Cardiovascular Disease in HIV-Infected Patients.Predict It and Prevent It.2015

Cardiovascular Disease in HIV-Infected Patients: Predict It and Prevent It

This program is supported by an educational grant fromBristol-Myers Squibb

clinicaloptions.com/hivCardiovascular Disease in HIV-Infected Patients: Predict It and Prevent It

Faculty

Priscilla Y. Hsue, MDProfessor of Medicine University of California at San FranciscoSan Francisco General HospitalSan Francisco, California

David A. Wohl, MDAssociate Professor of Medicine School of MedicineSite Leader, AIDS Clinical Trials Unit-Chapel HillUniversity of North Carolina at Chapel HillDirector, North Carolina AIDS Training and Education CenterChapel Hill, North CarolinaCo-Director for HIV ServicesNorth Carolina Department of CorrectionRaleigh, North Carolina


Disclosures

Priscilla Y. Hsue, MD, has disclosed that she has served on the advisory boards for Bristol-Myers Squibb, Gilead Sciences, and Merck and has received honoraria from Gilead Sciences.

David A. Wohl, MD, has disclosed that he has received consulting fees from Gilead Sciences and Janssen and funds for research support from Gilead Sciences and Merck.


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Overview

Epidemiology of cardiovascular disease in the setting of HIV

Monitoring and assessing CVD risk in HIV-infected pts

Inflammatory markers and imaging techniques and how they help elucidate effects of ART on CVD risk

Role of antiretrovirals in CVD risk

The role of statins in HIV-infected pts with CVD

Epidemiology of CVD in the Setting of HIV


Rates of CVD are Higher in HIV-Positive Pts HIV associated with a 50% increased acute MI risk after

adjustment for major traditional risk factors

Increased risk remained among those with well-treated HIV

Impact of HIV on risk comparable to traditional risk factors including HTN, DM, and hyperlipidemia

Drivers of CVD in HIV may include a combination of factors including a higher prevalence of traditional (eg, smoking) and nontraditional (eg, stress) risks, the effects of ART, and the effects of HIV itself

Freiberg MS, et al. JAMA Internal Medicine. 2013;173:614-622.


The Link Between HIV and CVD

Rate of acute MI higher in HIV-positive pts[1]

HIV infection is a risk factor for ischemic stroke[2]

HIV-infected men have a greater prevalence of coronary artery plaque[1,3]

1. Triant VA, et al. J Clin Endocrinol Metab. 2007;92:2506-2512. 2. Chow FC, et al. J Acquir Immune Defic Syndr. 2012;60:351-358. 3. Post WS, et al. Ann Intern Med. 2014;160:458-467.

Acu

te M

Is p

er

1000

PY

s

18-34 35-44 45-54 55-64 65-740

20

40

80

100

60

HIV-positive pts

HIV-negative pts

Age (yrs)


CVD and Mortality in HIV

Second leading non-HIV cause of death in US (~ 15%)[1] and third in Europe (~ 8%)[2]

Deaths due to CVD range from 6% to 15% in different cohorts[1-4]

As HIV-related deaths has decreased, rate of CVD death has increased[5]

– However, absolute rates of MI and stroke have declined with CVD risk factor reduction, use of ART regimens with better lipid effects, and improvements in immunocompetence[6-9]

In the US, HIV-infected individuals hospitalized for MI

– Have a higher mortality compared with controls (HR: 1.38; P = .04)

– Have lower rates of procedures[10]

1. Palella FJ, et al. J Acquir Immune Defic Syndr. 2006;43:27-34. 2. Lewden C, et al. J Acquir Immune Defic Syndr. 2008;48:590-598. 3. Smith CJ, et al. Lancet. 2014;384:241-248. 4. Sackoff JE, et al. Ann Intern Med. 2006;145:397-406. 5. Hanna D, et al. CROI 2014. Abstract 729. 6. Klein DB, et al. CROI 2014. Abstract 737. 7. Klein DB, et al. Clin Infect Dis. 2015;60:1278-1280. 8. Marcus JL, et al. CROI 2014. Abstract 741. 9 Marcus JL, et al. AIDS. 2014;28:1911-1919. 10. Pearce D et al AM J Cardiol 2012.


D:A:D: CVD Deaths Decreased in Era of Modern ART

Smith C, et al Lancet. 2014:384:241-248.

