Elsevier

Preventive Medicine

Volume 61, April 2014, Pages 66-74
Preventive Medicine

Derivation and validation of a set of 10-year cardiovascular risk predictive functions in Spain: The FRESCO Study

https://doi.org/10.1016/j.ypmed.2013.12.031Get rights and content

Highlights

  • A new set of coronary, cerebrovascular and cardiovascular risk functions is developed and validated.

  • These risk functions are valid for the Spanish population aged 35 to 79 years.

  • The Framingham adapted function tends to overestimate the risk in the Spanish population.

Abstract

Objective

To derive and validate a set of functions to predict coronary heart disease (CHD) and stroke, and validate the Framingham-REGICOR function.

Method

Pooled analysis of 11 population-based Spanish cohorts (1992–2005) with 50,408 eligible participants. Baseline smoking, diabetes, systolic blood pressure (SBP), lipid profile, and body mass index were recorded. A ten-year follow-up included re-examinations/telephone contact and cross-linkage with mortality registries. For each sex, two models were fitted for CHD, stroke, and both end-points combined: model A was adjusted for age, smoking, and body mass index and model B for age, smoking, diabetes, SBP, total and HDL cholesterol, and for hypertension treatment by SBP, and age by smoking and by SBP interactions.

Results

The 9.3-year median follow-up accumulated 2973 cardiovascular events. The C-statistic improved from model A to model B for CHD (0.66 to 0.71 for men; 0.70 to 0.74 for women) and the combined CHD-stroke end-points (0.68 to 0.71; 0.72 to 0.75, respectively), but not for stroke alone. Framingham-REGICOR had similar C-statistics but overestimated CHD risk.

Conclusions

The new functions accurately estimate 10-year stroke and CHD risk in the adult population of a typical southern European country. The Framingham-REGICOR function provided similar CHD prediction but overestimated risk.

Introduction

Prevention of cardiovascular (CV) diseases is a major public health objective (Perk et al., 2012, Reiner et al., 2011). Three main strategies exist to achieve this aim: the population approach, a focus on high-risk individuals, and opportunistic screening. The population approach includes policy initiatives and community interventions to promote healthy lifestyles and environmental changes (Rose, 1985), such as smoking ban legislation (Meyers et al., 2009). High-risk strategies are based on the intensive modification of risk factor exposure in individuals with a high probability of developing CV diseases. Both approaches are considered cost-effective for the primary prevention of these diseases (Emberson et al., 2004).

Opportunistic screening uses CV risk functions – calculations based on a series of characteristics (typically sex, age, and risk factor profile) – to predict an individual's risk of having a CV event, usually within the next 10 years (D'Agostino et al., 2008, Kannel et al., 2004). Risk functions have been developed to assess cardiovascular (Hippisley-Cox et al., 2007, Pencina et al., 2009, Perk et al., 2012, Ridker et al., 2007, Ridker et al., 2008), coronary (Assmann et al., 2002, Lloyd-Jones et al., 2004, Wilson et al., 1998), or stroke risk (Wolf et al., 1991) in different countries and continents; most of them are designed for the population aged 35 to 74 years. The widely used coronary risk functions developed by the Framingham investigators (D'Agostino et al., 2008, Kannel et al., 2004) have been adapted and validated in different populations (D'Agostino et al., 2001), including Spain, where the Framingham-REGICOR adapted function was developed by the REGICOR (Registre Gironí del Cor or Girona Heart Registry) investigators (Marrugat et al., 2003, Marrugat et al., 2007, Marrugat et al., 2011).

In addition to the adaptation and calibration of risk functions validated for different populations, the development of new risk functions is especially relevant for countries with low cardiovascular incidence and mortality. New risk functions should aim for simplicity and consider different ensembles of factors. For example: sex and age provide a reasonable starting-point for considering individual CV risk; the inclusion of non-laboratory variables can be useful for self-appraisal of risk (Gaziano et al., 2008); additional laboratory measurements that could improve the predictive capacity of the function could be incorporated into the clinical settings. Moreover, expanding the upper age limit to 79 years would be wise, particularly in low-incidence, low-mortality southern Europe as life expectancy continues to increase. Finally, another attempt to simplify and facilitate CV prevention has led to the so-called “global risk” prediction, which includes at least coronary heart disease (CHD) and stroke end-points in the same predictive function (D'Agostino et al., 2008).

