HIV and Cardiovascular Disease.How Worried Should We Be ? 2015

David Alain 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

HIV and Cardiovascular Disease:How Worried Should We Be?

Supported by educational grants from AbbVie, Bristol-Myers Squibb, Gilead Sciences, Janssen, Merck, and ViiV.

clinicaloptions.com25th Annual CCO HIV and Hepatitis C Symposium

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Disclosures

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


Outline

There are data suggesting increased risk of comorbidities, including CVD, in people with HIV

CVD is clearly more common in people with HIV

What is unclear is why

– Possibilities

– More risk factors (smoking, sedentariness, stress, depression)

– HIV (via immune and inflammatory mechanisms, microbial translocation, CMV)

– ART

Assessing risk

Approaches to prevention


Outline




– Possibilities



– ART

Assessing risk



The Link between HIV and CVD

Rates of AMI compared in HIV+ and HIV- pts at 2 Boston hospitals

– N of ~ 3800 for HIV+ pts; > 1 million for HIV- pts

– 8-yr period 1996-2004

The HIV cohort had significantly > proportions of hypertension (21.2% vs 15.9%), diabetes (11.5% vs 6.6%), and dyslipidemia (23.3% vs 17.6%) (P < .0001 for each)

Triant VA, et al. J Clin Endocrinol Metab. 2007;92:2506-2512.

Eve

nts

per

10

00 P

Ys

Eve

nts

per

10

00 P

Ys

18-34 35-44 45-54 55-64 65-74Age Group (Yrs)

0

20

40

80

100

60

0

2

4

10

12

8

6

RR 1.75*P < .0001

HIV Positive HIV Negative

*Adjustment was made for these plus age, sex, race, hypertension.


100

80

60

40

20

0

Post WS, et al. Ann Intern Med. 2014;160:458-467.

HIV Infection and Subclinical Coronary Atherosclerosis

+ - + - + - + - + - + -40-4453 26

45-49124 45

50-54118 88

55-5991 60

60-6450 54

65+14 36Men in Each Group, n

HIV StatusAge, yrs

Pre

vale

nce

of

No

nca

lcif

ied

Pla

qu

e (%

)



Outline




– Possibilities



– ART

Assessing risk



Outline




– Possibilities



– ART

Assessing risk



The Link Between HIV and CVD

Rates of AMI compared in HIV+ and HIV- pts at 2 Boston hospitals

– N of ~ 3800 for HIV+ pts; > 1 million for HIV- pts

– 8-yr period 1996 to 2004

The HIV cohort had significantly > proportions of hypertension (21.2% vs 15.9%), diabetes (11.5% vs 6.6%), and dyslipidemia (23.3% vs 17.6%) (P < .0001 for each)

Triant VA, et al. J Clin Endocrinol Metab. 2007;92:2506-2512.

Eve

nts

per

10

00 P

Ys

Eve

nts

per

10

00 P

Ys

18-34 35-44 45-54 55-64 65-74Age Group (Yrs)

0

20

40

80

100

60

0

2

4

10

12

8

6

RR 1.75*P < .0001

HIV Positive HIV Negative

*Adjustment was made for these plus age, sex, race, hypertension.


How Big Is the Contribution of HIV and HIV-Related Factors to CVD and Other Conditions Associated With Aging?

Traditional Factors



HIV Serostatus and Coronary Artery Plaque

Post WS, et al. Ann Intern Med. 2014;160:458-467.

Variable

Prevalence of plaque Noncontrast CT scans (n = 1001) CAC present Contrast-enhanced CT scans (n = 759) Any plaque present Noncalcified plaque present Mixed plaque present Calcified plaque present Coronary artery stenosis > 50% Coronary artery stenosis > 70%

Minimally Adjusted Model*

1.21 (1.08 to 1.35)

1.14 (1.05 to 1.24)1.28 (1.13 to 1.45)1.35 (1.10 to 1.65)1.05 (0.88 to 1.27)1.48 (1.06 to 2.07)1.20 (0.70 to 2.05)

.001

.001< .001.004.58.02.51

1.12 (0.99 to 1.26)

1.13 (1.04 to 1.23)1.25 (1.10 to 1.43)1.22 (0.98 to 1.52)1.02 (0.84 to 1.23)1.23 (0.86 to 1.75)0.76 (0.44 to 1.30)