Most Common Causes of Death, 1999-2011

100908070605040302010

0

All

Dea

ths

(%)

Total(N = 3909)

1999-2000(n = 256)

2001-02(n = 788)

2003-04(n = 862)

2005-06(n = 718)

2007-08(n = 658)

2009-11(n = 627)

AIDS relatedLiver related

CVD relatedNon-AIDS cancer

OtherUnknown


Evolution of CVD With Aging HIV-Infected Population As the HIV-infected population continues to age, new

cardiovascular issues are emerging

1980 1990 2000 2010 2020

Pericardial effusion Dilated cardiomyopathy

Coronary artery disease Peripheral vascular disease Pulmonary HTN

Diastolic dysfunction Sudden cardiac death Atrial fibrillation

Pre-ART ARTContinuous ARTEarlier initiation of ART


Sudden Cardiac Death in HIV

HIV-positive pts (n = 2860) at San Francisco General Hospital between 2000-2009 – 230 deaths; 30 (13%) were SCD

SCDs accounted for 86% of all cardiac deaths (30 of 35) HIV SCD rate: 2.6/1000 person-yrs (> 4 times general population)

Tseng ZH, et al. J Am Coll Cardiol. 2012;59:1891-1896.

Why is the rate of SCD higher in HIV?How can we predict at-risk individuals?

How do we prevent this?

50

40

30

20

10

0

Mo

rtal

ity

per

10

00

PY

s

2001 2002 2003 2004 2005 2006 2007 2008 2009Yr

AIDSSCD


Chronic Inflammation and Increased Risk for Comorbidities in HIV-Positive Pts

Untreated HIV Infection

Loss of immunoregulatory cells HIV replication Loss of gut mucosal integrity and microbial translocation

Decreased but persistent chronic inflammation, immune activation,

elevated coagulation markers, microbial translocation, and increased risk of coinfection

Increased incidence of comorbidities and clinical disease

ART

Traditional comorbidity risk factors, such as dyslipidemia, smoking, lipodystrophy, HTN, obesity, substance use

Deeks SG. Annu Rev Med. 2011;62:141-155.


Biomarkers of Inflammation Are Elevated in HIV-Positive Pts, Even When on ART

*Adjusted for age, race, smoking, hepatitis C infection, obesity, diabetes and MACS site. †Error bars represent 99.7% CIs, calculated with Bonferroni adjustment to maintain a family-wise error rate of 0.05. Filled markers represent statistical significance (P < .002).

Adjusted Percentage Differences in Biomarkers of Inflammation and Immune Activation in HIV-Positive Pts and Uninfected Individuals*†

(MACS, 1984-2009)

Dif

fere

nce

(%

)

CXCL10sC

D27IL

-10

sIL-2

RαIL

-2sT

NFR2IF

N-γCXCL13

TNF-αIL

-12p

70sI

L-6R

BAFFCCL2

IL-6

sCD14

GM

-CSF

CCL11CRPIL

-1β

sGP13

0IL

-8CCL13CCL17CCL4

100

60

0

-40

80

40

-20

-60

20

HIV suppressed relative to ART naive

HIV suppressed relative to HIV uninfected

Wada NI, et al. AIDS. 2015;29:463-471.


SMART: High Levels of Inflammation Markers Associated With Risk of CVD

Time-to-event methods were used to study associations of the baseline level of IL-6, hsCRP, and D-dimer with a CVD event

*IL-6 quartiles are < 1.10, 1.10-1.76, 1.77-3.01, > 3.01 pg/mL.†hsCRP quartiles are < 0.72, 0.72-1.71, 1.72-4.17, > 4.17 μg/mL.‡D-dimer quartiles are < 0.13, 0.13-0.21, 0.22-0.37, > 0.37 μg/mL.

Quartile 1 (low) Quartile 2 Quartile 3 Quartile 4 (high)

Time From Randomization (Mos)

Duprez DA, et al. PLoS One. 2012;7:e44454.

IL-6*(n = 5037)

hsCRP†

(n = 5095)D-dimer‡

(n = 5069)

Cu

mu

lati

ve P

arti

cip

ants

Wit

h C

VD

Eve

nt

(%)

P < .001 P < .001P < .00115

5

10

0

20

0 8 16 24 324 12 20 28 36 4440 48 0 8 16 24 324 12 20 28 36 4440 48 0 8 16 24 324 12 20 28 36 4440 48


Ryom L, et al. CROI 2015. Abstract 742.

D:A:D Renal Disease and CVD

Kaplan-Meier Progression to CVD by Confirmed Baseline eGFR25

20

15

10

5

0

Per

cen

tag

e W

ith

CV

D

Mos After Baseline720 12 24 36 48 60

Baseline (confirmed) eGFR≤ 30> 30 - ≤ 60> 60 - ≤ 90> 90

Pts Under Follow-up, n> 90> 60 - ≤ 90> 30 - ≤ 60≤ 30

24,605915598746

24,023890793739

22,376831383530

20,895768176026

18,979697764922

15,631598952413

13,0015134444

8


Low CD4+ Cell Count and Traditional CVD Risk Factors Predictive of Primary MI Low CD4+ cell count independently predicts primary MIs

