331. Comparing Cardiovascular Disease (CVD) Risk Scores Among HIV-Infected Patients in the CNICS Cohort
Session: Poster Abstract Session: HIV Co-morbidities
Thursday, October 3, 2013
Room: The Moscone Center: Poster Hall C
Posters
  • IDSA_CV_Risk_Poster_v4 final.pdf (607.2 kB)
    • Background: It is unclear how well HIV-specific and conventional CVD risk prediction models stratify risk of events for patients with HIV at high risk for myocardial infarction (MI). 

    Methods: CNICS is an 8-site HIV cohort with >27,000 patients, a centralized data repository with comprehensive clinical data such as lipids, and centralized MI adjudication facilitating comparisons using a definitive, well-defined outcome. We formed a convenience sample using 731 patients who required MI adjudication based on diagnoses or elevated cardiac enzymes. This group represents a high-risk population that may be challenging for risk scores and thus illuminate potential challenges in prediction of high-risk patients. Of the 731 patients, 200 had an adjudicated MI. Using risk status prior to event dates, we compared 4 scores (estimated by Cox models) using area under the curves (AUCs): Framingham NCEP III (FRS), Framingham refit (using HIV-specific calibration), Framingham + (Framingham refit + HIV factors predictive in CNICS: time on indinavir, tenofovir use, current CD4 count, ex-smoker), and the Data Collection on Adverse events of Anti-HIV Drugs (DAD) score (HIV-specific). 

    Results: DAD and FRS did not have significantly different AUCs for risk discrimination in this key population. Using re-calibration (Framingham refit) resulted in a higher AUC (0.604 vs. 0.538, p=0.03) compared with the FRS. However adding additional HIV-specific risk factors (Framingham refit + HIV) had no influence on the AUC (also 0.604).   

     

    Adjudicated MIs

    Score

    AUC

    95% CI

    FRS

    0.538

    0.49-0.59

    Framingham refit

    0.604

    0.56-0.65

    Framingham refit + HIV

    0.604

    0.56-0.65

    DAD

    0.511

    0.46-0.56

    Conclusion: We found adding HIV-specific risk factors did not substantially improve a FRS refit model in this difficult to stratify population. This high-risk population results in lower AUC because these individuals are hard to stratify in advance using baseline risk factors. However, performance in these populations does illustrate how robust these scores are in homogenous sub-populations. Future studies will focus on primary MIs rather than all adjudicated MIs and extend our risk score validation in the entire cohort.

    Robin Nance1, J.A.C. Delaney, PhD2, Susan Heckbert, MD1, Matthew Budoff, MD3, Pathmaja Paramsothy, MD1, Carl Grunfeld, MD, PhD4, Greer A. Burkholder, MD5, James H. Willig, MD, MSPh6, Michael J. Mugavero, MD, MHSc6, W. Christopher Mathews, MD, MSPH7, Carla V. Rodriguez, PhD8, Richard Moore, MD, MHS9, Joseph Eron, Jr., MD10, Sonia Napravnik, PhD10, Paul Crane, MD, MPH1, Peter Hunt, MD11, Priscilla Hsue, MD4, William Lober, MD1, Mari Kitahata, MD, MPH12, Michael S. Saag, MD6, Heidi M. Crane, MD, MPH13 and Centers for AIDS Research Network of Integrated Clinical Systems (CNICS), (1)University of Washington, Seattle, WA, (2)Epidemiology, University of Washington, Seattle, WA, (3)Los Angeles Biomedical Research Institute, Torrence, CA, (4)University of California, San Francisco, San Francisco, CA, (5)Infectious Diseases, University of Alabama at Birmingham, Birmingham, AL, (6)University of Alabama at Birmingham, Birmingham, AL, (7)University of San Diego, San Diego, CA, (8)Center for AIDS Research, University of Washington, Seattle, WA, (9)Johns Hopkins University School of Medicine, Baltimore, MD, (10)University of North Carolina at Chapel Hill, Chapel Hill, NC, (11)University Of California, San Francisco, San Francisco, CA, (12)Medicine, Center for AIDS Research, University of Washington, Seattle, WA, (13)Medicine/Infectious Diseases, University of Washington, Seattle, WA

    Disclosures:

    R. Nance, None

    J. A. C. Delaney, None

    S. Heckbert, None

    M. Budoff, None

    P. Paramsothy, None

    C. Grunfeld, None

    G. A. Burkholder, None

    J. H. Willig, None

    M. J. Mugavero, None

    W. C. Mathews, None

    C. V. Rodriguez, None

    R. Moore, None

    J. Eron, Jr., Janssen Services, LLC: Consultant, Consulting fee
    Gilead Sciences, Inc.: Consultant, Consulting fee

    S. Napravnik, None

    P. Crane, None

    P. Hunt, None

    P. Hsue, None

    W. Lober, None

    M. Kitahata, None

    M. S. Saag, None

    H. M. Crane, None

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