settings - Tuberculosis clinics - Sexually transmitted diseases clinics - Substance abuse treatment centers - Correctional facility treatment centers ●Nonclinical settings ●Screening may be discontinued in low-prevalence communities with demonstrated yield <1:1000 Branson BM, et al. MMWR Recomm Rep. 2006;55(RR-14):1-17.

27 27 Additional Considerations for HIV Testing in Persons of Advanced Age ●Consider periodic testing in persons with continued risk ●If identified as being HIV positive - Counsel to notify their partner(s) (sexual or injecting) Partner notification requirements vary by state law - Encourage the partner to be tested for HIV ●Once HIV infection is established, providers should continually encourage and discuss - Risk and harm reduction - Safe sex practices Nguyen N, et al. Clin Interv Aging. 2008;3:453-472.

28 28 Program Overview ●Epidemiologic trends ●HIV screening/testing ●When to start therapy: mortality and prognosis ●Treatment options and treatment response ●Management considerations

29 29 When to Start Treatment Clinical Category CD4 Cell Count (cells/mm 3 ) Viral Load (copies/mL) 2009 DHHS Guidelines 2008 IAS-USA Guidelines AIDS-defining illness or severe symptoms* Any value Treat Asymptomatic<350Any valueTreat 350 to 500Any valueTreat*Consider treatment >350>100,000Treat*Consider treatment >350<100,000Treat*Consider treatment (some patients) >500Any valueTreat/Optional*Defer Pregnant womenAny value Treat HIV-associated nephropathy Any value Treat HIV/HBV coinfection when HBV treatment is indicated Any value Treat Available at: http://www.aidsinfo.nih.gov/ContentFiles/AdultandAdolescentGL.pdf. Revision December 1, 2009; Hammer SM, et al. JAMA. 2008;300:555-570. *New recommendation.

30 30 ART Cohort: Risk of Disease Progression Over 5 Years After Starting HAART Progression to AIDS or Death Hazard Ratio (95% CI) 16-29 (Reference) 1.00 HAART initiated at HIV RNA <200 cells/µL or diagnosis of AIDS. Baseline CD4 count, IDU use, and an AIDS diagnosis was prognostic for progression. HIV RNA level at baseline was not prognostic. 1.16 (1.02-1.32) Progression to Death May M, et al. AIDS. 2007;21:1185-1197. 0.99 (0.82-1.20) 1.32 (1.14-1.52) 1.12 (0.91-1.38) 1.62 (1.39-1.90) 1.92 (1.53-2.41) 30-3940-49 >50 Age at Baseline (years) Hazard Ratio (95% CI) 16-29 (Reference) 1.00 1.26 (1.01-1.58) 1.29 (0.97-1.73) 1.66 (1.31-2.11) 1.80 (1.33-2.45) 3.09 (2.41-3.95) 3.29 (2.39-4.54) 30-3940-49 >50 Age at Baseline (years) At start of HAART 6 months after HAART At start of HAART 6 months after HAART

31 31 NA-ACCORD: Risk of Death Associated With Deferred HAART Baseline CD4 351 to 500 Cells/mm 3 Relative Risk of Death (95% CI) Deferral of HAART Female Sex Older Age (per 10-year Increments) 1.69* (1.26-2.26) Baseline CD4 Count (per 100 cells/mm 3 ) *P<0.001 and † P=0.03. 1.68* (1.48-1.91) 1.21 (0.89-1.64) 1.13 (0.72-1.78) Baseline CD4 >500 Cells/mm 3 Relative Risk of Death (95% CI) Deferral of HAART Female Sex Older Age (per 10-year Increments) 1.94* (1.37-2.79) Baseline CD4 Count (per 100 cells/mm 3 ) 1.83* (1.62-2.06) 1.85* (1.33-2.59) 0.93 † (0.87-0.99) Kitahata MM, et al. N Engl J Med. 2009;360:1815-1836.

