1

Metabolic Risk Factors in HIV-Infected Patients David A. Wohl, MD Associate Professor of Medicine School of Medicine Co-Principal Investigator AIDS Clinical Trial Unit University of North Carolina at Chapel Hill Chapel Hill, North Carolina

3 Educational Objectives Interpret study data on the association between HIV, ART, and cardiovascular disease (CVD) to evaluate risk in HIV-infected patients Interpret study data on the association between HIV, ART, and cardiovascular disease (CVD) to evaluate risk in HIV-infected patients Assess the evidence of association between ARVs and dyslipidemia, fat changes, and insulin disturbances to recognize metabolic complications in HIV-infected patients Assess the evidence of association between ARVs and dyslipidemia, fat changes, and insulin disturbances to recognize metabolic complications in HIV-infected patients Formulate strategies for the identification, assessment, and monitoring of CVD risk in HIV-infected patients, including control of dyslipidemia, body fat changes, and insulin resistance Formulate strategies for the identification, assessment, and monitoring of CVD risk in HIV-infected patients, including control of dyslipidemia, body fat changes, and insulin resistance On completion of this activity, participants should be able to:

ART and CVD Risk

5 CHD Risk Factors in HIV-Infected Population HIV Infection ART ? CHD Risk - - Diabetes *Metabolic syndrome Lipids* Family History Abdominal Obesity* Hyper- tension* Cigarette Smoking Hyper- glycemia Insulin Resistance* Inactivity, Diet AgeGender Orange = Modifiable Green = Nonmodifiable

6 Studies on CVD Risk in HIV-Infected and ART-Treated Patients StudyN EventARVEffectTraditional Risk Factors VA 1 36,766R 1,207 CHD ART or PINoNot evaluated HOPS P 84 CV events Specific ARVsNoAge >40 y, diabetes, HTN SMART p63 CHD Intermittent ART No – stopping therapy led to complication Age Kaiser R86 MI PIs Risk of HIV+ vs HIV- No risk on PI Not evaluated Medi-Cal 4 28,513RNA ART Risk with ART in 18–33-year-olds Not evaluated DAD 2 23,490P345 MI cART and PIYesSmoking, age, gender, HTN, DM French 5 34,976R49 MI PIYesAge Johns Hopkins Case control 43 CHD HIV+ vs HIV-YesAge, HTN, DM Frankfurt R29 MI ARTYesAge >40 y 1. Bozzette SA. N Engl J Med. 2003;348: Friis-Møller N. 13th CROI Denver. # Klein D. 13th CROI Denver. # Rickerts V. Eur J Med Res. 2000;5: Lichtenstein K. 13th CROI Denver. # El-Sadr W et al. 13th CROI Denver. #106LB. 4. Currier JS. JAIDS. 2003;33: Mary-Krause M. AIDS. 2003;21: Moore RD. 10th CROI Boston. #132.

7 HOPS Cohort Risk Category Adjusted OR (P Value) Age >40 y 3.31 (<0.001) Diabetes Diabetes 3.24 (<0.001) Hyperlipidemia 1.95 (0.024) Hypertension 1.73 (0.059) Nadir HDL 0.97 (0.004) Lichtenstein K et al. 13th CROI Denver. Abstract 735. Multivariate Analysis of Risk Factors for CVD (N=1807; CVD cases=57)

8 D:A:D Study: Incidence of MI Friis-Moller N et al. N Engl J Med. 2007;356: A Small Increase in Incident CVD Is Associated With Duration of Combination Antiretroviral Therapy RR per Year of ART Overall1.16 Men1.13 Women1.36 Exposure to ART (y) Incidence of MI per 1000 PY None 10 < >7

9 Veterans Affairs: Cardiovascular Admissions Bozzette SA et al. N Engl J Med. 2003;348: No ART 0<22–4>4 CVD Admissions per 100 PY NRTIs + PIs NRTIs + NNRTIs ART Use (y)

10 Contribution of Dyslipidemia to MI Risk *Adjusted for conventional risk factors (sex, cohort, HIV transmission group, ethnicity, age, BMI, family history of CVD, smoking, previous CVD events, lipids, diabetes, and hypertension). † Unadjusted model. Relative Rate of MI* (95% CI) 0.72 (0.52–0.99); P=0.05* 1.58 (1.43–1.75); P<0.001 † 1.26 (1.19–1.35); P<0.001* 1.10 (1.01–1.18); P=0.002 * 1.00 (0.93–1.09); P=0.92* Total cholesterol (per mmol/L) Triglycerides (per log 2 mmol/L higher) HDL cholesterol (per mmol/L) PI exposure (per additional year) NNRTI exposure (per additional year) Friis-Moller N et al. N Engl J Med. 2007;356:

11 SMART Study: Uncontrolled HIV Replication Increases the Risk of CVD El-Sadr W et al. 13th CROI Denver. Abstract 106LB. CD4 + guided drug conservation (DC) strategy associated with CD4 + guided drug conservation (DC) strategy associated with significantly greater disease progression or death compared with significantly greater disease progression or death compared with continuous viral suppression (VS): RR 2.5 (95% CI, 1.8–3.6; P<0.001) continuous viral suppression (VS): RR 2.5 (95% CI, 1.8–3.6; P<0.001) Includes increased CVD-, liver-, and renal-related deaths and nonfatal Includes increased CVD-, liver-, and renal-related deaths and nonfatal CVD events CVD events Severe Complications Endpoint and Components Subgroups P With Events (no.) Relative Risk 95% CI Severe complications CVD, liver, renal deaths Nonfatal CVD events (ECG changes included) Nonfatal hepatic events Nonfatal renal events VS Better DC Worse

