CROI 2015 Program and Abstracts

Abstract Listing

Poster Abstracts

WEDNESDAY, FEBRUARY 25, 2015 Session P-P5 Poster Session

Poster Hall

2:30 pm– 4:00 pm Cardiovascular Risk Prediction 746 Cumulative HIV Care Measures Highly AssociatedWith Acute Myocardial Infarction

Jorge L. Salinas 1 ; ChristopherT. Rentsch 2 ;Vincent C. Marconi 1 ; JanetTate 3 ; Adeel A. Butt 4 ; Matthew S. Freiberg 4 ; Matthew B. Goetz 5 ; Maria Rodriguez-Barradas 6 ; Amy Justice 3 ; David Rimland 1 1 Emory University, Atlanta, GA, US; 2 Atlanta VA Hospital, Decatur, GA, US; 3 Yale University, New Haven, CT, US; 4 University of Pittsburgh, Pittsburgh, PA, US; 5 David Geffen School of Medicine at University of California Los Angeles, Los Angeles, CA, US; 6 Baylor College of Medicine, Houston, TX, US Background: After accounting for established risk factors, people living with HIV (PLWHIV) have a 50-75% greater risk of acute myocardial infarction (AMI) than uninfected individuals. Several underlying causes for this association have been suggested including ongoing chronic inflammation, immune suppression, and a greater burden of anemia, renal disease, liver disease, and hepatitis C infection. While many of these factors have been studied in a cross-sectional manner, few have considered the association of cumulative HIV care measures with AMI among PLWHIV. We hypothesized that measuring these factors in a cumulative way would be associated with AMI incidence. Methods: Retrospective cohort study including PLWHIV starting antiretroviral therapy (ART) in the Veterans Aging Cohort Study Virtual Cohort (VACS VC) from 2000-2009. The impact of baseline, time-updated and cumulative measures of HIV viremia, CD4 count and the VACS Index were modeled. Cumulative measures were captured starting 6 months after ART initiation until AMI event, death, last clinic visit or censor date (December 31 , 2009) and calculated as follows: 1) Copy Years viremia (CYV)= Area under the curve of HIV viral load (VL) measures. Areas under the curve were calculated using the trapezoidal rule. The VACS Index score was calculated using age, HIV-1 RNA, CD4, aspartate and alanine transaminases, hemoglobin, platelet count, creatinine and known hepatitis C infection. An online calculator is available (http://vacs.med.yale.edu). The primary outcome was incident AMI determined using Medicare and VA ICD9 codes. Multi-variable proportional hazard (PH) models were fit for time to AMI. Results: 12,131 patients were included in the analysis. Separate PH models were fit for different measures of VL, CD4 and the VACS Index (basal, time-updated and cumulative) and results are presented in table 1. While all three cumulative measures predicted the studied outcome, VCY ≥ 63, 000 copy-years/mL (HR=4.17; 95%CI=3.59-4.85) and CD4Y<750 cell-years/mm 3 (HR=5.61; 95%CI=4.56-6.90); patients with higher VACS Index score-years had the highest risk of AMI (VISY ≥ 250; HR=40.56; 95%CI=33.25-49.47). 2) CD4 Years (CD4Y)= Area under the curve of CD4 measures. 3) VACS Index years (VISY)= Area under the VACS Index curve.

Poster Abstracts

Table 1. Multivariable Cox Proportional Hazards analyses of factors associated with time to Acute Myocardial Infarction among patients starting Initial ART regimens in the VACS Virtual Cohort; 2000-2009. Conclusions: Cumulative measures of viral load, CD4 count and VACS Index provide added information about risk of AMI, of these, VACS Index is the most comprehensive. 747 Cardiovascular Disease Risk Prediction in the HIV Outpatient Study (HOPS) Angela M.Thompson-Paul 1 ; Kenneth A. Lichtenstein 2 ; Carl Armon 3 ; Kate Buchacz 1 ; Rachel Debes 3 ; Joan S. Chmiel 4 ; Frank J. Palella 4 ; Stanley C.Wei 1 ; Jacek Skarbinski 1 ; JohnT. Brooks 1 1 US Centers for Disease Control and Prevention, Atlanta, GA, US; 2 National Jewish Health, Denver, CO, US; 3 Cerner Corporation, Vienna, VA, US; 4 Northwestern University, Feinberg School of Medicine, Chicago, IL, US Background: HIV infection is associated with an increased risk of cardiovascular disease (CVD); however, it is unknown if commonly used CVD risk prediction tools accurately predict risk in HIV-infected persons. In this analysis, we examined four CVD risk prediction equations to determine if they accurately estimate events and predict risk events in a large diverse cohort of HIV-infected adults in the United States. Methods: We analyzed longitudinal data on HIV Outpatient Study (HOPS) participants in care at 10 U.S. clinic sites as of 30 September 2013 who met the following criteria: had at least one year of follow-up after 1 January 2002, enrolled in the HOPS no later than 1 October 2010, had at least one total cholesterol measurement, and at least two systolic blood pressure measurements at baseline. We applied four CVD risk equations to the HOPS data to estimate 10-year CVD risk, and using Harrell’s C -statistic assessed their predictive ability to discriminate patients who did vs. did not experience incident CVD events. Incident CVD events were defined for each risk equation are as follows: 1) Framingham Point Score (FPS)– myocardial infarction (MI), fatal coronary heart disease (CHD), stroke; 2) Pooled Cohort Equation (PCE) - MI, stroke, coronary artery disease (CAD); 3) Systematic COronary Risk Evaluation (SCORE) for low-risk populations – fatal MI, stroke, peripheral vascular disease, CAD; and 4) the Data Collection on Adverse Effects of Anti-HIV Drugs (D:A:D) study equations - MI, sudden death, CAD, stroke, and death from other CHD.

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CROI 2015