32 32 ATHENA Cohort Study: Restoring CD4 Count to >800 cells/mm 3 ●National observational study - 554 of 5299 previously treatment- naïve patients were on uninterrupted HAART for 7 years - Baseline CD4: 221 cells/mm 3 HIV RNA: 5.0 log 10 copies/mL ●Restoring CD4 >800 cells/mm 3 - Less time to achieve and a greater proportion achieving with a higher pre-HAART CD4 cell count >500 cells/mm 3 : 87% 350-500 cells/mm 3 :73% 200-350 cells/mm 3 : 46% 50 to 200 cells/mm 3 : 26% Gras L, et al. JAIDS. 2007;45:183-192. Median CD4 Cell Count (cells/mm 3 ) Weeks on HAART Achieving CD4 >800 cells/mm 3 0 48 96 144 192 240 288 336 >500 350-500 200-350 50-200 <50 Baseline CD4 Strata (cells/mm 3 )

33 33 Predictors of Plateauing CD4 Cell Count Between 5 and 7 Years After Initiating HAART Odds Ratio CD4 >800 Cells/mm3 At 5 Years 2.23 (1.10-4.51) Multivariate Odds Ratio (95% CI) Gras L, et al. JAIDS. 2007;45:183-192. 3.01 (1.60-5.67) 6.10 (2.12-17.51) HAART Initiation at >50 Versus <50 Years of Age Viremia in Years 5 to 7 Versus No Viremia ●Assess patients with HIV RNA <500 copies/mL between 6 months and 5 years of uninterrupted HAART ●Lower range of CD4 cell count plateau associated with older age (>50 years) at the start of HAART - Lower normal CD4 cell range reported in older healthy individuals - Lower thymic function ●It may be appropriate to start HAART in older patients earlier than in younger patients

34 34 Program Overview ●Epidemiologic trends ●HIV screening/testing ●When to start therapy: mortality and prognosis ●Treatment options and treatment response ●Management considerations

35 35 DHHS Guidelines: Preferred Regimens NNRTIEfavirenz 1 /emtricitabine 2 /tenofovir DF PIAtazanavir 3 + ritonavir + emtricitabine 2 /tenofovir DF Darunavir + ritonavir (qd) + emtricitabine 2 /tenofovir DF INSTIRaltegravir + emtricitabine 2 /tenofovir DF Pregnant women Lopinavir/r bid + zidovudine/lamivudine 2 INSTI: Integrase strand transfer inhibitors. 1 Efavirenz should not be used during the first trimester of pregnancy or in women trying to conceive or not using effective and consistent contraception. 2 Lamivudine may substitute for emtricitabine or visa versa. 3 Atazanavir + RTV should not be used in patients who require >20 mg omeprazole equivalent/day. Available at: http://www.aidsinfo.nih.gov/ContentFiles/AdultandAdolescentGL.pdf. Revision December 1, 2009.

36 36 DHHS Guidelines: Alternative Regimens NNRTIEfavirenz + (abacavir 1 or zidovudine)/lamivudine 2 Nevirapine 3 + zidovudine/lamivudine 2 PIAtazanavir + ritonavir + (abacavir 1 or zidovudine)/lamivudine 2 Fosamprenavir + ritonavir (qd or bid) + either ([abacavir 1 or zidovudine]/lamivudine 2 ) or emtricitabine 2 /tenofovir DF Lopinavir/r 4 (qd or bid) + either ([abacavir 1 or zidovudine]/ lamivudine 2 ) or emtricitabine 2 /tenofovir DF Saquinavir + ritonavir + emtricitabine 2 /tenofovir DF Available at: http://www.aidsinfo.nih.gov/ContentFiles/AdultandAdolescentGL.pdf. Revision December 1, 2009. 1 Abacavir should not be used in patients who test positive for HLA-B*5701. Use abacavir with caution in patients with high risk of cardiovascular disease or pretreatment HIV RNA >100,000 copies/mL. 2 Lamivudine may substitute for emtricitabine or visa versa. 3 Nevirapine should not be used in patients with moderate to severe hepatic impairment (Child-Pugh B or C); or in women and men with pre-antiretroviral therapy CD4 >250 and >400 cells/mm 3, respectively. 4 Once-daily lopinavir/r is not recommended in pregnant women.

