Impact of Chronic HCV Co-infection on HIV Clinical Outcomes in the

District of Columbia

Sarah Willis, MPHDepartment of Epidemiology and Biostatistics

School of Public Health and Health Services

The George Washington University

2011 National HIV Prevention Conference

A Public Health/Academic Partnership between the

District of Columbia Department of Healthand

The George Washington University School of Public Health and Health Services

Department of Epidemiology and Biostatistics

Contract Number POHC-2006-C-0030

Background

• An estimated 1/4 of those infected with HIV are also infected with hepatitis C virus (HCV)

• Estimates of HIV/HCV co-infection range from 50-90% among certain sub-populations

• Supporting evidence that HIV negatively impacts HCV disease progression and reduces the effectiveness of available treatments

Background (2)

• Less research has been conducted regarding role of HCV co-infection on HIV disease and existing studies have conflicting results– Association between HCV/HIV co-infection and

worsening liver disease and higher mortality when compared to those with HIV or HCV monoinfection (Merriman et al)

– HCV co-infection associated with blunted CD4 cell recovery after initiating HAART yet no effect on virologic response or mortality (Carmo et al)

Objectives

Utilize routinely reported surveillance data to:1. Determine the extent of HIV/HCV co-infection

in the District of Columbia between 2000-2009

2. Describe potential factors that may be associated with HIV/HCV co-infection

3. Determine the impact that HIV/HCV co-infection has on HIV clinical outcomes and mortality

Methods• Identified name-based HIV/AIDS cases diagnosed

and reported to the DCDOH between 2000 – 2009 (n=10,215)

• Identified chronic HCV cases reported to DCDOH during the same time period (n=16,235)

• Used Link Plus Probability matching program to match cases by:– First and last name

– Date of birth

– Sex

– Race

• Reviewed potential matches for accuracy

Methods (2)• Performed bivariate analyses to detect differences

among HIV/HCV co-infected and HIV mono-infected individuals based on:– Demographics

– Entrance into HIV Care (time between HIV/AIDS diagnosis and first VL or CD4 test reported to DCDOH)

– Engagement in HIV Care• Continuous Care - evidence (e.g. HIV-related lab test) of at least 2

visits to an HIV medical provider 10-14 weeks apart

• Sporadic care - one visit to a provider or 2 visits but more than 14 weeks apart

– Viral load and CD4 count (at time of diagnosis and most recent results)

– Mortality

Methods (3)• Assessed timing of HIV/HCV co-infection

• Association between HIV/HCV co-infection and mortality (time to death) examined through:– Kaplan-Meier log rank test/log rank survival plots

– Cox proportional hazard ratio model

Demographics of Co-Infected and Monoinfected Cases

HIV/HCV Co-infected(n=1,151)

HIV Monoinfected

(n=9,017)

Chi-square p-value

SexMaleFemale

67.2%32.8%

70.5%29.5%

0.0189

Race/ethnicityWhiteBlackHispanicOther*

4.5%90.4%3.1%2.0%

14.4%77.5%5.8%2.3%

<0.0001

11.3% of reported HIV cases were HCV co-infected

*Other race includes Asian, Alaska Native, American Indian, Native Hawaiian, Pacific Islander, and Mixed and Unknown race

Age and Vital Status of Co-Infected and Monoinfected Cases

HIV/HCV Co-infected(n=1,151)

HIV Monoinfected

(n=9,017)

