title: Predicting cardiovascular events using three stage Discriminant Function is much more accurate than Framingham or QRISK.
abstract: The two best known approaches to predicting cardiovascular risk are Framingham and QRISK. Both methods correctly predict less than 70% of cases, with a high ratio of false positive predictions to true predictions. Each uses a combination of predictors that is applied to the data only once. The present approach uses the Discriminant Function with multiple applications. A British sample of data on cardiovascular risk was analysed. Principal Components analysis was used to reveal the underlying structure of the data-it identified four independent determinants of the data. Discriminant Function analysis in three stages was then used to accommodate the difficulties of dealing with multiple determinants. Ninety-four percent of the cases with cardiovascular incidents (CVI) were predicted correctly up to more than 20 years ahead, with a misclassification rate overall of 2.8 errors for every one correct. When checked for likely shrinkage from sample to sample using the Jacknife method 92% of CVI's were correctly predicted. Instead of a single application of a linear combination of predictors to find those people most likely to have cardiovascular events a repeated application of the predictors to the residuals from the previous prediction stage is likely to find a much higher proportion of true predictions and with much less error. The results also allow for a simple way of conveying the risk of CVI to individual patients.
authors: Faculty of Medical and Health Sciences, Clinical School, Auckland University, Hamilton, New Zealand. marshrw@hotmail.com
authors: Reginald Walter
authors: RW
authors: Marsh
mesh_terms: D000367:Age Factors; D001794:Blood Pressure; D005189:False Positive Reactions; D006801:Humans; D008055:Lipids / Q000097:blood; D008297:Male; D008875:Middle Aged; D009203:Myocardial Infarction / Q000453:epidemiology*; D025341:Principal Component Analysis; D018570:Risk Assessment; D012680:Sensitivity and Specificity; D020521:Stroke / Q000453:epidemiology*
chemical_list: D008055:Lipids