.076

.004

.001

.070.88.26.31

Adjusted for CAD Risk Factors†

PR (95% CI)‡ P Value PR (95% CI)‡ P Value

Extent of plaque§

Noncontrast CT scans CAC Agatston score (n = 527) Contrast-enhanced CT scans Segment involvement score Total coronary plaque score (n = 579) Noncalcified plaque score (n = 449) Mixed plaque score (n = 254) Calcified plaque score (n = 278)

Mean Difference (95% CI)ǁ

0.07 (-0.23 to 0.38)

0.14 (0.02 to 0.25)0.19 (0.05 to 0.33)0.16 (0.03 to 0.29)0.15 (-0.05 to 0.35)-0.02 (-0.21 to 0.17)

.65

.023

.009

.015

.133.83

0.03 (-0.34 to 0.29)

0.11 (-0.01 to 0.22)0.13 (-0.01 to 0.27)0.15 (0.02 to 0.29)0.16 (-0.04 to 0.36)-0.07 (-0.27 to 0.12)

.88

.075

.062

.026

.109.46

*Adjusted for age, race, CT scanning center, cohort (before vs after 2001).†Adjusted for age, race, CT scanning center, cohort, and CAD risk factors (systolic blood pressure, antihypertensive medication use, diabetes medication use, fasting glucose level, total and high-density lipoprotein cholesterol levels, use of lipid-lowering medications, body mass index, and pack-yrs of smoking).‡Ratio of HIV-infected to HIV-uninfected men.§Analyses (in natural log scale) include men with plaque present (plaque score >0).ǁHIV-infected minus HIV-uninfected men.

P Value Mean Difference (95% CI)ǁ P Value


1. Klein DB, et al. CROI 2014. Abstract 737. 2. Klein DB, et al. Clin Infect Dis. 2015;60:1278-1280. 3. Marcus JL, et al. CROI 2014. Abstract 741. 4. Marcus JL, et al. AIDS. 2014;28:1911-1919.

[3,4]

The reduced MI incidence rates for HIV+ in recent yrs is likely a result of:

– CVD risk factor reduction

– Use of more lipid-friendly ART

– Reduced immunodeficiency

Yr

200

150

100

50

1996-1999

2000-2003

2004-2007

2008-2009

2010-2011

250

0

Stroke Rates by HIV Status and Yr[3,4]

Ca

se

s p

er

10

0,0

00

PY

s

HIV+HIV-

400

MIs

pe

r 1

00

,00

0 P

Ys

300

200

100

0

1996-992000-03

2004-072008-09

2010-11

HIV+HIV-

MI Rates Over Time by HIV Status[1,2]


Hanna D, et al. CROI 2015. Abstract 729.

2001-2012 mortality data NYC

The NYC HIV Surveillance Registry and Vital Statistics Registry

National Death Index

145,000 HIV+ people

– 29,000 deaths

Over time, as HIV+ persons were less likely to die of HIV-related causes, the proportion succumbing to CVD increased

70

60

50

40

30

20

10

0

70

60

50

40

30

20

10

0

2001-2002

2003-2004

2005-2006

2007-2008

2009-2010

2011-2012

Yr of Death

Per

cen

t o

f A

ll D

eat

hs

2001-2002

2003-2004

2005-2006

2007-2008

2009-2010

2011-2012

Calendar Yr

CV

D D

eath

s p

er 1

000

Per

son

s (

Ag

e-S

tan

da

rdiz

ed

)

HIV-related, womenHIV-related, menMalignant neoplasms, womenMalignant neoplasms, menMajor cardiovascular diseases, womenMajor cardiovascular diseases, men

General population, menGeneral population, womenHIV diagnosed, menHIV diagnosed, women

Leading Underlying Causes of Death for HIV-Diagnosed New Yorkers, by Proportion

Age-Standardized CVD Mortality Rate, by HIV Diagnosis Status and Sex


Risk Factors for CVD Events in HIV+ Pts

Risk ratios for PI and boosted PI were estimated per additional yr, TC and HDL cholesterol per mmol/L higher, and systolic BP per 10 mmHg higher.

Friis-Moller N, et al. European J of CV Prevention and Rehab. 2010;17:491-501.

