BACKGROUND: The implementation of the Framingham risk models and Pooled Cohort Equations (PCE) is currently recommended in the United States for predicting ten-year risk of developing cardiovascular disease (CVD) in individuals. Over the past few years, these prediction models have been extensively validated in other individuals, settings and countries.
OBJECTIVES: To systematically review and summarize the discrimination and calibration of three CVD prediction models, and to determine heterogeneity in this performance across subpopulations or geographical regions.
METHODS: In December 2015, Medline and Embase were searched for studies investigating the external validation of three CVD risk equations (Framingham Wilson 1998, Framingham ATP III 2002 guideline and PCE 2013). This search was combined with a search in Web of Science and Scopus for citations of these three articles. Studies published before June 2013 were identified from a previous review in which we mapped all CVD risk prediction models until that date. Studies were eligible for inclusion if they externally validated the original prediction model without updating, in a general population setting. Critical appraisal was performed based on the CHARMS checklist. Data were extracted on participant selection, case-mix, essential study design characteristics, and model performance (quantified by the c-statistic and observed/expected ratio). Performance estimates were summarized using random effects metaanalysis models that accounted for differences in case-mix to explore sources of heterogeneity.
RESULTS: The search identified 10,687 references, of which 1,501 were screened in full text and 45 met our eligibility criteria. These articles described the external validation of Framingham Wilson (25 articles), Framingham ATP III (15 articles) or the PCE (10 articles). Our meta-analytical results will be presented during the MEMTAB symposium as we are currently meta-analyzing the results. We will present the overall range of performance of the three risk equations and attempt to compare these to each other. Furthermore, we will present the range of performance for casemix differences such as age, comorbidities and treatment.
CONCLUSION: The results of this study can help in identifying which of these three CVD models can reliably be used, whether there is heterogeneity in their performance and whether there are subpopulations for which further research is necessary to improve CVD risk prediction.
