Can the Risk of Cardiovascular Disease in HIV-Infected Patients Be Estimated from Conventional Risk Prediction Tools?

Although the striking benefits of combination antiretroviral therapy continue to prevail, a number of complications to treatment have been observed, including the increased risk of metabolic complications and the risk of cardiovascular disease associated with some antiretroviral drugs. The preponderance of studies assessing clinical outcomes have identified a risk associated with protease inhibitor (PI) treatment [1–4]. In general, the incidence of cardiovascular disease is not high in most HIV-infected populations studied, which consist mainly of younger individuals (although , for all age groups, the incidence has been found to be higher among HIV-infected individuals than among matched HIV-uninfected control groups) [5–7]. For the individual, the absolute risk of car-diovascular disease results from the composite risk factor profile, comprising age, sex, diabetes status, family history of car-diovascular disease, and modifiable risks. With the aging of the HIV-infected population , brought about by improved survival among HIV-infected patients, it is likely that rates of cardiovascular disease in this population will increase in the future unless interventions to reduce risk factors are actively pursued. At present, cardiovascular disease is one of the most frequent causes of death in the HIV-infected population. Asymptomatic patients who are thought to be at high risk of cardiovascular disease need to be identified so that they can be offered advice about medical interventions and lifestyle changes. Current guidelines recommend that the risk of cardiovascular disease be estimated from a conventional risk-prediction model, such as the Framingham score, which combines different risk factors into a numeric estimate of absolute risk. However, few studies have explored whether such models accurately predict the risk in HIV-infected patients. Such models may not accurately predict the risk in this population, because (1) these patients are generally younger than populations for whom risk-prediction tools were developed, (2) there may be an independent effect of the underlying HIV infection, (3) an independent effect of PI treatment has been observed, and (4) the effect of some of the conventional risk factors may differ from what has been observed in the background population, as outlined below. In the Data Collection on Adverse Effects of Anti-HIV Drugs cohort collaboration , which includes HIV-infected persons from Europe, Australia, and the United States, an earlier prediction model from the Framingham Study [8] was found to slightly under-predict the risk of myocardial infarction, whereas the underestimation was even greater for a Euro-pean prediction model [9]. The report by Kaplan et al. …