title: Framingham risk score for prediction of cardiovascular diseases: a population-based study from southern Europe.
abstract: BACKGROUND
  The question about what risk function should be used in primary prevention remains unanswered. The Framingham Study proposed a new algorithm based on three key ideas: use of the four risk factors with the most weight (cholesterol, blood pressure, diabetes and smoking), prediction of overall cardiovascular diseases and incorporating the concept of vascular age. The objective of this study was to apply this new function in a cohort of the general non Anglo-Saxon population, with a 10-year follow-up to determine its validity.
  
  
  METHODS
  The cohort was studied in 1992-94 and again in 2004-06. The sample comprised 959 randomly-selected persons, aged 30-74 years, who were representative of the population of Albacete, Spain. At the first examination cycle, needed data for the new function were collected and at the second examination, data on all events were recorded during the follow-up period. Discrimination was studied with ROC curves. Comparisons of prediction models and reality in tertiles (Hosmer-Lemeshow) were performed, and the individual survival functions were calculated.
  
  
  RESULTS
  The mean risks for women and men, respectively, were 11.3% and 19.7% and the areas under the ROC curve were 0.789 (95%CI, 0.716-0.863) and 0.780 (95%CI, 0.713-0.847) (P<0.001, both). Cardiovascular disease events occurred in the top risk tertiles. Of note were the negative predictive values in both sexes, and a good specificity in women (85.6%) and sensitivity in men (79.1%) when their risk for cardiovascular disease was high. This model overestimates the risk in older women and in middle-aged men. The cumulative probability of individual survival by tertiles was significant in both sexes (P<0.001).
  
  
  CONCLUSIONS
  The results support the proposal for "reclassification" of Framingham. This study, with a few exceptions, passed the test of discrimination and calibration in a random sample of the general population from southern Europe.
authors.affiliation: Community Medicine, Zone 3 Primary Health Care Centre, Albacete, Spain.
authors.forename: Luis M
authors.initials: LM
authors.lastname: Artigao-Rodenas
authors.forename: Julio A
authors.initials: JA
authors.lastname: Carbayo-Herencia
authors.forename: Juan A
authors.initials: JA
authors.lastname: Divisón-Garrote
authors.forename: Vicente F
authors.initials: VF
authors.lastname: Gil-Guillén
authors.forename: Javier
authors.initials: J
authors.lastname: Massó-Orozco
authors.forename: Marta
authors.initials: M
authors.lastname: Simarro-Rueda
authors.forename: Francisca
authors.initials: F
authors.lastname: Molina-Escribano
authors.forename: Carlos
authors.initials: C
authors.lastname: Sanchis
authors.forename: Lucinio
authors.initials: L
authors.lastname: Carrión-Valero
authors.forename: Enrique
authors.initials: E
authors.lastname: López de Coca
authors.forename: David
authors.initials: D
authors.lastname: Caldevilla
authors.forename: Juan
authors.initials: J
authors.lastname: López-Abril
authors.forename: Concepción
authors.initials: C
authors.lastname: Carratalá-Munuera
authors.forename: Adriana
authors.initials: A
authors.lastname: Lopez-Pineda
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D002318:Cardiovascular Diseases / Q000453:epidemiology*; D015331:Cohort Studies; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D011336:Probability; D012372:ROC Curve; D018570:Risk Assessment; D012307:Risk Factors; D012737:Sex Factors; D013030:Spain / Q000453:epidemiology
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