Abstract 4360198: PREVENT Heart Failure Equations Underpredict Physician-Adjudicated Heart Failure Events Among People with HIV in the Multi-Center CNICS Cohort

M Matthew Durstenfeld (UCLA, San Francisco, California, United States) R Ryan Kyle (University of Washington, Seattle, Washington, United States) B Bridget Whitney (University of Washington, Seattle, Washington, United States) A Alexander Hoffmann (Signaling Systems Laboratory, Department of Microbiology, Immunology and Molecular Genetics, and the Institute for Quantitative and Computational Biosciences, University of California) C Cody Cichowitz (University of California San Francisco, San Francisco, California, United States) P Peter Hunt (UCSF, San Francisco, California, United States) C Chris Longenecker (University of Washington, Seattle, Washington, United States) P Priscilla Hsue (University of California Los Angeles, Los Angeles, California, United States) G Greer Burkholder (University of Alabama at Birmingham, Birmingham, Alabama, United States) J Joseph Delaney (University of Washington, Olympia, Washington, United States) H Heidi Crane (University of Washington, Seattle, Washington, United States) M Matthew Feinstein (NORTHWESTERN UNIV - FEINBERG SCHOOL, Chicago, Illinois, United States)

Abstract

Background: HIV infection is associated with increased risk of heart failure (HF). The American Heart Association recently developed the Predicting Risk of Cardiovascular Events (PREVENT) equations, which includes a calculator for 10-year risk of HF events. This calculator has not yet been validated among people with HIV (PWH) at risk for HF. Purpose: The purpose of this study was to evaluate the PREVENT 10-year HF risk prediction calibration and discrimination among a diverse, multicenter cohort study of PWH with physician-adjudicated heart failure events. Hypothesis: The PREVENT 10-year HF equations will have acceptable discrimination and strong calibration. Methods: We included adults ages 30-79 years old with HIV and without HF enrolled in the Center for AIDS Research Network of Integrated Clinical Systems (CNICS) Cohort at two sites (University of Washington and University of Alabama at Birmingham) that participated in physician adjudication of HF events from 2008 to 2021. We calculated predicted 10-year HF risk at baseline using the PREVENT 10-year base equation. HF events were adjudicated according to a standard protocol by two cardiologists independently, with discrepancies resolved by a third reviewer. Follow-up was until first HF event, death, loss to follow-up, or end of the study period. We used Harrell’s C-index to assess discrimination and the Kaplan-Meier approximation of the Greenwood-Nam-D’Agostino estimator (to account for variable follow-up time) and goodness-of-fit test to assess calibration. Results: We included 4,970 individuals with a mean age of 44 and 20% female ( Table ). The mean predicted 10-year risk of HF by PREVENT was 2.5% (SD: 4.9) [median=1.1% (IQR: 0.5-2.5)]. Over a median of 6.1 years of follow-up (IQR: 2.4-9.4), 125 individuals had an incident HF event. Discrimination by Harrell’s C-index was 0.760 (95% CI: 0.713-0.808). Using the Greenwood-Nam-D’Agostino estimator, the ratio of observed events to predicted events by the PREVENT HF equation over ten years was 1.47 (p<0.001). The calibration slope by decile of predicted risk was 1.035 for PREVENT ( Figure ). Conclusions: Among a cohort of people with HIV in the United States, the PREVENT 10-year HF equation has acceptable discrimination but is poorly calibrated, with the observed probability of events ~50% higher than the predicted risk across deciles of predicted risk.

Article Details

Journal Circulation
Volume / Issue Vol. 152, Issue Suppl_3
Published November 04, 2025
ISSN 0009-7322
Publisher Lippincott Williams & Wilkins

Journal Info

Circulation

Lippincott Williams & Wilkins

ISSN: 0009-7322 Health Sciences

Authors (12)

M

Matthew Durstenfeld

UCLA, San Francisco, California, United States

R

Ryan Kyle

University of Washington, Seattle, Washington, United States

B

Bridget Whitney

University of Washington, Seattle, Washington, United States

A

Alexander Hoffmann

Signaling Systems Laboratory, Department of Microbiology, Immunology and Molecular Genetics, and the Institute for Quantitative and Computational Biosciences, University of California

C

Cody Cichowitz

University of California San Francisco, San Francisco, California, United States

P

Peter Hunt

UCSF, San Francisco, California, United States

C

Chris Longenecker

University of Washington, Seattle, Washington, United States

P

Priscilla Hsue

University of California Los Angeles, Los Angeles, California, United States

G

Greer Burkholder

University of Alabama at Birmingham, Birmingham, Alabama, United States

J

Joseph Delaney

University of Washington, Olympia, Washington, United States

H

Heidi Crane

University of Washington, Seattle, Washington, United States

M

Matthew Feinstein

NORTHWESTERN UNIV - FEINBERG SCHOOL, Chicago, Illinois, United States