37 37 IAS-USA Guidelines Recommendations for Treatment-Naïve Patients NNRTIPIDual NRTI PreferredEfavirenzLopinavir + ritonavirEmtricitabine/tenofovir DF 1 Atazanavir + ritonavirAbacavir/lamivudine 2 (if test negative for HLA-B*5701) Fosamprenavir + ritonavir Darunavir + ritonavir Saquinavir + ritonavir AlternativeNevirapineZidovudine/lamivudine Didanosine + emtricitabine Didanosine + lamivudine Select 1 NNRTI or 1 PI Plus a Dual NRTI 1 A baseline urinalysis and estimation of creatinine clearance or glomerular filtration rate for assessment of renal function are recommended. All patients receiving tenofovir should be observed for development of renal dysfunction. Lamivudine can be substituted for emtricitabine. 2 Emtricitabine can be substituted for lamivudine. Hammer SM, et al. JAMA. 2008;300:555-570.

38 38 COHERE Study ●Collaboration of Observational HIV Epidemiological Research Europe - Multi-cohort collaboration of 33 European cohorts ●Patients starting HAART (n=67,659) - Stratified by 10 age groups ( 60 years of age) ●Pre-HAART baseline in older patients - Distribution of HIV transmission categories similar with exception of IDU (lower in older versus younger patients) - Higher HIV RNA levels - Lower CD4 cell counts - Higher percentage of AIDS diagnoses 13 to 49 years of age: 18% to 29% >50 years of age: 32% to 33% COHERE Study Group. AIDS. 2008;22:1463-1473.

39 39 COHERE Study: Baseline Virologic and Immunologic Profile by Age Baseline HIV RNA HIV RNA (log 10 copies/mL) 13-17 4.8 18-2930-39 40-49 50-54 55-59 >60 4.8 5.0 5.1 4.9 COHERE Study Group. AIDS. 2008;22:1463-1473. Age at Baseline (years) CD4 (cells/mm 3 ) 13-17 222 18-2930-39 40-49 50-54 55-59 >60 256 188 178 173 210 Age at Baseline (years) Baseline CD4 Count

40 40 COHERE Study: HAART Response by Age 0 0.5 1.0 1.5 2.0 2.5 3.0 Time Since HAART (years) HIV RNA <50 Copies/mL Patients (%) COHERE Study Group. AIDS. 2008;22:1463-1473. Years of Age 18 to 29 (n=9134) 30 to 39 (n=22,410) 40 to 49 (n=11,580) 50 to 54 (n=2693) 55 to 59 (n=1656) >60 (n=1613) 0 0.5 1.0 1.5 2.0 2.5 3.0 Time Since HAART (years) CD4 Gain >100 Cells/mm 3 Patients (%) Years of Age 18 to 29 (n=9134) 30 to 39 (n=22,410) 40 to 49 (n=11,580) 50 to 54 (n=2693) 55 to 59 (n=1656) >60 (n=1613)

41 41 COHERE Study: Response by Baseline Age Achieving CD4 Count >200 Cells/mm 3 at 12 Months Patients (%) 13-17 85.6% 18-2930-39 40-49 50-54 55-59 >60 86.7% 76.3% 75.2% 73.9% 74.7% 80.5% COHERE Study Group. AIDS. 2008;22:1463-1473. Age at Baseline (years) Patients (%) 13-17 18-2930-39 40-49 50-54 55-59 >60 Age at Baseline (years) New AIDS Event At 12 Months P<0.0001 for trend 4.8% 5.2% 8.5% 9.6% 9.3% 7.0% 9.7% P<0.0001 for trend

42 42 COHERE Study: Continuation of HAART by Baseline Age COHERE Study Group. AIDS. 2008;22:1463-1473. Patients (%) 13-17 18-2930-39 40-49 50-54 55-59 >60 Age at Baseline (years) Discontinuation of All ARTs at 12 Months 15.3% 14.8% 9.2% 6.9% 7.9% 11.4% 7.3% P<0.0001 for trend ●Similar rates of discontinuing or switching >1 antiretroviral agent during the first 12 months of HAART ●Complete treatment discontinuation was rare - Lower rates were observed among those >40 years of age

