Importance: Persons with human immunodeficiency virus (HIV) that is treated with antiretroviral therapy have improved longevity but face an elevated risk of 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 multicenter HIV cohort with rigorous MI adjudication.
Design, setting, and participants: We evaluated the performance of standard of care and 2 new data-derived MI risk estimation models in 5 Centers for AIDS Research Network of Integrated Clinical Systems sites across the United States where a multicenter clinical prospective cohort of 19 829 HIV-infected adults received care in inpatient and outpatient settings since 1995. The new risk estimation models were validated in a separate cohort from the derivation cohort.
Exposures: Traditional cardiovascular risk factors, HIV viral load, CD4 lymphocyte count, statin use, antihypertensive use, and antiretroviral medication use were used to calculate predicted event rates.
Main outcomes and measures: We observed MI rates over the course of follow-up that were scaled to 10 years using the Greenwood-Nam-D'Agostino Kaplan-Meier approach to account for dropout and loss to follow-up before 10 years.
Results: Of the 11 288 patients with complete baseline data, 6904 were white and 9250 were men. Myocardial infarction rates were higher among black men (6.9 per 1000 person-years) and black women (7.2 per 1000 person-years) than white men (4.4 per 1000 person-years) and white women (3.3 per 1000 person-years), older participants (7.5 vs 2.2 MI per 1000 person-years for adults 40 years and older vs < 40 years old at study entry, respectively), and participants who were not virally suppressed (6.3 vs 4.7 per 1000 person-years for participants with and without detectable viral load, respectively). The 2013 Pooled Cohort Equations, which predict composite rates of MI and stroke, adequately discriminated MI risk (Harrell C statistic = 0.75; 95% CI, 0.71-0.78). Two data-derived models incorporating HIV-specific covariates exhibited weak calibration in a validation sample and did not discriminate risk any better (Harrell C statistic = 0.72; 95% CI, 0.67-0.78 and 0.73; 95% CI, 0.68-0.79) than the Pooled Cohort Equations. The Pooled Cohort Equations were moderately calibrated in the Centers for AIDS Research Network of Clinical Systems but predicted consistently lower MI rates.
Conclusions and relevance: The Pooled Cohort Equations discriminated MI risk and were moderately calibrated in this multicenter HIV cohort. Adding HIV-specific factors did not improve model performance. As HIV-infected cohorts capture and assess MI and stroke outcomes, researchers should revisit the performance of risk estimation tools.