PI

Boosted P

I

Male Sex

NRTI

Age (per 5

Yrs O

lder)

Current C

igare

tte

Smokin

g

Family

Histo

ry

of CVD

Exsmokin

g

Diabetes

Total

Cholestero

l HDL

Cholestero

l

Systolic

BP

Estimated Risk Ratio of CVD Events Among 22,625 HIV-Positive Pts

(D:A:D Study)

3.5

3.0

2.5

2.0

1.5

1.0

0.5

0

1.001.08

1.631.70

1.421.43

2.35

1.27

1.92

1.21

0.67

1.05

Est

imat

ed R

isk

Rat

io (

95%

CI)

Greater R

isk


Chronic Inflammation Is Associated With Increased Risk for Comorbidities in HIV+ Pts

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

Untreated HIV Infection

HIV replication

ART

Loss of immunoregulatory cellsLoss 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

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


100

60

0

-40

80

40

-20

-60

20

*Adjusted for age, race, smoking, HCV 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).

Biomarkers of Inflammation Are Elevated in HIV+ Pts Even on ART

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

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

(Multicenter AIDS Cohort Study, 1984-2009)

Dif

fere

nce

(%

)

CXCL10

sCD27

IL-1

0sI

L-2R

αIL

-2sT

NFR2IF

N-γCXCL1

3TNF-α

IL-1

2p70

sIL-

6RBAFFCCL2 IL

-6sC

D14G

M-C

SFCCL1

1CRPIL

-1β

sGP13

0IL

-8CCL1

3CCL1

7CCL4

HIV suppressed relative to ART naive

HIV suppressed relative to HIV uninfected


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

19,000 PYs of follow-up among 4304 PYs (median age: 42 yrs; median CD4: 526; 77% men)

– 157 all-cause deaths

– 117 non-AIDS deaths

– 101 progressions to AIDS

– 121 CVD

– 99 NADM

IL-6 (baseline) was found to be a stronger predictor of all cause mortality and many fatal non-AIDS events than the other 2 markers

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

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

25

20

15

10

5

0

Cru

de

In

cid

ence

Ra

tes

per

10

00 P

YF

U (

95%

CI)

All-cause death

Non-AIDS/violent/

accidental death

AIDS CVD NADM

Crude Incidence Rates of Clinical Outcomes Across Biomarker Quartiles*

Events, n

IL-6

1st quartile2nd quartile3rd quartile4th quartile

1421

35

87

72

23

6

16

3624

1526

54

33

2113

42

2819

10

*Quartiles were defined differently in SMART and ESPRIT trials.


Role of Monocytes in Atheromatous Plaque Development

HIV activates monocytes and endothelial cells (in conjunction with proatherogenic lipids)

– 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.


HIV Is Associated With Increased Arterial Inflammation HIV-positive individuals had signs of increased arterial inflammation compared with

noninfected controls with similar cardiac risk factors

Aortic inflammation in HIV-positive individuals was associated with the soluble inflammatory marker sCD163

Subramanian S et al. JAMA. 2012;308(4):379-386.

Arterial Inflammation Was Significantly Correlated With sCD163 Levels3.6

3.2

2.8

2.4

2.0

1.6

1.25 6 7 8 9

rho = 0.44, P = .03

Natural Log of sCD163 (ng/mL)

Ao

rtic

Tar

get

-to

-B

ackg

rou

nd

Rat

io


Pathogenesis of microbial translocation in HIV-positive pts

Factors That Contribute to Chronic Immune Activation: Microbial Translocation

Marchetti G, et al. Clin Microbiol Rev. 2013;26:2-18.

HIV-Uninfected Pt HIV-Positive Pt


A Marker of Microbial Translocation Declines During Suppressive ART but Does Not Normalize

Progressors were chronically HIV-positive individuals and individuals with AIDS (< 200 CD4+ cells/mm3)

Each group contains combined pt data from 2 unique cohorts, grouped according to HIV status and study design.

Brenchley JM, et al. Nat Med. 2006;12:1365-1371.

ProgressorsUntreated

Progressors48 Wks ART

Uninfected

150

100

50

0

Pla

sma

LP

S (

pg

/mL

)

P = .0107 P = .0026


7 clinical cohorts from NA-ACCORD (~ 20%)

All ART users except those on ABC at study entry

Only ART-naive persons observed to have initiated ART

Awaiting more comprehensive analysis using marginal structural model with time updated data (if capable of

doing with relatively small sample size)

ABC and CV Disease: NA-ACCORD

Palella F, et al. CROI 2015. Abstract 749LB.