12 Summary The is a strong correlation between LDL-C and CVD risk The is a strong correlation between LDL-C and CVD risk HDL-C is an independent predictor of CVD HDL-C is an independent predictor of CVD Combination HIV therapies are associated with increased risk of CVD, but recent data suggest that uncontrolled HIV infection is also a risk for CV events Combination HIV therapies are associated with increased risk of CVD, but recent data suggest that uncontrolled HIV infection is also a risk for CV events Further, traditional CVD risk factors, including some that can be changed (smoking), may have a greater impact on CVD risk than ART Further, traditional CVD risk factors, including some that can be changed (smoking), may have a greater impact on CVD risk than ART

Lipid Effects of ART

14 HIV Seroconversion and ART Years Mean Level (mg/dL) TC LDL HDL Pre-ART PreseroconversionART Mean Lipid Values Before and After HIV Infection and Treatment From MACS Riddler SA et al. JAMA. 2003;289: Nonfasting values Recommended NCEP values

15 RTV 100 mg BID x 14 d ► 7 d Washout ► LPV/r x 14 d Shafran SD et al. HIV Med. 2005;6: Metabolic Effects of Low-Dose Ritonavir in (HIV–) Healthy Volunteers ParameterBaseline RTV 100 mg BID LPV/r 400/100 mg BID N Total cholesterol (mg/dL) *197* LDL (mg/dL) 97113*120* HDL (mg/dL) 5451*53 Triglycerides (mg/dL) 7798*114* *P ≤0.01 change from baseline.

16 KLEAN: FPV + RTV vs LPV/r SGC + (ABC + 3TC) Eron J et al. Lancet. 2006;368:476–482. Fasting Lipid Levels at Week TCLDLHDLTG Fasting Lipid Levels (mg/dL) FPV + RTV at BL FPV + RTV at Wk 48 LPV/r at BL LPV/r at Wk 48

17 GEMINI: GEMINI: LPV/r vs SQV + RTV + (TDF/FTC) Median Lipid Parameters at Week 24 Walmsley S et al. IAS Sydney. Australia. Abstract TUPEB TCLDLHDLTG Median Plasma Lipids (mg/dL) SQV + RTV LPV/r Median change

18 Smith K et al. 8th International Congress on Drug Therapy in HIV Infection Glasgow, Scotland. Abstract P1. ALERT: RTV-Boosted Once-Daily FPV vs ATV + (TDF + FTC) Baseline n= Week 24 n= Median Fasting Lipids at Baseline and Week 24 Lipid Levels (mg/dL) Triglycerides Cholesterol HDLLDL FPV/r Baseline Week 24 ATV/rFPV/rATV/rFPV/rATV/rFPV/rATV/r

Total Cholesterol HDL Cholesterol Fasting LDL Cholesterol Fasting Triglyceride Non-HDL Cholesterol ATV 300 RTV Baseline ATV 300 RTV Week 96 ATV 400 Baseline ATV 400 Week 96 Median Value (mg/dL) mg/dL 130 mg/dL 40 mg/dL 150 mg/dL 190 mg/dL Study 089: ATV vs ATV + RTV + (d4T + 3TC) McComsey GA et al. 11th EACS Madrid, Spain. Abstract P9.3/04. Mean Change in Lipids

20 REDUCE: 100 vs 200 mg of RTV + (ABC/3TC) REDUCE: Once-Daily FPV With 100 vs 200 mg of RTV + (ABC/3TC) Similar Change in Mean Fasting Lipids 100 Week 48 Lipid Measure (mg/dL) FPV/r- 100 FPV/r- 200 FPV/r- 100 FPV/r- 200 FPV/r- 100 FPV/r- 200 FPV/r- 100 FPV/r- 200 Baseline Triglycerides Cholesterol HDL LDL Wohl D et al. 4th IAS Sydney, Australia. Poster TUPEB080.

21 A5142: LPV/r + EFV vs LPV/r + 2 NRTIs vs EFV + 2 NRTIs * * * * *Statistically significant difference with other 2 arms, P ≤0.01. P =0.023 P ≤0.01 NS By week 96, 10% and 12% of EFV and LPV subjects used a lipid-lowering agent. Median Change From Baseline (mg/dL) Haubrich R et al. 14th CROI Los Angeles, CA. Abstract TCHDLNon-HDLTG EFVLPV/rLPV/r + EFV Median Changes in Lipids From Baseline – Week 96

22 A5142: LPV/r + EFV vs LPV/r + 2 NRTIs vs EFV + 2 NRTIs P <0.05 By week 96, 10% and 12% of EFV and LPV subjects used a lipid-lowering agent. Median Change From Baseline (mg/dL) TCHDLNon-HDLTG d4TZDVTDF Median Changes in Lipids by NRTI From Baseline – Week 96 Haubrich R et al. 14th CROI Los Angeles, CA. Abstract 38.

23 Study 934: ZDV/3TC vs TDF + FTC Pozniak AL et al. JAIDS. 2006;43: Mean Change From Baseline (mg/dL) Study Week TDF + FTC + EFV ZDV/3TC + EFV Triglycerides Fasting LDL P =0.12 TDF + FTC + EFV ZDV/3TC + EFV P =0.067 Mean Change Lipid Profile

24 2NN Study: EFV vs NVP + (d4T + ZDV) *P<0.05; † P<0.001 for EFV vs NVP arm. Change From Baseline (%) Total Cholesterol LDL HDL Triglycerides TC/ HDL 31% 40% 34%* 49% † 6% † 27% 35% 43% 20% –4% – EFV NVP van Leth F et al. PLoS Med. 2004;1: Lipid Effects of NNRTIs

Insulin Resistance

26 Insulin Resistance Failure of target organs to respond normally to the action of insulin  Ability of insulin to store exogenous glucose (muscle/fat)  Ability of insulin to suppress endogenous glucose production (liver)

27 Diabetes and Insulin Resistance in HIV Infection Type 2 diabetes secondary to insulin resistance Type 2 diabetes secondary to insulin resistance Usually asymptomatic Usually asymptomatic Prevalence of type 2 diabetes Prevalence of type 2 diabetes Random glucose 1%–2% Random glucose 1%–2% OGTT 6%–10% OGTT 6%–10% Impaired glucose tolerance extra 15%–30% Impaired glucose tolerance extra 15%–30% Associations Associations Lipoatrophy and fat accumulation Lipoatrophy and fat accumulation  Age  Age Grinspoon S et al. N Engl J Med. 2005;352:48-62.