– Detectable HIV-1 RNA associated with primary MI risk at CD4+ cell counts

≥ 350 and ≥ 500 cells/mm3

– Traditional CVD risk factors are important predictors of primary MIsModel Adjusted Risk of Primary MI*

Unweighted CD4 models

CD4 < 100 1.95 (1.13-3.36)

CD4 < 200 1.69 (1.07-2.67)

CD4 < 350 1.36 (0.88-2.08)

CD4 < 500 1.26 (0.79-2.01)

CD4 and HIV-1 RNA models (reference: ≥ threshold and undetectable HIV-1 RNA)

CD4 ≥ 350 and detectable HIV-1 RNA 1.81 (1.17-2.81)

CD4 ≥ 500 and detectable HIV-1 RNA 1.61 (1.03-2.54)

*Adjusted for age, sex, tobacco, IDU, MSM, diabetes, statin use, treated hypertension, eGFR, ART.

Drozd DR, et al. CROI 2014. Abstract 739.

Monitoring and Assessing CV Risk in HIV


Assessing CV Risk in HIV Pts

Clinical

Monitoring lipids

Assessing traditional risk factors

HIV-related factors

Research

Coronary artery calcium score

CIMT

Markers of endothelial function

FDG-PET

Markers of inflammation


Comparison of Clinical CVD Risk Calculators: Input

CharacteristicACC/AHA

ASCVD

Framingham

SCORE QRISK2 JBS3 ASSIGNMI CVD

Diabetes ✓ ✓ ✓ ✓ ✓

Race/ethnicity ✓ ✓ ✓

Social deprivation ✓ ✓ ✓

Hypertension therapy ✓ ✓ ✓ ✓ ✓

BMI ✓ ✓ ✓ ✓

Family history of prematureCVD/CHD

✓ ✓ ✓ ✓

Chronic kidney disease ✓ ✓

Atrial fibrillation ✓ ✓

Rheumatoid arthritis ✓ ✓ ✓

Age, sex, smoking, lipids, blood pressure included in all models

Preiss D, et al. Can J Cardiol. 2015;31:613-619.


Comparison of CVD Risk Calculators: 10-Yr Prediction Output

EventACC/AHA

ASCVD

Framingham

SCORE QRISK2 JBS3 ASSIGNMI CVD

Fatal or nonfatal ASCVD ✓ ✓ ✓

CHD, TIA or stroke, or CVD death

✓ ✓

Fatal or nonfatal MI ✓

Fatal CVD ✓

Lifetime prediction ✓

Chance of survival free of MI or stroke

✓

Fatal or nonfatal ASCVD ✓

Preiss D, et al. Can J Cardiol. 2015;31:613-619.


1. Regan S, et al. CROI 2015. Abstract 751. 2. Thompson-Paul A, et al. CROI 2015. Abstract 747.

5-Yr Predicted Rate (%)

Framingham Risk Score[1]

5-Y

r E

ven

t R

ate

(%

)

5-Y

r E

ven

t R

ate

(%

)

ACC/AHA CVD Risk Calculator[1]

5-Yr Predicted Rate (%)

Observed

Predicted

Observed

Predicted

CVD Outcomes Underestimated in HIV-Positive Pts by Risk Calculators CVD risk scores calculated with data from 2006-2009 for pts in Partners HealthCare

System Cohort[1]

n = 2270 n = 215225

20

15

10

5

0< 2.5 2.5-4.9 5.0-7.4 7.5-9.9

25

20

15

10

5

0< 2.5 2.5-4.9 5.0-7.4 7.5-9.9

An outpatient study cohort (n = 2392) had similar findings of underestimated CVD risk (15% to 25%)[2]


Reducing CVD Risk Factors Can Decrease Risk of CVD in Older HIV+ Pts Effective treatment of modifiable risk factors, such as smoking,

cholesterol, and BP can significantly reduce an individual’s CVD risk

*Reduced by 1 mmol/L. †Reduced by 10 mm Hg.

Rel

ati

ve

Haz

ard

of

Dev

elo

pin

g C

VD

0

6

2

4

5

3

40 45 50 55 60 65Age (Yrs)

Model for Change in Relative Risk of CVD From Smoking Cessation, Reducing Cholesterol,* or Reducing Systolic BP† in a Cohort of 24,323 HIV-Positive Pts Without Prior CVD (D:A:D Study)

Reducing cholesterol

Reducing systolic BP

Smoking cessation

Petoumenos K, et al. HIV Med. 2014;15:595-603.


