Observed versus predicted cardiovascular events and all-cause death in HIV infection: a longitudinal cohort study

Abstract

Background: The aim of the study was to assess the applicability of an algorithm predicting 10-year cardiovascular disease (CVD) generated in the setting of the Framingham Heart Study to a real-life, contemporary Italian cohort of HIV-positive subjects.

Methods: The study was an observational longitudinal cohort study. The probability for 10-year CVD events according to the Framingham algorithm was assessed in 369 consecutive HIV-positive participants free from overt CVD enrolled in 2004, who were followed for a median of 10.0 years (interquartile range, 9.1-10.1). Cardiovascular events included myocardial infarction, hospitalized heart failure, revascularized angina, sudden cardiac death, stroke, peripheral arterial disease.

Results: Over 3097 person-years of observation, we observed a total of 34 CVD events, whereas Framingham algorithm predicted the occurrence of 34.3 CVD events. CVD event rate was 11.0/1000 person-years of follow-up. In a receiver operating characteristics curve analysis, Framingham risk equation showed an excellent predictive value for incident CVD events (c-statistics, 0.83; 95% confidence interval, 0.76-0.90). In a multivariable Cox analysis, age, smoking and diabetes were independent predictors of CVD events. All-cause death rate was 20.0/1000 person-years of follow-up (n = 62 deaths). Causes of death included liver diseases (18), malignancies (14), AIDS-related (11); cardiovascular (9) and others (10). In a Cox analysis, age, AIDS diagnosis and chronic hepatitis were independent predictors of death.

Conclusions: Observed CVD events in HIV-infected patients were well predicted by Framingham algorithm. Established major CVD risk factors are the strongest determinants of CVD morbidity in an Italian contemporary cohort of HIV-positive subjects. Interventions to modify traditional risk factors are urgently needed in HIV people.

Keywords: Atherosclerosis; Cardiovascular diseases; Framingham risk; HIV; Mortality.

Fig. 1

Flow-chart of the study

Fig. 2

Predicted and observed 10-year cardiovascular event rate by different cardiovascular risk strata (Framingham Risk Score) and in the whole population

Fig. 3

ROC curve analysis receiver operating characteristic (ROC) curve analysis, describing areas under curves with their 95% confidence intervals (CI) and comparing them to the null hypothesis (area = 0.5). An area under the ROC curve of 1.0 indicates perfect classification of cases (future event) and non-cases (future censoring), whereas 0.5 means that the classification is not better than chance