Сердечно-сосудистые заболевания у ВИЧ-инфицированных пациентов : предсказать и предупредить. [ 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 from
Bristol-Myers Squibb

clinicaloptions.com/hiv
Cardiovascular Disease in HIV-Infected Patients: Predict It and Prevent It
Faculty
Priscilla Y. Hsue, MD
Professor of Medicine
University of California at San Francisco
San Francisco General Hospital
San Francisco, California
David A. Wohl, MD
Associate Professor of Medicine
School of Medicine
Site Leader, AIDS Clinical Trials Unit-Chapel Hill
University of North Carolina at Chapel Hill
Director, North Carolina AIDS Training and Education Center
Chapel Hill, North Carolina
Co-Director for HIV Services
North Carolina Department of Correction
Raleigh, 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.
AcuteMIsper
1000PYs
18-34 35-44 45-54 55-64 65-74
0
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

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
100
90
80
70
60
50
40
30
20
10
0
AllDeaths(%)
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 related
Liver related
CVD related
Non-AIDS cancer
Other
Unknown

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 ART
Continuous ART
Earlier 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
Mortalityper
1000PYs
2001 2002 2003 2004 2005 2006 2007 2008 2009
Yr
AIDS
SCD

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)
Difference(%)
CXC
L10sC
D
27
IL-10sIL-2R
α
IL-2
sTN
FR
2IFN
-γ
CXC
L13TN
F-α
IL-12p70sIL-6RBAFFCC
L2
IL-6sC
D
14
G
M
-C
SFCC
L11
CR
P
IL-1β
sG
P130
IL-8CC
L13CC
L17CC
L4
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)
CumulativeParticipantsWithCVDEvent(%)
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 eGFR
25
20
15
10
5
0
PercentageWithCVD
Mos After Baseline
720 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
24,605
9155
987
46
24,023
8907
937
39
22,376
8313
835
30
20,895
7681
760
26
18,979
6977
649
22
15,631
5989
524
13
13,001
5134
444
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 MIs
Model 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
Characteristic
ACC/
AHA
ASCVD
Framingham
SCORE QRISK2 JBS3 ASSIGN
MI CVD
Diabetes ✓ ✓ ✓ ✓ ✓
Race/ethnicity ✓ ✓ ✓
Social deprivation ✓ ✓ ✓
Hypertension therapy ✓ ✓ ✓ ✓ ✓
BMI ✓ ✓ ✓ ✓
Family history of premature
CVD/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
Event
ACC/
AHA
ASCVD
Framingham
SCORE QRISK2 JBS3 ASSIGN
MI 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-YrEventRate(%)
5-YrEventRate(%)
ACC/AHACVD 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 = 2152
25
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.
RelativeHazardof
DevelopingCVD
0
6
2
4
5
3
40 45 50 55 60 65
Age (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 Us
Inflammatory 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
0
ActivatedCD4+TCells(%)
HIV Infected,
Untreated
(n = 13)
HIV Infected,
Treated
(n = 99)
HIV
Uninfected
(n = 6)
P < .001
P < .001
75
50
25
0
ActivatedCD8+TCells(%)
HIV Infected,
Untreated
(n = 13)
HIV Infected,
Treated
(n = 99)
HIV
Uninfected
(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
0
CrudeIncidenceRates
per1000PYFU(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
0
Any
Plaque,
Baseline
Any
Plaque,
Last Visit
Formation
of New
Plaque
WIHSParticipantsWith
FocalCarotidArteryPlaque
(%)
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
0
Any
Plaque,
Baseline
Any
Plaque,
Last Visit
Formation
of New
Plaque
MACSParticipantsWith
FocalCarotidArteryPlaque
(%)
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
PrevalenceofCoronary
Atherosclerosis(%)
P = .02
34.4%
59.0%
Non-HIV–Infected
Control Subjects
HIV-Infected
Subjects

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
AorticFDGUptakeTBR
3.0
2.5
2.0
1.5
1.0
HIV
(n = 27)
FRS-
Matched
Controls
Athero-
sclerotic
Controls Natural Log of sCD163 (ng/mL)
AorticTBR
P = .29
3.6
3.4
3.2
3.0
2.8
2.6
2.4
2.2
2.0
1.8
1.6
1.4
1.2
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
0
Incidenceper1000Person-Yr
Exposure (Yr)
8
None > 4< 1 1-2 2-3 3-4
Events, n
Person-yrs, n
3
5714
9
4140
14
4801
22
5847
31
7220
47
8477

