Derivation and validation of SIDIAP-FHP score: A new risk model predicting cardiovascular disease in familial hypercholesterolemia phenotype

Rafel Ramos; Luís Masana; Marc Comas-Cufí; Maria García-Gil; Ruth Martí-Lluch; Anna Ponjoan; Núria Plana; Lia Alves-Cabratosa; Jaume Marrugat; Roberto Elosua; Irene R Dégano; Mauel A Gomez-Marcos; Alberto Zamora

doi:10.1016/j.atherosclerosis.2019.10.016

Derivation and validation of SIDIAP-FHP score: A new risk model predicting cardiovascular disease in familial hypercholesterolemia phenotype

Atherosclerosis. 2020 Jan:292:42-51. doi: 10.1016/j.atherosclerosis.2019.10.016. Epub 2019 Oct 30.

Authors

Affiliations

¹ Institut Universitari d'Investigació en Atenció Primària Jordi Gol (IDIAP J Gol), Catalonia, Spain; ISV Research Group. Research Unit in Primary Care, Primary Care Services, Girona. Catalan Institute of Health (ICS), Catalonia, Spain; Biomedical Research Institute, Girona (IdIBGi), ICS, Catalonia, Spain; Department of Medical Sciences, School of Medicine, University of Girona, Spain. Electronic address: ramos.girona.ics@gencat.cat.
² Xarxa de Unitats de Lipids de Catalunya (XULA), Girona, Spain; Lipids and Arteriosclerosis Research Unit, "Sant Joan" University Hospital, Internal Medicine Department, IISPV, Universitat Rovira i Virgili, CIBERDEM, Reus, Spain.
³ Institut Universitari d'Investigació en Atenció Primària Jordi Gol (IDIAP J Gol), Catalonia, Spain; ISV Research Group. Research Unit in Primary Care, Primary Care Services, Girona. Catalan Institute of Health (ICS), Catalonia, Spain.
⁴ Institut Universitari d'Investigació en Atenció Primària Jordi Gol (IDIAP J Gol), Catalonia, Spain; ISV Research Group. Research Unit in Primary Care, Primary Care Services, Girona. Catalan Institute of Health (ICS), Catalonia, Spain; Biomedical Research Institute, Girona (IdIBGi), ICS, Catalonia, Spain.
⁵ Registre Gironí del COR (REGICOR) Group, Municipal Institute for Medical Research (IMIM), Barcelona, Spain; CIBER of Cardiovascular Diseases (CIBERCV), Barcelona, Catalonia, Spain.
⁶ CIBER of Cardiovascular Diseases (CIBERCV), Barcelona, Catalonia, Spain; Faculty of Medicine, University of Vic-Central University of Catalonia (UVic-UCC), Vic, Spain; Cardiovascular, Epidemiology and Genetics Research Group (EGEC), Municipal Institute for Medical Research (IMIM), Barcelona, Spain.
⁷ Registre Gironí del COR (REGICOR) Group, Municipal Institute for Medical Research (IMIM), Barcelona, Spain; CIBER of Cardiovascular Diseases (CIBERCV), Barcelona, Catalonia, Spain; Faculty of Medicine, University of Vic-Central University of Catalonia (UVic-UCC), Vic, Spain.
⁸ . Institute of Biomedical Research of Salamanca (IBSAL), Primary Health Care Research Unit, The Alamedilla Health Center, Salamanca, Spain; Department of Medicine, University of Salamanca, Salamanca, Spain.
⁹ Department of Medical Sciences, School of Medicine, University of Girona, Spain; Xarxa de Unitats de Lipids de Catalunya (XULA), Girona, Spain; Lipids and Arteriosclerosis Unit, Blanes Hospital, Girona, Spain; Laboratory of Translational Medicine (Translab), School of Medicine, University of Girona, Spain.

PMID: 31759248
DOI: 10.1016/j.atherosclerosis.2019.10.016

Abstract

Background and aims: Assessment of individual cardiovascular risk, distinguishing primary and secondary prevention, would improve the clinical management of the population with familial hypercholesterolemia. We aimed to develop and validate two risk functions to predict incident and recurrent atherosclerotic cardiovascular disease (ASCVD) in a primary care-based population with familial hypercholesterolemia phenotype (FHP), and to compare their predictive capacity with that of the SpAnish Familial hypErcHolEsterolemiA cohoRT (SAFEHEART) risk equation (SAFEHEART-RE).

Methods: Data from the Catalan primary care system database (SIDIAP) of patients ≥18 years old with FHP in 2006-2013 were used to develop and validate two risk functions to predict incident and recurrent ASCVD. A validation dataset was also used to compare the model predictive capacity to that of SAFEHEART-RE.

Results: The new model (SIDIAP-FHP) included age, diabetes, smoking, sex (male), hypertension, and baseline low-density lipoprotein cholesterol in the primary prevention cohort and age, diabetes, smoking, and disease characteristics (progressive, recent, polyvascular, or included myocardial infarction) in the secondary prevention cohort. The models demonstrated a fair fit: C-Statistic: 0.71 (95%CI:0.68-0.75) in primary prevention and 0.65 (95%CI:0.60-0.70) in secondary prevention (higher than that of SAFEHEART-RE: 0.64 [95%CI:0.60-0.68] and 0.55 [95%CI:0.51-0.59], respectively; both p < 0.01). The Brier scores obtained with the SIDIAP-FHP score were significantly lower than that obtained with SAFEHEART-RE in both the primary and secondary prevention cohorts.

Conclusions: The SIDIAP-FHP score provides accurate ASCVD risk estimates for primary and secondary prevention in the FHP population, with better predictive capacity than that of SAFEHEART-RE in this general population, especially in persons with previous ASCVD.

Keywords: Atherosclerosis; Cardiovascular diseases; Familial hypercholesterolemia; Prevention; Risk assessment.

Publication types

Comparative Study
Validation Study

MeSH terms

Aged
Atherosclerosis / diagnosis*
Atherosclerosis / etiology*
Cohort Studies
Female
Humans
Hyperlipoproteinemia Type II / complications*
Hyperlipoproteinemia Type II / genetics
Male
Middle Aged
Models, Statistical*
Phenotype
Retrospective Studies
Risk Assessment / methods*