28 Diabetes Risk Factors Insulin Resistance  Obesity (abdominal)  Physical inactivity  Genetic – Family history – Race/ethnicity  Older age  Dyslipidemia  Peripheral lipoatrophy  Reduced adiponectin  Increased liver/muscle fat  Inflammatory cytokines  Low testosterone  Oxidant stress  HCV infection  Protease inhibitors Potential HIV- Associated Risk Factors Classic Type 2 Diabetes Risk Factors

29 Impact of Various PIs on Glucose and Glucose Disposal Rate PI 2-Hour OGTT Single-Dose Study CLAMP 5-Day CLAMP 10-Day CLAMP 4-Week CLAMP IDV No data  LPV/r  ATV/r  ATV  APV  1. Noor MA et al. AIDS. 2001;15:F11-F18; 2. Dubé MP et al. JAIDS. 2001;27: ; 3. Behrens G et al. AIDS. 1999;13:F63-F70; 4. Martinez E et al. AIDS. 1999;13: ; 5. Walli RK et al. Eur J Med Res. 2001;6: ; 6. Noor MA et al. AIDS. 2002;16:F1-F8; 7. Dubé MP et al. Clin Infect Dis. 2002;35: ; 8. Sension M et al. Antivir Ther. 2002;7:L26; 9. Noor MA et al. AIDS. 2004;18: ; 10. Lee GA et al. Clin Infect Dis. 2006;43:

Body Shape Changes

31 Body Fat Changes Two phenotypes described in HIV-infected patients Two phenotypes described in HIV-infected patients Lipoatrophy Lipoatrophy Strongest association with thymidine analogues Strongest association with thymidine analogues Metabolic effects incompletely described but may contribute to insulin resistance Metabolic effects incompletely described but may contribute to insulin resistance Visceral adiposity Visceral adiposity Weight gain common initially with all ART Weight gain common initially with all ART Unclear association with specific ART Unclear association with specific ART

32 Lipoatrophy vs Wasting Syndrome Lipoatrophy is characterized by the loss of subcutaneous fat in face, buttocks, abdomen, and limbs Lipoatrophy is characterized by the loss of subcutaneous fat in face, buttocks, abdomen, and limbs Lean tissue (muscle) is not lost Lean tissue (muscle) is not lost In wasting syndrome, both fat, lean tissue, and weight diminish In wasting syndrome, both fat, lean tissue, and weight diminish

33 Lipoatrophy — Facial Mild Moderate Severe Mild Moderate Severe

34 Lipoatrophy: Risk Factors Almost certainly interrelated Almost certainly interrelated Antiretroviral therapy Antiretroviral therapy Thymidine analogue exposure (d4T >ZDV) Thymidine analogue exposure (d4T >ZDV) Combinations of ART (eg, EFV + NRTIs, NFV + NRTIs) Combinations of ART (eg, EFV + NRTIs, NFV + NRTIs) Host factors Host factors Age Age HIV disease factors HIV disease factors Duration of illness Duration of illness Severity of illness: AIDS, low CD4 + cell count Severity of illness: AIDS, low CD4 + cell count

35 Lipohypertrophy Lipohypertrophy is characterized by an increase in fat depots — typically visceral, dorsocervical, and breast tissue fat Lipohypertrophy is characterized by an increase in fat depots — typically visceral, dorsocervical, and breast tissue fat Subcutaneous fat (pinch an inch fat) does not increase Subcutaneous fat (pinch an inch fat) does not increase Difficult to distinguish from general “lipohypertrophy” associated with modern living Difficult to distinguish from general “lipohypertrophy” associated with modern living

HIV+ patient with obesity. Subcutaneous fat is thick and fat in the abdomen is scant. HIV+ patient with visceral adiposity. Subcutaneous fat is scant and fat in the abdomen is thick. CT Scans of Two HIV+ Patients Subcutaneous Fat (pinch an inch fat) Visceral Fat (dark shaded areas) Images courtesy of D.A. Wohl.

P <0.001 Upper back Abdominal fat WaistChestNeckLegsButtocksArmsFaceCheeks 0 P <0.001 P =0.055 P =0.090 P =0.055 P =0.31 P =0.47 Lipoatrophy Prevalence Distribution in HIV+ vs HIV– Controls FRAM Study Group. JAIDS. 2005;40: FRAM Study Group. J AIDS. 2006;42: P <0.001 P =0.058 P =0.22 P =0.004 P =0.025 P =0.053 Upper Back Abdominal Fat Waist ChestNeckLegsButtocksArmsFaceCheeks 0 Men Women HIV Control Percentage Reporting Fat Loss

38 Upper back Abdominal fat WaistChestNeckLegsButtocksArmsFaceCheeks P =0.039 P <0.044 P <0.001 P <0.009 P =0.43 P =0.13 P =0.17 P =0.54 FRAM Study Group. J AIDS. 2005;40: FRAM Study Group. J AIDS. 2006;42: P =0.011 P <0.001 P =0.003 P <0.001 P =0.32 P =0.001 P =0.048 P =0.003 P =0.40 Upper back Abdominal fat WaistChestNeckLegsButtocksArmsFace Cheeks P =0.34 Men Women HIV Control Percentage Reporting Fat Gain Lipohypertrophy Prevalence Distribution in HIV+ vs HIV– Controls Percentage Reporting Fat Gain

39 FRAM: Lipoatrophy and Lipohypertrophy Do Not Consistently Present Together FRAM Study Group. JAIDS. 2005;40: FRAM Study Group. J AIDS. 2006;42: Peripheral Lipoatrophy (%) P=0.10 P <0.001 Central Lipohypertrophy Central Lipoatrophy NoYes Central Lipohypertrophy Central Lipoatrophy P=0.006 Men (n=425) Women (n=183) Peripheral Lipoatrophy Was Associated With Central Lipoatrophy, NOT Central Lipohypertrophy Peripheral Lipoatrophy (%)

40 Study 613: LPV/r + ZDV/3TC Followed by LPV/r Monotherapy LPV/r EFV CategoryLPV/rEFV P Value Lipoatrophy5%34%<0.001 Lipohypertrophy45%44%>0.99 Both0%16%0.002 Lipohypertrophy Lipoatrophy Both Change in Limb Fat (%) Change in Trunk Fat (%) Lipoatrophy and Lipohypertrophy at Week 96 Cameron DW et al. 14th CROI. 2007; Los Angeles, Calif. Abstract 44.