43 43 Kaiser Permanente Northern California: Older Age and Response/Tolerability to HAART ●Retrospective, observational, cohort study of HIV patients with known dates of HAART initiation (n=5090) ●Patients >50 years of age at HAART initiation - Higher percentage with a CD4 count <200 cells/mm 3 and AIDS diagnosis - Higher modified Charlson comorbidity index scores - Higher levels of HAART adherence in the year after HAART initiation Baseline (years of age) 18-39 (n=2259) 40-49 (n=1834) >50 (n=997) CD4 <200 cells/mm 3 (%) 43.045.847.6* HIV RNA >10K copies/mL (%) 66.362.661.6 AIDS (%)61.769.472.1 † Adherence (%)83.785.788.9 † Modified Charlson Comorbidity Index score (%) 0 1-2 >3 80.0 18.3 1.7 76.0 21.9 2.1 68.5 † 27.2 † 4.3 † Silverberg MJ, et al. Arch Intern Med. 2007;167:684-691. *P=0.01 and † P<0.001.

44 44 Kaiser Permanente Northern California: Virologic Response and Age Achieving HIV RNA <500 Copies/mL at 12 Months Hazard Ratio (95% CI) 18-39 1.00 (Reference) 40-49 >50 Age at Baseline (years) Experiencing HIV RNA Rebound Within 2 Years *P=0.009 and † P=0.01. Adjusted for age only. Similar results when adjusted for all potential predictors. 0.97 (0.88-1.06) 1.15* (1.04-1.27) Hazard Ratio (95% CI) 18-39 1.00 (Reference) 40-49 >50 Age at Baseline (years) 0.81 † (0.69-0.96) 0.88 (0.73-1.06) Silverberg MJ, et al. Arch Intern Med. 2007;167:684-691.

45 45 Kaiser Permanente Northern California: Immunologic Response and Age 0 1 2 3 4 5 6 Time After HAART Initiation (years) CD4 Cell Count CD4 Count (cells/mm 3 ) Years of Age 18 to 39 (n=2259) 40 to 49 (n=1834) >50 (n=997) Silverberg MJ, et al. Arch Intern Med. 2007;167:684-691. P=0.001 P=0.07 P=0.66 ●CD4 gains 1 year after HAART initiation were lower in the older group (P=0.046) - 18-39 years of age +131.8 cells/mm 3 - 40-49 years of age +121.38 cells/mm 3 - >50 years of age +111.8 cells/mm 3 ●Despite blunted initial immunologic responses in the older group, CD4 counts were similar by year 3

46 46 Kaiser Permanente Northern California: Clinical Outcomes Rates per 1000 Person-Years Death AIDS-Defining Illnesses (hospitalizations) 28.8 47.4* 8.4 7.5 Age (years) <50 months (n=4094) <50 months (n=4094) >50 (n=997) >50 (n=997) Silverberg MJ, et al. Arch Intern Med. 2007;167:684-691. PCP Candidiasis AIDS Dementia Wasting Syndrome AIDS Diagnoses 28.5 36.4 † 2.3 5.9* 1.6 5.9* 2.3 7.2* *P<0.001 and † P=0.01 versus <50 years of age.

47 47 HAART and HIV in Older Persons ●Better adherence ●Similar virologic response ●Slower CD4 recovery in some cohorts ●Higher risk of progressing to AIDS ●Increased mortality Ledergerber B. 15 th CROI. Boston, 2008. Abstract 108. Grabar S, et al. J Antimicrob Chemother. 2006;57:4-7. Gebo KA. Drugs Aging. 2006;23:897-913. COHERE Study Group. AIDS. 2008;22:1463-1473.

48 48 Program Overview ●Epidemiologic trends ●HIV screening/testing ●When to start therapy: mortality and prognosis ●Treatment options and treatment response ●Management considerations

49 49 VACS Virtual Cohort: Comorbidities Among Older HIV-Infected Patients Patients (%) Any Comorbidity Hypertension DiabetesVascular Disease 19% Years of Age <40 (n=8522) 40 to 49 (n=14,561) 50-59 (n=7225) >60 (n=3122) 39% 53% 66% 7% 17% 30% 45% 2% 6% 12% 21% 1% 4% 11% 23% 5% 7% 11% 16% 5% 16% 17% 7% 1% 2% 4% 6% Pulmonary Disease Liver Disease Renal Disease Goulet JL, et al. Clin Infect Dis. 2007;45:1593-1601. Cross-sectional analyses of patient data from the VACS virtual cohort (1997-2004). Age was associated with all comorbidities except liver disease (P<0.001).

