Development of appropriate coronary heart disease risk prediction models in HIV-infected patients.

Prediction equations for coronary heart disease (CHD) risk are useful tools that inform clinicians and patients about the absolute risk for developing CHD. A basic principle in CHD prevention is that the intensity of risk-reducing interventions should be based on the individual patient’s absolute CHD risk. In the current era of human immunodeficiency virus (HIV) infection and highly active antiretroviral therapy (HAART), knowing one’s CHD risk and acting to reduce it have become imperative to long-term survival. Given the increased life expectancy as a result of HAART, more HIV-infected persons will experience complications not related to HIV per se and will reach an age at which they are at increased risk for developing CHD. However, existing CHD risk prediction equations were not developed in HIV-infected adults or children. In the general population, CHD risk prediction models derived from the Framingham Heart Study estimate the risk of total CHD (angina pectoris, myocardial infarction [MI], CHD death)1 or estimate the risk for hard CHD end points (MI, CHD).2 The traditional risk factors used to predict CHD risk and how risk factor alterations affect CHD outcomes in HIV-infected and HIV-seronegative people are summarized in the Table. The estimates of the relative effects of traditional risk factors on CHD outcomes appear similar between HIVand non–HIVinfected patients. However, they are based on only 2 studies in HIV-infected patients. Although traditional CHD risk factors may operate in the same manner in HIV patients as in the general population, there may still be a need to identify and evaluate HIV-specific CHD risk factors and equations, to refine existing CHD prediction equations, and to develop new HIV-specific CHD prediction equations for adults, adolescents, and children. To date, Framingham CHD risk predictions have performed reasonably well when applied to HIV-infected patients. We need to evaluate whether new HIV-specific CHD risk prediction approaches perform better than existing algorithms. This task represents a formidable challenge but is crucial to improving care and reducing healthcare costs for people living with HIV.