D:A:D replication

Full Study Population

Restricted Study Population

0 1.00 2.00 3.00 4.00

Adjusted HR


NA-ACCORD: Risk Factors Associated With MI

Palella F, et al. CROI 2015. Abstract 749LB.

Recent ABC use

Age < 40 (vs 50-59) yrs

Age 40-49 (vs 50-59) yrs

Age ≥ 60 (vs 50-59) yrs

Smoking

Hypertension

Diabetes

eGFR 30-59 (vs ≥ 60) mL/min/1.73m2

eGFR < 30 (vs ≥ 60) mL/min/1.73m2

High (≥ 240 vs < 240 mg/dL) total cholesterol

Statin use

High (≥ 300 vs < 300 mg/dL) triglycerides

0 8.006.004.002.00

Adjusted HR for MI

Restricted study population

Full study population


D:A:D Renal Disease and CVD

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

25

20

15

10

5

0 12 24 36 48 60 720

Mos After Baseline24,605915598746

24,023890793739

22,376831383530

20,895768176026

18,979697764922

15,631598952413

13,0015134444

8

>90>60-≤60>30-≤60≤30

N Under Follow-up

Kapian-Meier Progression to CVD by Confirmed Baseline eGFR

Per

cen

tag

e W

ith

CV

D

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


Toxic Effects of Stress

Helplessness and health

– More helplessness > risk of CVD, DM, and depression

Effects occur early and linger

– Early hardships continue to be associated with illness later in life despite SE ascendancy

Poverty by definition produces stress for which there are fewer resources to address problems

Stress leads to biological changes (hypercortisolism, increases in markers of inflammation)

– ? CNS changes such as reduced hippocampus volume?


Take Homes

This is complex

Clear signals for role of discrimination in risk of CVD

There are underlying psychosocial, genetic, and sex differences in one’s susceptibility to exposure to discrimination

Depression is major co-occurrence

Discrimination is a factor that needs to be included in CVD research

Lewis T, et al. Annu Rev Clin Psychol. 2015;11:407-40.


Chronic depressive symptoms Present AbsentHIV Status Infected Uninfected Race Black Hispanic Whites and othersBMI category Underweight or nomal BMI Overweight ObeseEducation Completed high school/GED Did not complete high schoolHousehold income level < $12,000/yr $12,000/yrUse of antidepressants Present AbsentIllicit drug use Present AbsentAlcohol use Present Absent

2.4 ± 0.60.1 ± 0.3

0.8 ± 0.3-0.4 ± 0.6

1.3 ± 0.4-0.5 ± 0.5-0.3 ± 0.7

0.2 ± 0.5-0.2 ± 0.61.5 ± 0.5

0.6 ± 0.40.4 ± 0.5

1.4 ± 0.4-0.4 ± 0.4

1.7 ± 0.50.2 ± 0.3

1.0 ± 0.60.4 ± 0.3

-1.4 ± 0.80.8 ± 0.3

< .01

.07

.01

.23

.7

< .01

.02

.41

< .01

1.3 ± 0.6-0.3 ± 0.4

0.3 ± 0.40.2 ± 0.6

0.9 ± 0.40.3 ± 0.60.2 ± 0.6

0.7 ± 0.50.02 ± 0.50.7 ± 0.5

0.4 ± 0.50.5 ± 0.5

0.6 ± 0.40.3 ± 0.5

0.6 ± 0.50.4 ± 0.4

1.0 ± 0.5-0.03 ± 0.5

-0.4 ± 0.61.3 ± 0.4

< .01

.52

.34

.37

.86

.51

.72

.07

< .01

VariableUnadjusted Estimated

FRS (Mean ± SE) P Value Adjusted* Estimated FRS P Value

*Adjusted for initial visit Framingham risk score in addition to factors displayed in the table.Note: Bold values denote P < .01

Chronic Depressive Symptoms and Framingham Coronary Risk in HIV-Infected and Uninfected Women


Demographics, CVD Risk Factors, and Other Important

Covariates Models

HIV-Specific Factors Models

HR (95% CI) HR (95% CI)

Any depressive disorder

1.31 (1.03-1.67) 1.31 (1.03-1.67)

MDD 1.27 (0.98-1.64) 1.28 (0.99-1.65)