Aspirin and CVD

Secondary prevention: Pts with established CAD, TIA/CVA: dose 75 mg-162 mg/day (up to 325 mg for some pts)[1]

– Definitive benefit in MI, stroke, and CV death

Primary prevention less clear: “Consider 75-162 mg/day for pts at higher risk, especially those with 10-yr risk of CHD ≥ 10% whose risk of bleeding is not increased”[2]

– Reduces risk of first MI

– No reduction in rates of stroke or CV death

– Balance increase bleeding vs benefit

Aspirin, HIV, and MI: study in Boston, use of aspirin in HIV not associated with lower MI rates but limitations of study [3]

1. Smith SC, et al. Circulation. 2006;113:2363-2372. 2. Pearson TA, et al. Circulation. 2002;106:388-391. 3. Suchindran S, et al. Open Forum Infect Dis. 2014;1:ofu076.


The Role of CV Risk Analysis Tools in HIV-Infected Pts ACC/AHA ASCVD

– User-friendly

– Analysis can be done using online tool or via mobile phone app

– Indicates if pt cannot be assessed because risk is too low

– Provides 10-yr and lifetime risk assessment

Inflammatory Markers and Imaging Techniques and How They Help Elucidate Effects of

ART on CV Risk


Markers of Inflammation, Vascular Imaging:What They Are and What They Tell UsInflammatory and coagulation markers

hsCRP, IL-6, D-dimer

Imaging: CV Risk and progression of atherosclerosis

Carotid ultrasound: CIMT

Carotid CT: CAC and CTA

Brachial artery reactivity testing: FMD and endothelial function

PET and arterial inflammation


Chronic Inflammation Persists in the Setting of Treated HIV Infection T-cell activation higher in treated HIV vs controls[1,2]

Lipopolysaccharide higher in treated HIV vs controls[2]

Tissue factor elevated in treated HIV vs controls[3]

Many biomarkers of chronic inflammation elevated in HIV suppressed pts vs uninfected[4]

1. Hunt PW, et al. J Infect Dis. 2003;187:1534-1543. 2. Brenchley JM, et al. Nat Med. 2006;12:1365-1371. 3. Funderburg NT, et al. Blood. 2010;115:161-167. 4. Wada NI, et al. AIDS. 2015;29:463-471.


Pts With Sustained Viral Suppression Had Lower Levels of T-Cell Activation Than Untreated Pts but Higher Levels Than Uninfected Controls

T-Cell Activation Persists Despite Viral Suppression With ART

Hunt PW, et al. J Infect Dis. 2003;187:1534-1543.

30

20

10

0Act

ivat

ed C

D4+

T C

ells

(%

)

HIV Infected, Untreated

(n = 13)

HIV Infected, Treated(n = 99)

HIVUninfected

(n = 6)

P < .001

P < .001

75

50

25

0Act

ivat

ed C

D8+

T C

ells

(%

)

HIV Infected, Untreated

(n = 13)

HIV Infected, Treated(n = 99)

HIVUninfected

(n = 6)

P < .001

P < .001


Plasma IL-6 Levels Correlated With Incidence of Mortality SMART and ESPRIT trials

19,000 person-yrs of follow-up among 4304 pts (median age: 42 yrs; median CD4+ cell count: 526; 77% men)

– 157 all-cause deaths

– 117 non-AIDS deaths

– 101 progressions to AIDS

– 121 CVD

– 99 NADM

Baseline plasma IL-6 was a stronger predictor of all cause mortality and many fatal non-AIDS events than D-dimer and hsCRP

Adjustment attenuated the associations but IL-6 remained significant including for CVD

Borges A, et al. CROI 2015. Abstract 761.

Crude Incidence of Clinical Outcomes by Plasma IL-6

25

20

15

10

5

0Cru

de

In

cid

ence

Ra

tes

per

10

00 P

YF

U (

95%

CI)

Events, n 14 21 35 87 6 16 23 72 15 26 24 36 13 21 33 54 10 19 28 42

AIDS CVD NADM

All Cause Death

Non-AIDS/Violent/

Accidental Death

1st quartile

2nd quartile

3rd quartile

4th quartile


Role of Monocytes in Atheromatous Plaque Development HIV in conjunction with pro-atherogenic lipids up-regulates

adhesion molecules on endothelia

HIV activates monocytes

– Increase monocyte transmigration

– Increase uptake of oxLDL

– Promote differentiation into foam cells

– And contribute to atherosclerotic plaque formation

Campbell J, et al. AIDS. 2014;28:2175-2187.


Recent Carotid Studies in HIV

IMT progression occurs at bifurcation region and is associated with hsCRP in HIV[1]

VCAM-1 and CD14dim16- associated with carotid IMT in HIV[2]

Carotid IMT and hsCRP associated with all cause death in HIV[3]

FRAM study: Association of HIV with IMT similar to that of traditional risk factors like smoking[4]

1. Hsue PY, et al. J Am Heart Assoc. 2012;1:pii: jah3-e000422. 2. Barbour JD, et al. Atherosclerosis. 2014;232:52-58. 3. Mangili A, et al. Atherosclerosis. 2011;214:468-473. 4. Grunfeld C, et al. AIDS. 2009; 23:1841-1849.