41 MACS: Increase in Waist Size in HIV+ Men May Be Return to “Normal” NRTIs associated with BMI ; NNRTIs and PIs are not NRTIs associated with BMI  ; NNRTIs and PIs are not Cumulative NRTI exposure associated with significant decreases in waist, hip, thigh circumferences Cumulative NRTI exposure associated with significant decreases in waist, hip, thigh circumferences Significant increases in BMI, waist, hip circumference observed each year of follow-up, regardless of HIV status Significant increases in BMI, waist, hip circumference observed each year of follow-up, regardless of HIV status Baseline waist circumference lower in HIV+ men; increased more rapidly than in HIV– controls Baseline waist circumference lower in HIV+ men; increased more rapidly than in HIV– controls Suggests increased waist may reflect return to “normal” Suggests increased waist may reflect return to “normal” Brown T et al. International AIDS Conference Toronto, Canada. Abstract WEPE0136.

42 Body Fat Redistribution Trends Over Time on ART Mallon PW et al. AIDS. 2003;17: Median Change From Baseline Value (%) Central Abdominal Fat Limb Fat Time Since ART Initiation (wk) N=40 The Example of Thymidine Analogue Containing Regimen That Has Become Dogma

43 GS 903 and GS 934: TDF vs d4T + (EFV+3TC) and TDF + FTC vs ZDV/3TC + (EFV) Gallant JE et al. JAMA. 2004;292: ; Pozniak AL et al. JAIDS. 2006;43: Week Study 903 Week Study *P<0.001 TDF + 3TC + EFV d4T + 3TC + EFV Mean Limb Fat (kg) 8.6* * 8.1 †‡ *P=0.034 † P<0.001 § P= TDF + FTC + EFV ZDV/3TC + EFV Total Limb Fat (kg) * † § * ‡ P=0.01 Differential Effect of NRTIs on Total Limb Fat

44 Komarow L et al. International AIDS Conference Toronto, Canada. Abstract WEPE0167. ACTG 5005s: PI vs No PI + (ZDV/3TC) Change in Extremity Fat (%) Week No PI PI Fitted Lines DEXA Substudy: DEXA Substudy: Change in Limb Fat

45 Median Change From Baseline in Extremity Fat Through 96 Weeks P Values at Week 96 LPV/r + EFV vs LPV: LPV/r + EFV vs EFV: <0.001 LPV/r vs EFV: EFV LPV/r LPV/r + EFV Trunk fat increased 12%–16% and was not different across randomized groups (P >0.05) Median Change in Extremity Fat (%) Haubrich R et al. 14th CROI Los Angeles, CA. Abstract Weeks on Study EFVLPV/rLPV/r + EFV

46 Lipoatrophy (>20% Loss of Extremity Fat) at Weeks 48 and Weeks on Study Lipoatrophy (% with >20% loss) EFV LPV/r LPV/r + EFV P Values at Week 96 LPV/r + EFV vs LPV/r: LPV/r + EFV vs EFV: <0.001 LPV/r vs EFV: % 17% 32% 7% 10% 21% EFV LPV/r LPV/r + EFV Haubrich R et al. 14th CROI Los Angeles, CA. Abstract 38.

Weeks on Study d4T ZDV TDF Lipoatrophy at Weeks 48 and 96 (NRTI Arms Only) 16% 8% 26% 27% 9% 42% P Values at Week 96 ZDV vs TDF: <0.001 d4T vs TDF: <0.001 d4T vs ZDV: d4T TDF ZDV Lipoatrophy (% with >20% loss) Haubrich R et al. 14th CROI Los Angeles, CA. Abstract 38.

48 Proportion of Subjects With Lipoatrophy at Week 96 Within Subgroups Model includes randomized arm and NRTI, for NRTI-containing regimens only VariableOR (95% CI)P Value EFV vs LPV/r2.7 (1.5 – 4.6) <0.001 d4T vs ZDV1.9 (1.1 – 3.5)0.029 TDF vs ZDV0.24 (0.1 – 0.5) <0.001 n=41 n=43 n=63 n=73 n=67 n=50 Logistic Regression for Lipoatrophy at Week 96 Patients Haubrich R et al. 14th CROI Los Angeles, CA. Abstract 38.

Mean Change in Body Fat RTV Appears to Protect Against Lipoatrophy Mean Change From Baseline in Body Fat Through Week 96 (%) ATV RTV Limb Fat ATV RTV Trunk Fat ATV 400 Limb Fat ATV 400 Trunk Fat Study Week Study 089: ATV vs ATV + RTV + (d4T + 3TC) McComsey GA et al. 11th EACS Madrid, Spain. Abstract P9.3/04.

50 Study 089: ATV vs ATV + RTV + (d4T + 3TC) ATV RTV ATV 400 P < Week 96 Week 48 Proportion of Patients (%) Lipoatrophy Defined as ≥20% Fat Loss vs Baseline by CT or DEXA McComsey GA et al. 11th EACS, Madrid, Spain. Abstract P9.3/04.

