Systematic Review of Validity Assessments of Framingham Risk Score Results in Health Economic Modelling of Lipid-Modifying Therapies in Europe

Jonas Hermansson and Thomas Kahan ()
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Jonas Hermansson: Karolinska Institutet
Thomas Kahan: Karolinska Institutet

PharmacoEconomics, 2018, vol. 36, issue 2, No 7, 205-213

Abstract: Abstract Background The Framingham Risk Score is used both in the clinical setting and in health economic analyses to predict the risk for future coronary heart disease events. Based on an American population, the Framingham Risk Score has been criticised for potential overestimation of risk in European populations. Objective We investigated whether the use of the Framingham Risk Score actually was validated in health economic studies that modelled the effects of lipid-lowering treatment with statins on coronary heart disease events in European populations. Methods In this systematic literature review of all relevant published studies in English (literature searched September 2016 in PubMed, EMBASE and SCOPUS), 99 studies were identified and 22 were screened in full text, 18 of which were included. Key data were extracted and synthesised narratively. Results The only type of validation identified was a comparison against coronary heart disease risk data from one primary preventive and one secondary preventive clinical investigation, and from observational population data in one study. Taken together, those three studies reported an overall satisfactory accuracy in the results obtained by Framingham Risk Score predictions, but the Framingham Risk Score tended to underestimate non-fatal myocardial infarctions. In five studies, potential issues in applying the Framingham Risk Score on a European population were not addressed. Conclusion Further studies are needed to ascertain that the Framingham Risk Score can accurately predict cardiovascular outcome in health economic modelling studies on lipid-lowering therapy in European populations. Future modelling studies using the Framingham Risk Score would benefit from validating the results against other data.

Date: 2018
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DOI: 10.1007/s40273-017-0578-1

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