Chi-square p-value

Age at HIV diagnosis13-1920-2930-3940-4950-59≥60

0.2%3.7%

13.9%48.1%28.8%5.3%

3.1%20.6%32.4%28.1%11.8%4.1%

<0.0001

Vital Status*AliveDead

80.5%19.5%

88.5%11.5%

<0.0001

*as of December 31st, 2009

HIV Mode of Transmission

17.6%

40.3%

4.6%

23.5%

13.8%

36.4%

12.1%

2.6%

31.6%

17.2%

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

35.0%

40.0%

45.0%

MSM IDU MSM/IDU Heterosexual Risk Not Identified

Prop

orti

on o

f Dia

gnos

ed C

ases

HIV/HCV Co-infected HIV

Timing of HIV/HCV InfectionConcurrent Infections

(< 3 months apart)27.1%

HIV Infection 3+ months

prior to HCV14.2%

HCV Infection 3+ months prior to HIV

58.7%

HIV Care Seeking BehaviorHIV/HCV

Co-infected(n=1,151)

HIV Monoinfected

(n=9,017)

Chi-square p-value

Entrance into Care< 3 months3 – 6 months6 – 12 months> 1 yearNot in care

56.9%5.7%6.3%

25.0%6.0%

59.9%4.6%5.6%

20.4%9.5%

<0.0001

Engagement in CareNo careSporadic CareContinuous Care

6.0%57.7%36.3%

9.5%61.4%29.1%

<0.0001

HIV Viral Load at Time of HIV Diagnosis

Kruskal Wallis; p = 0.3031

10,55116,406

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000

90,000

100,000

HIV/HCV Co-infection HIV only

Med

ian

Vir

al L

oad

at D

iagn

osis

(c

opie

s/m

L)

Most Recent Viral Load Results

Kruskal Wallis; p = 0.0119

74 740

500

1,000

1,500

2,000

2,500

3,000

3,500

HIV/HCV coinfection HIV only

CD4 Count at HIV Diagnosis

Kruskal Wallis; p-value = 0.3986

185 192

0

50

100

150

200

250

300

350

400

450

500

HIV/HCV coinfection HIV only

Med

ian

CD4

Coun

t at D

iagn

osis

(c

ells

/µL)

Most Recent CD4 Results

Kruskal Wallis; p-value = 0.0002

389445

0

100

200

300

400

500

600

700

HIV/HCV coinfection HIV only

Med

ian

CD4

Coun

t (ce

lls/µ

L)

Survival Among HIV/HCV and HIV only cases

HIV only cases

HIV/HCV co-infected cases

Log-rank = 47.35p-value = <0.0001

Adjusted Hazard Ratio for Mortality among HIV/HCV Co-infected Cases

Adjusted Hazard Ratio†

95% Confidence Interval

HCV/HIV vs. HIV only 1.20 1.02, 1.40

† Adjusted for sex, race/ethnicity, age, engagement in care, HIV mode of transmission, and progression to AIDS

Conclusions

• More than half of HIV/HCV co-infections were infected with HCV first

• In comparison to HIV monoinfected cases, HIV/HCV co-infected cases in DC were more likely to be:– Black– Over 40 years of age– IDU

• HIV/HCV co-infected cases in DC may have poorer HIV clinical outcomes over time– Lower CD4 counts among HIV/HCV co-infected cases at

most recent test– Increased mortality among HIV/HCV co-infected cases

Limitations

• May have underestimated HIV/HCV co-infections due to errors in data entry, name changes or incorrect spelling

• Large proportion of cases with missing CD4 and viral load data at diagnosis and at follow-up (25%-75%) in eHARS, could not assess their clinical outcomes

Recommendations

• Subsequent studies should be conducted to better understand the impact of HCV co-infection on HIV disease

• Studies utilizing surveillance data for this purpose should:– Improve completeness of VL and CD4 test results data – Obtain data on ART utilization

• Prevention and treatment interventions should be developed for sub-populations with high rates of HCV/HIV co-infection, such as IDUs

Acknowledgments

DC DOH HIV/AIDS, Hepatitis, STD, TB Administration

– Angelique Griffin*– Yujiang Jia– Gregory Pappas– Rowena Samala– Tiffany West*

George Washington University School of Public Health and Health Services

– Amanda D. Castel*– Irene Kuo*– Alan Greenberg

*Co-authors