51 LPV/r Monotherapy Maintenance vs EFV + ZDV/3TC in Limb Fat Changes EFV + ZDV/3TC LPV/r P <0.001 ~2.3 kg LPV/r: N= EFV: N= Week Median Change in Limb Fat (%) EFV + ZDV/3TC LPV/r LPV/r + ZDV/3TC Cameron D et al. 14th CROI Los Angeles, CA. Abstract 44LB.

52 Trunk Fat Changes Median Change in Trunk Fat (%) LPV/r + ZDV/3TC EFV + ZDV/3TC LPV/r N = EFV N = Time (weeks) ~1.1 kg No Significant Difference in Trunk Fat at Week 96 Cameron D et al. 14th CROI Los Angeles, CA. Abstract 44LB.

53 Psychosocial Impact Self-evaluated quality of relationships with friends, family, sexual partner is inversely associated with self- perception of peripheral fat loss in HIV/AIDS outpatients (N=457) 1 Self-evaluated quality of relationships with friends, family, sexual partner is inversely associated with self- perception of peripheral fat loss in HIV/AIDS outpatients (N=457) 1 A survey of HIV/AIDS patients with body fat changes (N=33) 2 demonstrated an association with: A survey of HIV/AIDS patients with body fat changes (N=33) 2 demonstrated an association with: Social withdrawal Social withdrawal Adversely affected sexual relationships Adversely affected sexual relationships Forced disclosure of HIV status due to facial lipoatrophy Forced disclosure of HIV status due to facial lipoatrophy Depression Depression Poor body image Poor body image Low self-esteem Low self-esteem ART noncompliance ART noncompliance Economic impact of surgical interventions Economic impact of surgical interventions Belief that body changes were more challenging than Belief that body changes were more challenging than living with HIV living with HIV 1.Santos CP et al. AIDS. 2005;19(suppl 4):S14-S Santos CP et al. AIDS. 2005;19(suppl 4):S14-S Collins E et al. AIDS Reader. 2000;10:

54 Conclusions In the largest prospective cohort study, CVD is associated with ART but absolute risk is low In the largest prospective cohort study, CVD is associated with ART but absolute risk is low Other traditional risks for CVD are also prevalent, including those that can be modified Other traditional risks for CVD are also prevalent, including those that can be modified Cessation of ART has been associated with increased CVD risk Cessation of ART has been associated with increased CVD risk NRTIs, NNRTIs, and PIs have varying effects on lipids, insulin resistance, and fat distribution changes NRTIs, NNRTIs, and PIs have varying effects on lipids, insulin resistance, and fat distribution changes Boosted PIs are associated with increased prevalence of dyslipidemia, although evidence suggests that RTV contributes substantially to lipid effects Boosted PIs are associated with increased prevalence of dyslipidemia, although evidence suggests that RTV contributes substantially to lipid effects

55 Conclusions Fat disturbances in HIV-infected patients are multifactorial Fat disturbances in HIV-infected patients are multifactorial Lipoatrophy and lipohypertrophy do not commonly occur together Lipoatrophy and lipohypertrophy do not commonly occur together Two recent comparative studies suggest that risk of lipoatrophy is lower with a ritonavir-boosted PI than an NNRTI and an unboosted PI Two recent comparative studies suggest that risk of lipoatrophy is lower with a ritonavir-boosted PI than an NNRTI and an unboosted PI Abdominal fat increases are common to all ART regimens studied so far Abdominal fat increases are common to all ART regimens studied so far Selection between DHHS-recommended regimens should consider the differential effects on many factors, including lipids and body fat distribution Selection between DHHS-recommended regimens should consider the differential effects on many factors, including lipids and body fat distribution

Assessing and Managing Metabolic Complications and CVD Risk Ross J. Simpson, Jr, MD, PhD Professor of Medicine University of North Carolina School of Medicine Clinical Professor of Epidemiology School of Public Health Director, Preventive Cardiology Clinic Principal Clinical Coordinator Medical Review of North Carolina Chapel Hill, North Carolina

57 Educational Objectives On completion of this activity, participants should be able to: Interpret study data on the association between HIV, ART, and cardiovascular disease (CVD) to evaluate risk in HIV-infected patients Interpret study data on the association between HIV, ART, and cardiovascular disease (CVD) to evaluate risk in HIV-infected patients Assess the evidence of association between ARVs and dyslipidemia, fat changes, and insulin disturbances to recognize metabolic complications in HIV-infected patients Assess the evidence of association between ARVs and dyslipidemia, fat changes, and insulin disturbances to recognize metabolic complications in HIV-infected patients Formulate strategies for the identification, assessment, and monitoring of CVD risk in HIV-infected patients, including control of dyslipidemia, body fat changes, and insulin resistance Formulate strategies for the identification, assessment, and monitoring of CVD risk in HIV-infected patients, including control of dyslipidemia, body fat changes, and insulin resistance

ART and CVD Risk

59 Cardiac Risk Factors What are cardiac risk factors? What are cardiac risk factors? Increased age Increased age Sex (men are at higher risk) Sex (men are at higher risk) Smoking Smoking Elevated LDL cholesterol (LDL) Elevated LDL cholesterol (LDL) Low HDL cholesterol (HDL) Low HDL cholesterol (HDL) Hypertension Hypertension Presence of diabetes (or risk equivalent) Presence of diabetes (or risk equivalent) How to define cardiac risk and need for intervention How to define cardiac risk and need for intervention Persons with 2 or more risk factors are at increased risk of coronary heart disease (CHD) Persons with 2 or more risk factors are at increased risk of coronary heart disease (CHD) Risk assessment tools can be used to calculate percent of CHD risk Risk assessment tools can be used to calculate percent of CHD risk Wilson PW et al. Circulation. 1998;97:

60 Multiple Risk Factors: INTERHEART Odds Ratio (99% CI) 2.9 ( ) 2.4 ( ) 1.9 ( ) 3.3 ( ) 13.0 ( ) 42.3 ( ) 68.5 ( ) ( ) ( ) Smoke (1) DM (2) ApoB/A1 (4) 1+2+3All 4+Obesity All Risk Factors HTN (3) Risk Factor (adjusted for all others) +Psycho- social Yusuf S et al. Lancet. 2004;364: Multiple Traditional Risk Factors Confer Synergistic Increase in Risk of MI in General Population

61 Traditional Factors Contribute Most to Coronary Heart Disease in HIV Population Diabetes *Metabolic syndrome. Orange = Modifiable. Green = Nonmodifiable. Insulin Resistance* HIV Infection ART ? Coronary Heart Disease RISK Lipids* Family History Abdominal Obesity* Hypertension* Cigarette Smoking Hyperglycemia Inactivity & Diet Age Gender

62 CVD Risk Assessment Algorithms Tools to Predict the 10-Year Risk of MI 1. Wilson PW et al. Circulation. 1998;97: ; 2. Assmann G et al. Circulation. 2002;105: Framingham Score 1 PROCAM 2 Age ++ Smoking status ++ Presence of diabetes (or risk equivalent) –+ Treatment for HTN (if SBP >120 mm Hg) +– Blood pressure ++ MI in family history –+ TC +– HDL ++ LDL –+ TGs –+

63 CVD Risk in HIV-Infected Patients Observed Predicted Duration of ART (y) MI Incidence per 1000 PY < Incidence of MIs is low: 345 over 94,469 patient-years (PY) of follow-up (3.7/1000 PY) Law MG et al. HIV Med. 2006;7: Observed and Predicted MI Incidence According to Framingham Risk Equation in the D:A:D Study

64 Estimating CVD Risk Summary Possible to estimate risk of CVD disease using mathematical algorithms based on outcomes of large cohorts with long-term follow-up Possible to estimate risk of CVD disease using mathematical algorithms based on outcomes of large cohorts with long-term follow-up Total estimated risk is influenced by calculated non-HDL cholesterol, age, gender, blood pressure, smoking status, and other factors Total estimated risk is influenced by calculated non-HDL cholesterol, age, gender, blood pressure, smoking status, and other factors

65 Cardiovascular Risk Factors and ART: Interventions Dyslipidemia Dyslipidemia Specific interventions for dyslipidemia Specific interventions for dyslipidemia Lipid-lowering agents Lipid-lowering agents Statins Statins Fibrates Fibrates Niacin Niacin Change antiretroviral therapy Change antiretroviral therapy

Assessment and Management of Dyslipidemia

67 Approach to Dyslipidemia: IDSA Guidelines Obtain fasting lipid profile prior to starting ARVs and within 3-6 months of starting new regimen Count number of CVD risk factors in profile and determine level of risk. If ≥2 risk factors, perform a 10-year risk calculation Intervene for modifiable nonlipid risk factors such as diet and smoking If above the lipid threshold based on risk group despite vigorous lifestyle interventions, consider altering ARV therapy or lipid-lowering drugs Serum LDL cholesterol above threshold or TG mg/dL with elevated non-HDL cholesterol: STATIN Serum TG >500 mg/dL: FIBRATE LIPID-LOWERING DRUG THERAPY Evaluation and Management of Dyslipidemia in HIV-Infected Patient Dubé M et al. Clin Infect Dis. 2003;37:

68 Lipids and CVD Risk Increasing plasma LDL increases relative risk of CHD A 30 mg/dL ↑ in LDL is associated with ~30% ↑ CHD risk Relative Risk of CHD (log scale) 3.7 LDL Cholesterol (mg/dL) Grundy SM et al. Circulation. 2004;110:

69 Higher HDL Reduces Cardiovascular Risk at All LDL Levels 1 mg/dL increase in HDL reduces CVD risk by 2% in men and 3% in women 1 Low HDL cutoffs: <40 mg/dL for men; <50 mg/dL for women 2 1. Gordon T et al. Am J Med. 1977;62: ; 2. Gordon DJ et al. Circulation. 1989;79:8-15. LDL (mg/dL) HDL (mg/dL) Relative Risk of CHD Framingham Heart Study – 10-Year Risk for CHD Event

70 Hypertriglyceridemia Is Independently Associated With CVD Group No. of Studies RR Associated With ↑ 88 mg/dL 95% Confidence Interval Men –1.39 Women –2.07 USA –1.50 Scandinavia –1.65 Other Europe –1.34 Cullen P. Am J Cardiol. 2000;86: RR=relative risk.

71 Drugs Used in the Treatment of Dyslipidemia Statins Inhibit intrinsic production of cholesterol Risk of interaction with PIs Risk of skeletal muscle and hepatic toxicities Fibrates Augment lipoprotein lipase activity (  VLDL) Lower TG levels, increase HDL Concomitant use with statins may increase risk of muscle and hepatic toxicities Others Ezetimibe, bile acid sequestrants, nicotinic acid, fish oil, etc

72 Lipid-Lowering Therapy Overview Nicotinic Acid LDL  , TG , HDL  Side effects: flushing, hyperglycemia, hyperuricemia, upper GI distress, hepatotoxicity Statins LDL , TG , HDL  Side effects: myopathy,  liver enzymes Fibric Acids LDL , TG , HDL  Side effects: dyspepsia, gallstones, myopathy Ezetimibe LDL , TG , HDL  Side effects:  liver enzymes, diarrhea Omega-3 Fatty Acids LDL , TG  , HDL  Side effects: GI, taste Bile Acid Sequestrants LDL , TG , HDL  Side effects: GI distress/ constipation,  absorption of other drugs

73 Balancing ART and Lipid-Lowering Agents Fibrates Fluvastatin Pravastatin* Low Interaction Potential Statin- Fibrates Atorvastatin Rosuvastatin Lovastatin Simvastatin Use Cautiously Contraindicated With PIs Balancing Lipid Management With ART in HIV-Infected Patients Potential Drug–Drug Interactions With PIs Dubé M et al. Clin Infect Dis. 2003;37: ; Van Der Lee M et al. 13th CROI Denver, CO. Abstract 588; Prezista [package insert]. Raritan, NJ: Tibotec Therapeutics; *Not recommended with darunavir/ritonavir.