HIV and Carotid IMT in MACS/WIHS Cohorts 1.6-fold greater risk of new plaque formation in HIV-positive vs HIV-negative individuals (RR: 1.61;

95% CI: 1.12-2.32), adjusting for cardiometabolic factors Increased plaque occurred even among persistently virologically suppressed HIV-positive

individuals vs uninfected individuals (RR: 1.56; 95% CI: 1.07-2.27) HIV-positive individuals with BL CD4+ ≥ 500 cells/mm3 had plaque risk not statistically different from

uninfected individuals

Hanna D, et al. Clin Infect Dis. 2015;[Epub ahead of print].

HIV infected (n = 571)HIV uninfected (n = 207)

100

80

60

40

20

0Any

Plaque,Baseline

AnyPlaque,

Last Visit

Formation of New Plaque

WIH

S P

art

icip

an

ts W

ith

F

oc

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Ca

roti

d A

rte

ry P

laq

ue

(%

)

43(8)

16(8)

93(16) 21

(10)

70(12)16

(8)

HIV infected (n = 363)HIV uninfected (n = 172)

100

80

60

40

20

0Any

Plaque,Baseline

AnyPlaque,

Last Visit

Formation of New Plaque

MA

CS

Pa

rtic

ipa

nts

Wit

h

Fo

ca

l C

aro

tid

Art

ery

Pla

qu

e

(%)

90(25)

41(24)

132(36) 51

(30)94

(26)26

(15)


CT Angiography in HIV

Asymptomatic HIV-positive pts had higher prevalence and degree of coronary atherosclerosis vs uninfected controls[1]

Among ART-treated HIV-infected pts, plasma sCD163 significantly higher (P = .02) and correlated with noncalcified plaque[2]

1. Lo J, et al. AIDS. 2010;24:243-253. 2. Burdo TH, et al. J Infect Dis. 2011;204:1227-1236.

(n = 78)(n = 32)

Coronary Atherosclerosis[1]100

80

60

40

20

0

Pre

vale

nce

of

Co

ron

ary

Ath

ero

scle

rosi

s (%

)

P = .02

34.4%

59.0%

Non-HIV–InfectedControl Subjects

HIV-InfectedSubjects


Subramanian S, et al. JAMA. 2012;308:379-386.

Aortic Inflammation Higher Among Pts With HIV Infection Cardiac 18F-FDG-PET assessment of arterial wall inflammation in pts with

HIV infection on stable ART (n = 27) vs uninfected controls (n = 27)

P < .001

Ao

rtic

FD

G U

pta

ke T

BR

3.0

2.5

2.0

1.5

1.0HIV

(n = 27)FRS-

Matched Controls

Athero-scleroticControls Natural Log of sCD163 (ng/mL)

Ao

rtic

TB

R

P = .293.63.43.23.02.82.62.42.22.01.81.61.41.2

5.5 6.0 6.5 7.0 7.5 8.0 8.5

P = .03

Role of Antiretrovirals in Cardiovascular Disease Risk


D:A:D: Incidence of MI Increases With Exposure to Combination ART

Incidence of MI by Yr of Exposure to ART

D:A:D Study. N Engl J Med. 2003;349:1993-2003.

7

6

5

4

3

2

1

0Inci

den

ce p

er 1

000

Per

son

-Yr

Exposure (Yr)

8

None > 4< 1 1-2 2-3 3-4

Events, nPerson-yrs, n

35714

94140

144801

225847

317220

478477


Magnificent Consortium: Traditional, HIV, Genetic CAD Factors and Cardiac Events 571 cases with first CAD

event compared with 1304 controls

– CAD events: MI, unstable angina, angioplasty/stent, coronary bypass surgery

Multivariate analysis

– Current ART (including current ABC) associated with similar risk for cardiac event as CAD risk factors

– HTN, high cholesterol, history of smoking

Case-Control Study of 24 Observational HIV Cohorts (US, EU, Australia, and Argentina)

to Evaluate CAD, 2000-2009

Rotger M, et al. Clin Infect Dis. 2013;57:112-121 Odds Ratio (95% CI)0 1 2 3 4

Quartile 2 vs quartile 1Quartile 3 vs quartile 1

Quartile 4 vs quartile 1

CD4HIV-1 RNA

Indinavir ≥ 1 yr of exposureLopinavir ≥ 1 yr of exposure

On ARTAbacavir current exposure

Low HDL cholesterolHypertension

High cholesterolPast smoking

DiabetesFamily history of CAD

Age per 5 yrsCurrent smoking


START Study: Randomized Comparison of Immediate vs Delayed ART

Study stopped in May 2015 due to excess of events (86 vs 41) in the deferred treatment arm

Most common AIDS-related illnesses among study participants were pulmonary TB, Kaposi’s sarcoma, and non-Hodgkin's lymphoma; the most common serious non-AIDS–related illnesses were cancer, heart attack, and deaths due to various causes

Immediate treatment

Defer treatment until CD4+ cell count

≤ 350 cells/mm³

Treatment-naive pts with

CD4+ cell count > 500 cells/mm³

(N = 4685)

NIH. Press release. May 27, 2015.