50 50 VACS Virtual Cohort: Comorbidities Among Older HIV-Infected Patients Patients (%) Any Substance Abuse/Dependence Disorder Alcohol DrugAny Psychiatric Disorder 21% Years of Age <40 (n=8522) 40 to 49 (n=14,561) 50-59 (n=7225) >60 (n=3122) 24% 35% 11% 16% 24% 18% 9% 18% 28% 5% 17% 15% 20% 19% 3% 9% 7% 4% 2% 12% 6% 11% 13% Schizophrenia Major Depression/ Bipolar Goulet JL, et al. Clin Infect Dis. 2007;45:1593-1601. Cross-sectional analyses of patient data from the VACS virtual cohort (1997-2004).

51 51 Incidence of CHD: Medi-Cal Claims Data of Patients With and Without HIV Disease CHD Incidence per 100 Patient Years Men 18-24 25-34 35-44 45-54 55-64 65-74 >75 18-24 25-34 35-44 45-54 55-64 65-74 >75 Age Category (years) Age Category (years) 1994-2000. *P<0.01; † P<0.05. Currier JS, et al. JAIDS. 2003;33:506-512. 18-24 25-34 35-44 45-54 55-64 65-74 >75 18-24 25-34 35-44 45-54 55-64 65-74 >75 Age Category (years) Age Category (years) Women HIV-infected (n=20,742) Non HIV-infected (n=970,259) HIV-infected (n=7771) Non HIV-infected (n=2,084,437) * * * * * † † † † CHD Incidence per 100 Patient Years

52 52 Risk of Coronary Heart Disease in HIV-Infected Persons: Medi-Cal Database ●Age-specific, covariate-adjusted, relative risk of coronary heart disease by antiretroviral drug exposure - Compared with treatment-naïve HIV- infected patients ●Adjusted for - Diabetes mellitus - Hyperlipidemia - Kidney disease - Hypertension ●The absolute risk of an MI is low in young patients, despite the high relative risk Currier JS, et al. JAIDS. 2003;33:506-512. Relative Risk (95% CI) Age category (y) 18-332.06* (1.42-2.99) 34-491.08 (0.91-1.28) 50-650.79 (0.63-1.00) >661.61 (0.65-2.04) *P<0.001 vs treatment-naïve HIV-infected patients. Relative Risk of CHD Among Treated HIV-Infected Patients

53 53 D:A:D Study: Incidence of Myocardial Infarction and Duration of HAART DAD Study Group, et al. N Engl J Med. 2007;356:1723-1735. Exposure (y): None 7 Exposure (y): None 7 No. of events 16 17 20 41 61 62 51 47 30 No. of events 16 17 20 41 61 62 51 47 30 No. of person-y 11,815 7105 9027 12,098 14,892 14,394 11,351 7935 5853 No. of person-y 11,815 7105 9027 12,098 14,892 14,394 11,351 7935 5853 Relative rate per additional year of exposure 1.16 (95% CI 1.09-1.23) Incidence per 1000 Person-Years

54 54 D:A:D Study: Risk Factors Associated With CVD-Related Mortality in HIV Patients ●HIV-infected patients (n=33,347) - Total deaths (n=2192) Cardiovascular-related: 11% - Follow-up 158,959 person-years ●Significant risk factors for cardiovascular-related mortality - Diabetes, hypertension, smoking, age, and HBV coinfection - Lower CD4 counts were associated with a higher risk of death ●Need to address modifiable risk factors to further reduce cardiovascular-related mortality Smith C, et al. 16 th CROI. Montreal, 2009. Abstract 145. Adjusted Rate Ratios for Cardiovascular Death (95% CI) Diabetes2.47 (1.76-3.47) Hypertension2.23 (1.69-2.94) Smoking1.57 (1.05-2.45) Age1.42 (1.35-1.49) HBV coinfection 1.38 (1.01-1.89)

55 55 HOPS Cohort: Risk Factors for CHD ●8024 outpatients (1993-2005) - 51 myocardial infarctions ●Myocardial infarction cases - Peaked in the year 2000 ●Statin use increased from 25% in 2005 ●Statin use was associated with a reduced risk of CHD among those with hyperlipidemia - Hazard ratio 0.34 (P=0.02) ●CHD risk was unrelated to specific antiretroviral agents or changes in antiretroviral therapy Lichtenstein K, et al. 13 th CROI. Denver, 2006. Abstract 735. Adjusted Odds Ratio Age >40 years3.31* Diabetes mellitus3.24* Hyperlipidemia1.95 † Hypertension1.73 ‡ Significant Independent Risk Factors for CHD CHD includes myocardial infarction, peripheral vascular disease, coronary artery disease, and stroke. *P<0.001; † P=0.024; ‡ P=0.059.