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 1
CD4
HIV-1 RNA
Indinavir ≥ 1 yr of exposure
Lopinavir ≥ 1 yr of exposure
On ART
Abacavir current exposure
Low HDL cholesterol
Hypertension
High cholesterol
Past smoking
Diabetes
Family history of CAD
Age per 5 yrs
Current 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
renal disease
9 0.2 2 0.1 4.5 (1.0-20.9) .05
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 MI
Study
Study
Design
Age, Yrs
(range)
Event
(n)
Pts,
N
TDF
CV 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 MI
Study Study
Design
Age,
Yrs
(Range)
Event
(n)
Pts, N TDF
CV Effect
ABC
CV
Effect
Time on
ABC, Mos
Adj Risk of
MI
(95% CI)
FHDB[1]
CC
47
(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†
72
0.70
(0.2 -2.4)
VA[3]
Cohort 46
MI
(278)
19,424 No No* 24
1.18
(0.92-1.50)
FDA[4]
Meta-
analysis
of
RCTs
36-42
MI
(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.
ǂ
Without 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 ABCRAL
DTG
ATV/RTV or ATV/COBI
DRV/RTV or DRV/COBI
EVG/COBI
EFVRPV
ETV

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.
TDF
Placebo
Non HDL
P = .01
TC
P < .01
LDL
P = .06
HDL
P = .91
TG
P = .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/FTC
ATV/RTV + TDF/FTC
P < .001
ACTG 5202[2]
TC LDL HDL TG
MedianChange
0
10
20
30
40
50
60
70
22
10
40
15
12
21
13
24
10 8
2 5
14
8
13
29
EFV + ABC/3TC
ATV/RTV + ABC/3TC
P < .001
P < .001
P < .001
P < .001
P = .002
21
70
34
13
22
9
-14
184
P < .0001
STARTMRK[1]
TC LDL HDL TG
MeanChange(mg/dL)
0
10
20
30
40
50
60
70
RAL + TDF/FTC
EFV + TDF/FTC
P < .0001
P < .0001
P = .0002

1516
-8
of First-line ART: Boosted PIs vs INSTIs
RAL + TDF/FTC
ATV/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.
DTG + 2 NRTIs
DRV/RTV + TDF/FTC
ACTG 5257[1]
TC HDL TG
MeanChange(mg/dL)
0
10
20
13
1
15
6
4
-3
66 5
FLAMINGO[2]
TC LDL HDL
MeanCh
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 Wk
0 24 48 96
ATV
RAL
DRV
Carotic IMT: Mean Change
(95% CI)50
40
30
20
10
μm
Study Wk
0 48 96 144
ATV
RAL
DRV
0

of First-line ART: COBI vs RTV
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 8
1111
56
8
23
P = .
006
ATV/RTV + TDF/FTC
EVG/COBI/TDF/FTC
Study 103[1]
TC LDL HDL TG
MedianChange(mg/dL)
0
10
20
30
40
50
60
70
5
19 11
11
5
6
19
32
P = .
063
ATV/RTV + TDF/FTC
ATV/COBI + TDF/FTC
Study 114[2,3]
TC LDL HDL TG
MedianChange(mg/dL)
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
3
2
1
0
-1
-2
-3
Statin Control
300
250
200
150
100
50
0
P < .05
MeanCIMTCha
MeanChangei

Factors Contributing to CVD in HIV-
Positive Pts
Traditional Risk
Factors
Traditional Risk
Factors
ART ToxicityART Toxicity CoinfectionCoinfection
CVDCVD
Monocyte and macrophage
activation
Monocyte and macrophage
activation
Chronic inflammationChronic inflammation
Other proinflammatory
and procoagulant pathways
Crowe S. IAS 2014.

Drug–Drug Interactions With First-line
ART and Lipid-Lowering Therapy
Antiretroviral Contraindicated Titrate Dose No Dose Adjustment
EFV Atorvastatin
Simvastatin
Pravastatin
Rosuvastatin
Pitavastatin
RPV Atorvastatin
Pitavastatin
ATV/RTV
ATV/COBI
Lovastatin
Simvastatin
Atorvastatin
Rosuvastatin
Pitavastatin
DRV/RTV
DRV/COBI
Lovastatin
Simvastatin
Atorvastatin
Pravastatin
Rosuvastatin
Pitavastatin
EVG/COBI/TDF/
FTC
Lovastatin
Simvastatin
Atorvastatin
Rosuvastatin
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

Go Online for More CCO
Educational Programming on
Cardiovascular Disease
ClinicalThought™ commentaries by expert faculty focusing on the
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CME-certified Interactive Virtual Presentation planned and narrated
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clinicaloptions.com/CVDisease

Сердечно-сосудистые заболевания у ВИЧ-инфицированных пациентов : предсказать и предупредить. [ Cardiovascular Disease in HIV-Infected Patients.Predict It and Prevent It ].2015

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