Study endpoints(over 6 yrs)

Fatal AIDS or nonfatal serious AIDS events (CV, liver, renal, and cancer)

Non-AIDS–related death


CVD in SMART Trial of Immediate vs Deferred ART Outcomes including CVD (ART Better than no ART)

El Sadr W, et al. N Engl J Med. 2006;355:2283-2296.

Endpoint* Drug Conservation Group(N = 2720)

Viral Suppression Group(N = 2752)

HR for Conservation Group vs Viral

Suppression Group (95% CI)

P Value

Participants With Event, n

Event Rate(per 100 Person-Yr)

Participants With Event, n

Event Rate(per 100 Person-Yr)

Primary endpoint 120 3.3 47 1.3 2.6 (1.9-3.7) < .001

Death from any cause

55 1.5 30 0.8 1.8 (1.2-2.9) .007

Opportunistic disease

Serious 13 0.4 2 0.1 6.6 (1.5-29.1) .01

Nonserious 63 1.7 18 0.5 3.6 (2.1-6.1) < .001

Major CV, renal, or hepatic disease

65 1.8 39 1.1 1.7 (1.1-2.5) .009

Fatal or nonfatal CVD

48 1.3 31 0.8 1.6 (1.0-2.5) .05

Fatal or nonfatal renal disease

9 0.2 2 0.1 4.5 (1.0-20.9) .05

Fatal or nonfatal liver disease

10 0.3 7 0.2 1.4 (0.6-3.8) .46

Grade 4 event 173 5.0 148 4.2 1.2 (1.0-1.5) .13

Grade 4 event or death from any cause

205 5.9 164 4.7 1.3 (1.0-1.6) .03

*Numbers of individual events of each type do not sum to the total number because some participants had more than 1 event. Endpoint definitions are listed in the Supplementary Appendix. Grade 4 events were determined on the basis of toxicity grades developed by the Division of AIDS of the NIAID.


Summary of Key Analyses Showing ABC Associated With Risk of MIStudy Study

DesignAge, Yrs (range)

Event(n)

Pts,N

TDFCV Effect

ABC CV Effect

Time on ABC, Mos

Risk of MI (95% CI)

D:A:D[1] Cohort 40 (35-47)

MI, validated(387) 22,625 No Yes ≥ 6 1.70

(1.17-2.47)

D:A:D 2013[2] Cohort 39(33-46)

MI(493) 32,663 Yes 1.47

SMART[3] RCT 45(39-51)

MI, validated(19) 2752 No Yes Current 4.3

(1.4-13.0)

STEAL[4] RCT 45.7±8.8

MI(3) 357 No Yes 96 2.2

QPHID[5] CC 47 (22-67)

MI(125) 7053 No Yes 6 1.79

(1.16-2.76)

Danish[6] Cohort 39(33-47)

MI(67)

2952 No Yes > 6 2.00 (1.07-3.76)

VA (Choi)[7] Cohort 48 CV event(501) 10,931 No Yes 6 1.64

(0.88-3.08)

Swiss[8] Cohort Not given CVD event(350) 11,625 No Yes > 1-6 3.36

(2.04-5.53)

MAGNIFICENT[9] CC 50 (22-85.5)

CVD event

(571) 571 No Yes Current 1.56 (1.17-2.07)

NA-ACCORD[10] Cohort MI, validated(301) 16,733 Yes > 6 1.33

Swiss HIV Cohort[11] Cohort 45 CVD event

(365) 11,856 Yes > 6 2.06 (1.43-2.98)

1. Friis-Moller N, et al. Eur J Cardiovasc Prev Rehabil. 2010;17:491-501. 2. Friis-Moller N, et al. Eur J Prev Cardiol. 2015;[Epub ahead of print]. 3. SMART/INSIGHT Study Group. AIDS. 2008;22:F17-24. 4. Martin A, et al. Clin Infect Dis. 2009;49:1591-1601. 5. Durand M, et al. JAIDS. 2011;57:245-253. 6. Obel N, et al. HIV Medicine. 2010;11:130-136. 7. Choi AI, et al. AIDS. 2011;25:1289-1298. 8. Young J, et al. IAS 2013. Abstract MOPE070. 9. Rotger M, et al. Clin Infect Dis. 2013;57:112-121. 10. Palella F, et al. CROI 2015. Abstract 749LB. 11. Young J, et al. JAIDS. 2015;[Epub ahead of print].