56 56 Abacavir and CVD Risk: Summary of Key Studies/Analyses Study Design Event Assessment Effect of Abacavir Found on CVD Risk D:A:D (n=33,347) Prospective, observational cohort Prospective, predefined Yes 1 FHDB (n=289 cases; 884 controls) Case control in observational cohort Prospective (validated retrospectively) Yes 1 (1 st year of exposure) SMART (n=2752) Randomized control trial, observational analysis Prospective, predefined Yes 1 STEAL (n=357) Randomized control trialProspectiveYes 1 QPHID (n=142 cases; 1420 controls) Case control in observational cohort ICD 9 code, acute MI not validated Yes 1 GSK analysis (n=14,174) Randomized control trials (n=54) Retrospective, database search No 2 ALLRT ACTG (n=3205) Randomized control trials (n=5) RetrospectiveNo 2 VACCR (n=19,424) Retrospective observational cohort ICD 9 code, acute MI not validated No 1 Behrens GM, et al. Curr Opin Infect Dis. 2010;23. [Epub ahead of print]. FHDB: French Hospital Databaseon HIV; QPHD: Quebec’s public health insurance database; VACCR: Veterans Administration’s Clinical Case Registry. 1 All or majority of patients were treatment-experienced at abacavir initiation. 2 All or majority of patients were treatment-naïve at abacavir inclusion.

57 57 VA Cohort: Abacavir Exposure and Acute MI Risk ●Retrospective study (n=19,424) - Follow-up 76,376 patient-years ●Events during period of observation - Acute MI (n=278) 3.69 (3.28-4.15) per 1000 patient-years - Cerebrovascular accidents (n=868) 11.68 (10.93-12.48) per 1000 patient-years Acute MI by Baseline CVD Risk Factors Acute MI (n=278) No Acute MI (n=19,146) Age (years)51*46 Male (%)9997 Smoking (%)3328 Diabetes(%)22*13 Hypertension(%)68*38 Hypercholesterolemia (%)41*26 CKD (eGFR <60 MDRD) (%) 18* 7 HCV (%)38 † 31 *P<0.0001 and † P=0.13 versus no acute MI. Bedimo R, et al. 5 th IAS Conference. Cape Town, 2009. Abstract MoAB202.

58 58 VA Cohort: Abacavir Exposure and Acute MI Risk ●Cumulative abacavir exposure - Marginal, non-statistically significant increase in risk of acute MI and cerebrovascular accidents - Association was attenuated by adjusting for traditional cardiovascular risk factors and renal dysfunction at baseline ●Abacavir in last regimen - No association with acute MI and cerebrovascular accidents ●3-fold increased risk of acute MI with renal insufficiency - Channeling effect: chronic kidney disease patients more likely to receive abacavir versus tenofovir DF Adjusted Risk of Acute MI per 1000 Patient-Years Patient- Years Risk of Acute MI HAART with abacavir 38811.18 (0.92-1.50) HAART with other NRTIs 25,0770.99 (0.87-1.11) Mono and dual antiretroviral therapy 66421.29* (1.10-1.52) Adjusted for traditional CVD risk factors (age, type 2 (diabetes, hyperlipidemia, hypertension, tobacco use). *P=0.002. Bedimo R, et al. 5 th IAS Conference. Cape Town, 2009. Abstract MoAB202.