Dysthymic disorder

1.46 (1.07-1.99) 1.47 (1.08-2.01)

Association of Depressive Disorders With Incident AMI (separate models)

2.59

3.32 3.28

3.88

Unadjusted Incident AMI Rates per 1000 Person-Yrs by Depressive Disorder

5.0

4.0

3.0

2.0

1.0No

Depressive Disorder

Any Depressive

Disorder

MDD Dysthymic Disorder

Depressive Disorders Predicts Incident AMI in HIV+ Veterans: Veterans Aging Cohort Study


Outline




– Possibilities



– ART

Assessing risk



CVD Risk Prediction Equations Developed for the General Population Consistently Underestimate CVD Risk in HIV Pts

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

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

5-Y

r E

ven

t R

ate

(%

)

5-Y

r E

ven

t R

ate

(%

)

ACC/AHA CVD Risk Calculator

5-Yr Predicted Rate (%)

Observed

Predicted

Observed

Predicted

Observed vs Predicted 5-Yr CVD Outcomes in Partners Healthcare System HIV Longitudinal Cohort of 2270 HIV-Positive Pts[1]

25

20

15

10

5

0

25

20

15

10

5

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


Outline




– Possibilities



– ART

Assessing risk



Address: Reducing Traditional CVD Risk Factors Can Decrease Risk of CVD in Older HIV-Positive Pts

Effective treatment of modifiable risk factors, such as smoking, cholesterol, and BP, can significantly reduce an individual’s CVD risk

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)

*Reduced by 1 mmol/L. †Reduced by 10 mm Hg. Petoumenos K, et al. HIV Med. 2014;15:595-603.

Reducing cholesterol

Reducing systolic BP

Smoking cessation

6

5

4

3

2

40 45 50 55 60 65Age (Yrs)

Rel

ativ

e H

azar

d o

f D

evel

op

ing

CV

D


Rosuvastatin Effects on Carotid Intimal Thickness and Coronary Calcium Score

Inclusion

HIV-1 & ≥ 18 yrs

On ART > 6 mos & HIV-1 RNA ≤ 1000 cps/mL

Fasting LDL-C ≤ 130 mg/dL

Heightened immune activation (CD8+CD38+DR + ≥ 19% or hsCRP ≥ 2 μg/mL)

No CVD or diabetes

No fragility fractures

No immunomodulatory, bone tx, or hypolipemics

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

Endpoints

Cardiovascular

– Carotid IMT (by US)

– Coronary artery calcium score (by CT)

CVD risk

– Systemic & vascular inflammation

– Lymphocyte & monocyte activation

– Lipids

– Insulin resistance

– Body composition

Rosuvastatin(n = 72)

Placeobo(n = 75)

SATURN-HIV Design

Stratified by:PI vs notOsteopenia vs notCAC vs not

Wk 96Wk 48Wk 0


Rosuvastatin Effects on Carotid Intimal Thickness and Coronary Calcium Score As expected, LDL-C drop was greater in rosuvastatin arm

3 pts (2 on statin) with premature study drug discontinuation

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

Mean Change in CIMT Mean Change in CAC in Those With BL Calcification

P < .05

Statin Control

0.4

0.2

0

-0.2

-0.4

P < .05

Statin Control

300

200

100

0


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

stable ART with LDL-c < 130 and ≥ 1 coronary plaque by CTA

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

– Placebo (n = 21)

Statin therapy reduced progression of coronary plaques over a yr

– Reduced overall plaque volume, including lipid-laden plaques

– Plaque volume decreased 4.7% with atorva; increased 18.0% in the placebo arm

– Reduced high-risk morphology plaques by 19% in atorva arm (20% increase in placebo arm)

Statin therapy safe and well tolerated

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


Contributing Factors to CVD in HIV+ Pts

Crowe S. IAS 2014. WESY 0103.

Traditional risk factors

Traditional risk factors cART toxicitycART toxicity Coinfection with eg

CMVCoinfection with eg

CMV

Monocyte and mϕactivation

Monocyte and mϕactivation

Other proinflammatory and procoagulant pathways

Other proinflammatory and procoagulant pathways

Cardiovascular diseaseCardiovascular disease

Chronic inflammationChronic inflammation

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HIV and Cardiovascular Disease.How Worried Should We Be ? 2015

Health & Medicine