Summary of Key Analyses Showing ABC NOT Associated With Risk of MIStudy Study

DesignAge, Yrs

(Range)

Event(n)

Pts, N TDFCV Effect

ABC CV

Effect

Time on ABC, Mos

Adj Risk of MI

(95% CI)

FHDB[1] CC47

(41-54)MI

(289)74,958 No No* > 6

1.27ǂ

(0.64-2.49)

ALLRT/ACTG[2] Cohort

37(27-50)

MI(36)

5056 No No† 720.70

(0.2 -2.4)

VA[3] Cohort 46MI

(278) 19,424 No No* 24

1.18 (0.92-1.50)

FDA[4]

Meta-analysis

ofRCTs

36-42MI

(24)9868 No No 19

1.02 (0.56-1.84)

*All or majority of pts were treatment naive at ABC inclusion. †All or majority of pts were treatment experienced at ABC initiation.ǂWithout adjustment for cocaine use OR: 2.01 (1.11-3.64).

1. Lang S, et al. Arch Intern Med. 2010;170:1228-1238. 2. Ribaudo HJ, et al. Clin Infect Dis. 2011;52:929-940. 3. Bedimo RJ, et al. Clin Infect Dis. 2011;53:84-91. 4. Ding X, et al. J Acquir Immune Defic Syndr. 2012;61:441-447.


DHHS Guidelines: Factors to Consider When Selecting an Initial ART Regimen When selecting a regimen for an individual pt, a number of

pt and regimen specific characteristic should be considered, with the goal of providing a potent, safe, tolerable, and easy to adhere to regimen for the pt in order to achieve sustained virologic control

– CVD is one of several specific comorbidities listed among those to consider

– In pts with high cardiac risk, consider avoiding ABC- and LPV/RTV-based regimens

– Associated with increased cardiovascular risk in some studies

DHHS Adult Guidelines. April 2015.


ART and Effects on Lipids

TDF ABCRALDTG

ATV/RTV or ATV/COBIDRV/RTV or DRV/COBIEVG/COBI

EFVRPVETV


ACTG 5206: TDF Lowers LDL in Pts With Virologic Suppression Double-blind pilot study

of alternating TDF and placebo for 12 wks in pts (n = 17) with HIV-1 RNA < 400 copies/mL ≥ 90 days on ART 4-wk washout between treatment periods

Dyslipidemia: fasting 150-999 mg/dL or non-HDL 100-249 mg/dL

Primary endpoint: change in non-HDL over 12 wks of active TDF minus the change over 12 wks of placebo

Median Change in Lipid Parameters

Tungsiripat M, et al. AIDS. 2010;24:1781-1784.

TDFPlacebo

Non HDLP = .01

TCP < .01

LDLP = .06

HDLP = .91

TGP = .83

0.2

0

-0.2

-0.4

-0.6

-0.8

-1.0

-1.2


Lipid Changes From BL to Wk 48 in RCTs of First-line ART: NNRTI Comparisons

This slide is an illustration only and not meant to be a cross-study comparison.

1. Lennox J, et al. Lancet. 2009;374:796-806. 2. Daar E, et al. Ann Intern Med. 2011;154:445-456..

EFV + TDF/FTCATV/RTV + TDF/FTC

P < .001

ACTG 5202[2]

TC LDL HDL TG

Me

dia

n C

ha

ng

e

(mg

/dL

)

0

10

20

30

40

50

6070

22

10

40

1512

2113

24

10 82 5

148

13

29

EFV + ABC/3TCATV/RTV + ABC/3TC

P < .001P < .001

P < .001

P < .001

P = .002

21

70

34

13

22

9-14

184P < .0001

STARTMRK[1]

TC LDL HDL TG

Me

an

Ch

an

ge

(m

g/d

L)

0

10

20

30

40

50

60

70 RAL + TDF/FTCEFV + TDF/FTC

P < .0001

P < .0001

P = .0002


1516

-8

Lipid Changes From BL to Wk 48 in RCTs of First-line ART: Boosted PIs vs INSTIs

RAL + TDF/FTCATV/RTV + TDF/FTC

DRV/RTV + TDF/FTC

1. Ofotokun I, et al. Clin. Infect. Dis. 2015;60:1842-1851. 2. Quercia R, et al. Clin. Drug Invest. 2015;35:211-219.This slide is an illustration only and not meant to be a cross-study comparison.