59 59 Cardiovascular Disease and HAART ●Accumulating data indicate that HIV-infected patients on HAART may have an increased relative risk of CHD with longer exposure to therapy - The excess risk may depend in part on the presence of other risk factors - The role of HIV infection remains unclear

60 60 Cardiovascular Considerations in Antiretroviral Therapy ●Modification of coronary heart disease risk and use of antiretroviral agents that are less likely to cause metabolic disturbances may be warranted when patients have many options ●Fear of coronary heart disease should not preclude the use of effective HAART

61 61 Malignancies and HIV: Prevalence Trends Over the Past 10 years ●AIDS-related malignancies - Decreased Kaposi sarcoma and CNS lymphoma - Increased Non-Hodgkin lymphoma ●Non-AIDS defining malignancies - Overall incidence increased by >3-fold - Greatest increases seen in liver, larynx, anal, and lung cancers - No increase in prostate and breast cancers Mitsuyasu RT. Top HIV Med. 2008;16:117-121. Engels EA, et al. Int J Cancer. 2008;123:187-194. Patel P, et al. Ann Intern Med. 2008;148:728-736.

62 62 D:A:D Study: Risk Factors Associated With Non-AIDS Cancer Mortality in HIV Patients ●HIV-infected patients (n=33,347) - Total deaths (n=2192) Non-AIDS cancers: 12% - Follow-up 158,959 person-years ●Significant risk factors for non-AIDS cancers mortality - High BMI, smoking, and age - Lower CD4 counts were associated with a higher risk of death ●Need to address modifiable risk factors to further reduce non-AIDS cancer mortality Smith C, et al. 16 th CROI. Montreal, 2009. Abstract 145. Adjusted Rate Ratios for Non-AIDS Cancer Death (95% CI) High BMI (>26 kg/m 2 ) 4.08 (2.86-5.82) Smoking1.61 (1.06-2.46) Age1.42 (1.35-1.50)

63 63 Comorbidities and Older HIV Patients: Bone Disease ●SUN Study (CDC funded) - Low bone mineral density in 62% of patients receiving HAART Osteopenia: 52%; osteoporosis: 10% - Osteoporosis was associated with Older age, lower BMI, longer duration since HIV diagnosis, advanced HIV disease ●Initiation of HAART causes increased bone turnover without compensatory bone formation - Immune reconstitution or dysregulation of bone formation? - Secondary causes: vitamin D deficiency, hyperparathyroidism ●Treatment for low bone mineral density - Bisphosphonate therapy Bhavan KP, et al. Curr HIV/AIDS Rep. 2008;5:150-158.

64 64 Other Comorbidities in Older HIV-Infected Patients ●Increased pain ●Loss of muscle mass ●Decreasing glomerular filtration rate ●Hepatic dysfunction ●Neurocognitive dysfunction ●Immunosenescence Gebo KA. Drugs Aging. 2006;23:897-913. Bhavan KP, et al. Curr HIV/AIDS Rep. 2008;5:150-158.

65 65 Functional Issues With Aging and HIV ●Frailty phenotype (presence of >3 of the following) - Exhaustion, slowed walking speed, low activity level, weakness, and weight loss - Associated with poorer health outcomes ●MACS - A 55-year-old HIV-infected person has similar frailty as a 65-year- old HIV-negative person ●Proposed mechanisms - Mitochondrial dysfunction and increased number of free radicals and cytokines activate inflammatory pathways, ultimately leading to frailty Gebo KA, et al. Curr Infect Dis Rep. 2009;11:246-254. Desquilbet L, et al. J Gerontol A Biol Sci Med Sci. 2007;62:1279-1286. Oursler KK, et al. AIDS Res Hum Retroviruses. 2006;22:1113-1121.

66 66 HIV in Persons of Advanced Age: Summary ●HIV population is aging ●Providers should ask all patients about high-risk behaviors and educate them on the risks ●Presentation of HIV in older persons may be different than in your patients ●Older patients have more severe HIV course, more opportunistic infections and malignancies, shortened survival, and shorter AIDS-free intervals

67 67 HIV in Persons of Advanced Age: Summary ●Current HAART therapy is effective in reducing HIV disease progression and mortality - Consider starting HAART earlier in older patients Similar virologic response as with younger patients, but slower CD4 cell recover ●Consider the potential risk of exacerbating comorbidities of older patients when choosing antiretroviral therapy ●Higher adherence rates in older HIV-infected patients is a key factor to overcome potential obstacles to a robust response - Increased risk of adverse events, higher comorbidity burden, and possible age-related immune senescence


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