Assessing and Refining Myocardial Infarction Risk Estimation Among Patients With Human Immunodeficiency Virus

Abstract

Importance Persons with human immunodeficiency virus (HIV) treated with antiretroviral therapy (ART) have improved longevity but are at elevated risk for myocardial infarction (MI) due to common MI risk factors and HIV-specific factors. Despite these elevated MI rates, optimal methods to predict MI risks for HIV-infected persons remain unclear. Objective To determine the extent to which existing and de novo estimation tools predict MI in a multi-center HIV cohort with rigorous MI adjudication. Design We evaluated the performance of standard-of-care and two new data-derived MI risk estimation models in the Centers for AIDS Research Network of Integrated Clinical Systems (CNICS) multi-center prospective clinical cohort. The new risk estimation models were validated in a cohort separate from the derivation cohort. Setting Clinical sites across the U.S. where HIV-infected adults receive medical care in inpatient and outpatient settings. Participants HIV-infected adults receiving care anytime since 1995 at 5 CNICS sites where MIs were adjudicated (N=19829). Exposures Common cardiovascular risk factors, HIV viral load, CD4 count, and medication use were used to calculate predicted event rates. Main Outcome and Measures Observed MI rates over the course of follow-up, scaled to 10 years using an observed prime approach to account for dropout and loss to follow-up prior to 10 years. Results MI rates were higher among blacks, older participants, and participants who were not virally suppressed. The 2013 Pooled Cohort Equations (PCEs), which predict composite rates of MI and stroke, adequately discriminated MI risk (Harrell’s C Statistic = 0.75). Two data-derived models incorporating HIV-specific covariates exhibited weak calibration in a validation sample and did not discriminate risk any better (Harrell’s C Statistic = 0.72 and 0.73) than the PCEs. The PCEs were moderately calibrated in CNICS but predicted consistently lower than observed prime rates of MI. The PCEs Conclusions and relevance The PCEs discriminated MI risk and were moderately calibrated in this multi-center HIV cohort. Adding HIV-specific factors did not improve model performance. As HIV-infected cohorts capture and assess outcomes of MI and stroke, the performance of risk estimation tools should be revisited.

Estimating Longitudinal Risks and Benefits From Cardiovascular Preventive Therapies Among Medicare Patients

“…34–36 Others have noted underestimation of risk by the Pooled Cohort Equations in patient groups with inflammatory conditions, such as HIV. 37 In contrast, the equations have demonstrated good discrimination and excellent calibration around decision thresholds in cohorts that are population-based and broadly representative of the United States, specifically including Medicare-eligible participants. 38 In the REGARDS cohort (REasons for Geographic And Racial Differences in Stroke), which includes community-dwelling individuals from all 48 contiguous Unites States and large numbers of black and white participants, the Pooled Cohort Equations were overall well-calibrated, including among Medicare participants.…”

Epidemiology of ischemic heart disease in HIV

“…94 More recently, the FRS was shown to have moderate discrimination (ability to distinguish patients with and without outcome) and good calibration (agreement between observed and predicted risk) and the ACC/AHA to have good discrimination but poor calibration in HIV. 95 A recent large study from CNICS found that the ACC/AHA risk score underestimated risk and had reasonable discrimination but moderate calibration, 96 and that the incorporation of HIV-specific variables did not improve its performance. 96 …”

“…95 A recent large study from CNICS found that the ACC/AHA risk score underestimated risk and had reasonable discrimination but moderate calibration, 96 and that the incorporation of HIV-specific variables did not improve its performance. 96 …”

Cardiovascular Disease Imaging in HIV

“…Some studies suggest that the new 2013 ACC/AHA algorithm, that was not determined based on data from patients with HIV, may indeed underestimate CVD rates, especially in young patients at lower risk thresholds, but also potentially overestimate at higher risk thresholds. 5 In addition, key questions of sex and racial differences remain as to the use of these equations. Uniquely, relative CVD rates (HIV versus control) are higher in women, 3 and the ideal risk prediction equation must be able to accurately identify women and other subpopulations of HIV at highest risk.…”

“…Notably, adding HIV-specific risk did not improve model performance in these studies. 5 Together, these prior studies beg the questions of the unique, nontraditional mechanisms that may explain the observed increased event rates among patients with HIV, and how we may identify those patients at risk for CVD in HIV, and ultimately how we may treat such patients.…”