DTG + 2 NRTIs DRV/RTV + TDF/FTC

ACTG 5257[1]

TC HDL TG

Mea

n C

ha

ng

e (m

g/d

L)

0

10

2013

1

15

64

-3

66 5

FLAMINGO[2]

TC LDL HDLMea

n C

ha

ng

e (m

g/d

L)

0

10

20

4

23

33

-6

14

3 22

30

40

-5

30

TG

LDL


Atazanavir Associated With Slowed IMT Progression A5260s: metabolic substudy of ACTG 5257

– 328 ART-naive pts with no CVD randomized to receive ATV/RTV, RAL, or DRV/RTV (each paired with TDF/FTC)

– Carotid IMT evaluated by B-mode ultrasonography

Stein JH, et al. J Am Coll Cardiol. 2014;63:2301-2302.

Non-HDL: Mean Change (95% CI)20

10

0

-10

-20

mg

/dL

Study Wk0 24 48 96

ATVRALDRV

Carotic IMT: Mean Change (95% CI)50

40

30

20

10

μm

Study Wk0 48 96 144

ATVRALDRV

0


Lipid Changes From BL to Wk 48 in RCTs of First-line ART: COBI vs RTV

This slide is an illustration only and not meant to be a cross-study comparison.

1. De Jesus E, et al. Lancet. 2012;379:2429-2438. 2. Gallant JE, et al. J Infect Dis. 2013;208:32-39. 3. Gallant JE, et al. AIDS 2012. Abstract TUAB0103.

10 81111

568

23

P = .006

ATV/RTV + TDF/FTCEVG/COBI/TDF/FTC

Study 103[1]

TC LDL HDL TG

Med

ian

Ch

ang

e (m

g/d

L)

0

10

20

30

40

50

60

70

519 11

11 56

19

32

P = .063

ATV/RTV + TDF/FTCATV/COBI + TDF/FTC

Study 114[2,3]

TC LDL HDL TG

Med

ian

Ch

ang

e (m

g/d

L)

0

10

20

30

40

50

60

70

P = .081

What Is the Role of Statins in HIV-Infected Pts With CVD?


Randomized Trial of Statin Therapy and Coronary Plaque Progression Randomized 12-mo trial in HIV+ pts

on stable ART with LDL < 130 and ≥ 1 coronary plaque

– Atorvastatin 20 mg ( to 40 mg at 3 mos) (n = 19) vs

– Placebo (n = 21)

Statin therapy reduced progression of coronary plaques

– Reduced overall plaque volume, including lipid-laden plaques

– Reduced high-risk morphology plaques

Statin therapy safe and well tolerated

Lo J, et al. CROI 2015. Abstract 136.

Plaque Progression in Proximal Left Anterior Descending Coronary Artery

With Atorvastatin or Placebo

BL

12 mos

PlaceboAtorvastatin


Rosuvastatin Effects on Carotid Intimal Thickness and Coronary Calcium Score SATURN-HIV: double-blind, randomized, placebo-

controlled trial of rosuvastatin in HIV-positive pts (N = 147)

Longenecker T, et al. CROI 2015. Abstract 137.

Mean Change in CIMT Mean Change in CCA in Those

With BL Calcification

Statin Control

P < .05

-4

4

3210

-1-2-3

Statin Control

300

250

200

150

100

50

0

P < .05

Mea

n C

IMT

Ch

ang

e (m

m)

Mea

n C

ha

ng

e in

CA

C S

core


Factors Contributing to CVD in HIV-Positive Pts

Traditional Risk Factors

Traditional Risk Factors ART ToxicityART Toxicity Coinfection Coinfection

CVDCVD

Monocyte and macrophageactivation

Monocyte and macrophageactivation

Chronic inflammationChronic inflammation

Other proinflammatory and procoagulant pathways

Crowe S. IAS 2014.


Drug–Drug Interactions With First-line ART and Lipid-Lowering TherapyAntiretroviral Contraindicated Titrate Dose No Dose Adjustment

EFV AtorvastatinSimvastatinPravastatin

Rosuvastatin

Pitavastatin

RPV AtorvastatinPitavastatin

ATV/RTVATV/COBI

LovastatinSimvastatin

AtorvastatinRosuvastatin

Pitavastatin

DRV/RTVDRV/COBI


AtorvastatinPravastatin

Rosuvastatin

Pitavastatin

EVG/COBI/TDF/FTC


AtorvastatinRosuvastatin

DTG

RAL

DHHS Adult Guidelines. April 2015.


Conclusions: Managing CV Risk in HIV Pts

Rates of CVD higher in HIV-infected pts vs general population

CVD risk can be assessed by considering

– Traditional risk factors

– HIV-related factors

Starting ART early can mitigate CV risk even though certain ART drugs may increase lipids

Statins have been shown to be effective in reducing CV risk in pts without HIV infection and should be used as indicated in HIV-infected pts

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Cardiovascular Disease in HIV-Infected Patients.Predict It and Prevent It.2015

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