The objective of the FRESCO study (Función de Riesgo ESpañola de acontecimientos Coronarios y Otros, or “Spanish risk function of coronary and other cardiovascular events”) was to develop and validate for the Spanish population aged 35 to 79 years a set of CHD, stroke, and global CV risk functions of differing complexities that use easily implemented risk factor measurements and can be automatically calculated by electronic medical records systems. In the subset of 35- to 74-year-old participants, the study also compared the performance of these FRESCO functions and the validated Framingham-REGICOR function.

Section snippets

Design and participants

We conducted a pooled analysis of individual data from 11 population cohorts in 7 Spanish regions examined between 1992 and 2005 with similar methods. The component studies (and the associated regions) were: CORSAIB (Rigo Carratala et al., 2005) (Balearic Islands), DRECA-2 (Santos et al., 2009) (Andalusia), MURCIA (Huerta et al., 2010) (Murcia), EMMA (Ramos et al., 2012), REGICOR (Grau et al., 2007), REUS (Cabré et al., 2008), ZONA FRANCA (Alzamora et al., 2010) (Catalonia), NAVARRA and RIVANA (

Results

The 64,824 recruited participants yielded 50,408 eligible subjects (23,289 (46.2%) men and 27,119 (53.8%) women) aged 35 to 79 years who were followed a median of 9.3 years (447,516 person-years). The flow chart of inclusion and first CV event is displayed in Fig. 1.

The derivation and validation cohort characteristics are described in Table 1: no important differences were observed. Participant characteristics and a summary of the CV events are detailed by component cohort and sex in

Discussion

We present a set of valid, simple, and incremental risk functions to predict CHD, stroke, and global CV events at 10 years for a typical southern European population aged 35 to 79 years, using both classic and non-laboratory cardiovascular risk factors. Moreover, we report that the Framingham-REGICOR adapted function has an adequate discrimination capacity but tends to overestimate the risk in the Spanish population.

The functions presented here are relatively simple, and some of them could be

Conclusions

The new functions presented here accurately and precisely estimate 10-year risk of stroke and CHD, separately or combined, in a typical southern European population aged 35 to 79 years. In the population subgroup aged 35 to 74 years, the new CHD functions discriminate as well as the Framingham-REGICOR risk function currently used in this age group. On the other hand, Framingham-REGICOR tended to systematically overestimate CHD risk in the validation cohort.

Funding

This work was supported by MARATO TV3 (081630), Instituto de Salud Carlos III — Fondo Europeo de Desarrollo Regional — European Regions Development Funds [Red de Investigación Cardiovascular RD12/0042 (Programa HERACLES); Red RedIAPP RD06/0018; PI081327; PI1101801]; AGAUR [2009 SGR 1195]; CIBER Epidemiología y Salud Pública; and CIBER de Fisiopatología de la Obesidad y la Nutrición. MG was supported by the Instituto de Salud Carlos III — Fondo Europeo de Desarrollo Regional — European Regions

Conflict of interest

The authors declare that they have no conflict of interest.

Acknowledgments

The authors wish to thank Ruth Martí, Susana Tello, Marta Cabañero, Yolanda Ferrer, Sandra Farré, and Esmeralda Gómez for the data management and administrative support, and Elaine Lilly, Ph.D., Writer's First Aid, for the English language revision of the manuscript. We also appreciate the collaboration of the Registre de Mortalitat de Catalunya del Servei d'Informació i Estudis, Departament de Salut, Generalitat de Catalunya (Anna Puigdefàbregas, Gloria Ribas, and Rosa Gispert).

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