74 HOPS: Lipid-Lowering Agent Use Use of lipid-lowering agents associated with lower CVD risk in HIV+ patients with hyperlipidemia Patients on Anti-HTN or LLA (%) Incidence MI/1000 PY HR adj 95% CI P Value – Lichtenstein K et al. 13th CROI Denver, CO. Abstract 735. Anti-HTN= antihypertensive agent; LLA= lipid-lowering agent.

75 ACTG 5087: Efficacy and Safety of Fenofibrate vs Pravastatin in HIV+ Subjects Aberg J et al. AIDS Res Hum Retroviruses. 2005;21:757–767. Percent Responder * Single=monotherapy with either fenofibrate or pravastatinFeno=fenofibrate Prav=pravastatin Dual=combination therapy with fenofibrate and pravastatinD-Feno=fenofibrate initiation in combination therapy D-Prava=pravastatin initiation in combination therapy *P=0.04 for dual-arm comparison. * NCEP III Composite Response (LDL/HDL/TG)

76 Group A – fish oil, then add fenofibrate Group B – fenofibrate, then add fish oil Gerber J et al. 13th CROI Denver, CO. Abstract 146. ACTG 5186: Fish Oil and Fenofibrate 665 * * 338 Fasting Serum Triglycerides (ITT) – Step 1 * Fasting Serum Triglycerides (ITT) – Step Mean Serum Triglycerides (mg/dL) Single Drug Fish oil+Feno Group A Group A combo Group B Group B combo * * Pre-fish oil Post-fish oil Pre-fenofibrate Post-fenofibrate Mean Serum Triglycerides (mg/dL) *P<0.05.

77 ACTG A5148: Long-Acting Niacin Treatment of Hyperlipidemia in HIV+ Patients Baseline Week 48 Change Lipid profile (mg/dL) Triglycerides478–153 * Total cholesterol253–8.1 * HDL † LDL217–19.0 * Insulin sensitivity (mU/Lmmol/L) HOMA ‡ *P<0.001; † P= 0.002; ‡ P= Dube MP et al. Antivir Ther. 2006;11:

78 LDL and TC Results After Adding Ezetimibe *P<0.05 vs baseline. Total CholesterolLDLTriglyceridesHDL Change From Baseline (%) Week 6 Week 12 Week * * * * * * Klibanov OM et al. IAS Sydney, Australia. Poster TUPEB076.

79 Improvement in Lipid Levels Observed With LLAs vs Switching PI Therapy PI  NVP PI  EFV Add pravastatin Add bezafibrate Calza L et al. AIDS. 2005;19: Triglycerides Months Mean Plasma TGs (mg/dL) Months Total Cholesterol Mean Total Cholesterol (mg/dL)

80 D:A:D Study: Lipid Changes After Starting LLT or Switch From a PI to an NNRTI 12-Month Change in Lipid Profile Van der Valk M et al. 8th International Congress on Drug Therapy in HIV Infection; 2006; Glasgow, Scotland. Abstract PL12.2. Change (mmol/L) Total Cholesterol LDL TG HDL TC:HDL Ratio Control SwitchLLT LLT= lipid-lowering therapy.

81 Insulin Resistance and Body Fat Changes

82 American Diabetic Association Definitions PrediabetesDiabetes Mellitus Fasting glucose 100–125 mg/dL ≥126 mg/dL 2-hr post load glucose during oral glucose tolerance test (OGTT) 140–199 mg/dL ≥200 mg/dL Symptoms of diabetes with random glucose of ≥200 mg/dL American Diabetes Association. Diabetes Care. 2007;30(suppl 1):S4-S44.

83 D:A:D―Is Diabetes a CHD Risk Equivalent in HIV-Infected Patients? Worm SW et al. Lipodystrophy Workshop. July 19–21, 2007; Sydney, Australia. Abstract O-09. History of CHD and/or DM +CHD/+DM , Events PYFU –CHD/-DM +CHD/–DM –CHD/+DM Incidence Rate/1000 PY

84 Insulin Resistance Management Thiazolidinediones Thiazolidinediones  Subcutaneous fat 23±10%;  VAT 21±8% 1  Subcutaneous fat 23±10%;  VAT 21±8% 1  Leg subcutaneous fat; improved insulin sensitivity 2  Leg subcutaneous fat; improved insulin sensitivity 2  Insulin levels; no effect on SAT or VAT 3  Insulin levels; no effect on SAT or VAT 3  Subcutaneous fat,  OGTT 34 mg/dL 4  Subcutaneous fat,  OGTT 34 mg/dL 4 Rosiglitazone did not improve LA,  TGs 5 Rosiglitazone did not improve LA,  TGs 5 Metformin Metformin  Insulin and visceral fat 6,7  Insulin and visceral fat 6,7  Waist circumference; weight loss 7  Waist circumference; weight loss 7  Waist circumference, SAT, VAT, TAT,  OGTT 20 mg/dL but 32% GI AEs 4  Waist circumference, SAT, VAT, TAT,  OGTT 20 mg/dL but 32% GI AEs 4 1. Gelato MC et al. JAIDS. 2002;31: ; 2. Hadigan C et al. Am J Clin Nutr. 2003;77: ; 3. Sutinen J et al. Antivir Ther. 2003;8: ; 4. van Wijk JP et al. Ann Intern Med. 2005;143: ; 5. Carr A et al. Lancet. 2004;363: ; 6. Saint-Marc T et al. AIDS. 1999;13:1000; 7. Hadigan C et al. JAMA. 2000;284:

85 Lipohypertrophy Relative Visceral Fat Gain Lipoatrophy Subcutaneous Fat Loss Limbs Visceral abdominal fat accumulation Breasts Dorsocervical fat pad Lipomas Face SQ abdomen Buttocks Body-Fat Abnormalities Defining Metabolic Complications Carr A et al. AIDS. 1998;12:F51; Grinspoon S, Carr A. N Engl J Med. 2005;352:48; Carr A et al. Lancet. 1999;353: ; Haubrich R et al. 14th CROI Los Angeles. Abstract 38; Boyd MA et al. J Infect Dis. 2006;194:642. Dyslipidemia Low HDL Cholesterol Disorders of Glucose Metabolism Insulin resistance Glucose intolerance Diabetes Hyper- triglyceridemia Not all patients will have these features. Lactate

86 Assessment Tools Clinical methods Clinical methods Clinical assessment Clinical assessment Anthropometry Anthropometry Research methods Research methods Dual-energy x-ray absorptiometry (DEXA) Dual-energy x-ray absorptiometry (DEXA) Computed tomography (CT) Computed tomography (CT) Magnetic resonance imaging (MRI) Magnetic resonance imaging (MRI) Levine J et al. J Appl Physiol. 2000;88:452; Kamel E et al. Obes Res. 2000;8:36; Mitsiopoulos N et al. J Appl Physiol. 1998;85:115.

87 Clinical Assessment Facial lipoatrophy grading   Grade 1: Mild/localized. Appearance almost normal   Grade 2: Deeper, longer central cheek atrophy. Facial muscles (especially zygomaticus major) beginning to show through   Grade 3: Deeper, wider atrophic area. Muscles clearly showing   Grade 4: Widespread atrophy. Facial skin lies directly on muscles over wide area, extending toward orbital region Grinspoon S, Carr A. N Engl J Med. 2005;352:48; James J et al. Dermatol Surg. 2002;11:979–986. Progression of Lipoatrophy

88 Pharmacologic Interventions Have Limited Efficacy and Present Risks Adapted from Sutinen J. Curr Opin Infect Dis. 2005;18: InterventionLipids Insulin Resistance Central Adiposity Lipoatrophy rGHWorse ReducedWorse MetforminBetter Reduced Worse Glitazones=/WorseBetter==/Better Pravastatin Cholesterol Better No change Better Uridine HDL worse (lower) No changeIncreasedBetter Additional data on the role of NNRTIs in fat changes are required. rGH= recombinant growth hormone.

89 Smoking Cessation

90 APROCO Cohort (HIV+)MONICA Sample (HIV–) Blood Glucose ≥126 mg/dL NS P< Smoking P<0.01 Hypertension Percent Patients NS P< HDL <40 mg/dL LDL >160 mg/dL N=223 HIV+ men and women on PI-based regimens vs 527 HIV– male subjects: N=223 HIV+ men and women on PI-based regimens vs 527 HIV– male subjects: – HIV+ patients have lower HDL and higher TG – Predicted risk of CHD > in HIV+ men (RR=1.2) and women (RR = 1.6), P in HIV+ men (RR=1.2) and women (RR = 1.6), P< Savès M et al. Clin Infect Dis. 2003;37:292–298. Incidence of Smoking Is Increased Among HIV-Infected vs General Population

91 Smoking Cessation: Nonpharmacologic Therapy Interventions Interventions Identify reasons for quitting Identify reasons for quitting Discuss options Discuss options Set a quit date, chosen by the patient Set a quit date, chosen by the patient Set up a support system Set up a support system Identify rationalizations Identify rationalizations Define slip vs relapse Define slip vs relapse Identify alternatives for cravings Identify alternatives for cravings Provide reliable sources of information Provide reliable sources of information Refer to local smoking cessation programs Refer to local smoking cessation programs

92 Nicotine Replacement Therapy DrugActionCostDosing OTC GumFast acting $ Wk 1–6 1 q 1–2 h Wk 7–9 1 q 2–4 h Wk 10–12 1 q 4–8 h LozengeFast acting $ lozenges Wk 1–6 1 q 1–2 h Wk 7–9 1 q 2–4 h Wk 10–12 1 q 4–8 h PatchSlow acting $ wk kit Step 1 21 mg X 6 wk Step 2 14 mg X 2 wk Step 3 7 mg X 2 wk Prescription Inhaler 10 mg cartridge Fast acting $ inhaler Wk 1–12 6–16 cart/day (max 40/day) Wk 13–24 Gradual taper Nasal spray 1 dose=2 spraysFast acting $ bottle (100 doses) Wk 1–8 1–2 doses/h (min 8/d) Wk 9–14 Gradual taper Available at:

93 Smoking Cessation: Pharmacologic Therapy Drug Dosing Bupropion SR Days 1 – mg QD Day 4 – end of treatment 150 mg BID Hepatic impairment Max: 150 mg QD Varenicline Days 1 – mg QD Days 4 – mg BID Day 8 – end of treatment 1 mg BID Physician's Desk Reference. Available at

94 Conclusions CVD risk in patients with HIV infection can be estimated on modifiable and nonmodifiable risk factors CVD risk in patients with HIV infection can be estimated on modifiable and nonmodifiable risk factors Smoking, hypertension, insulin resistance, and dyslipidemia should be monitored and managed to reduce CVD Smoking, hypertension, insulin resistance, and dyslipidemia should be monitored and managed to reduce CVD Lipids are an important component of CVD risk, but dyslipidemia occurs in context of other risk factors, all of which should be considered Lipids are an important component of CVD risk, but dyslipidemia occurs in context of other risk factors, all of which should be considered Body fat changes are significant in treatment success and potentially affect adherence, quality of life, and psychosocial well-being Body fat changes are significant in treatment success and potentially affect adherence, quality of life, and psychosocial well-being Limited interventions are available for managing body fat changes Limited interventions are available for managing body fat changes Interventions to control dyslipidemia include lifestyle changes, pharmacotherapy (statins, fibrates, others), and switching ART Interventions to control dyslipidemia include lifestyle changes, pharmacotherapy (statins, fibrates, others), and switching ART