The addition of depression to the Framingham Risk Equation model for predicting coronary heart disease risk in women
| Autor: | Amanda L Stuart, Adrienne O'Neil, Paul Lewandowski, Mark A. Kotowicz, Felice N. Jacka, C. B. Taylor, Aaron J. Fisher, Julie A. Pasco, Michael Berk, Katherine J. Kibbey, Lana J. Williams, John Atherton |
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| Rok vydání: | 2015 |
| Předmět: |
medicine.medical_specialty
Epidemiology Population Context (language use) Coronary Disease 030204 cardiovascular system & hematology Risk Assessment 03 medical and health sciences 0302 clinical medicine Risk Factors Internal medicine medicine Humans 030212 general & internal medicine Myocardial infarction Longitudinal Studies Prospective Studies education Prospective cohort study education.field_of_study Depressive Disorder Framingham Risk Score Models Statistical Receiver operating characteristic Unstable angina business.industry Public Health Environmental and Occupational Health Australia medicine.disease Cardiology Female Risk assessment business |
| Zdroj: | Preventive medicine. 87 |
| ISSN: | 1096-0260 |
| Popis: | Background Depression is widely considered to be an independent and robust predictor of Coronary Heart Disease (CHD), however is seldom considered in the context of formal risk assessment. We assessed whether the addition of depression to the Framingham Risk Equation (FRE) improved accuracy for predicting 10-year CHD in a sample of women. Design A prospective, longitudinal design comprising an age-stratified, population-based sample of Australian women collected between 1993 and 2011 (n = 862). Methods Clinical depressive disorder was assessed using the Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders (SCID-I/NP), using retrospective age-of-onset data. A composite measure of CHD included non-fatal myocardial infarction, unstable angina coronary intervention or cardiac death. Cox proportional-hazards regression models were conducted and overall accuracy assessed using area under receiver operating characteristic (ROC) curve analysis. Results ROC curve analyses revealed that the addition of baseline depression status to the FRE model improved its overall accuracy (AUC:0.77, Specificity:0.70, Sensitivity:0.75) when compared to the original FRE model (AUC:0.75, Specificity:0.73, Sensitivity:0.67). However, when calibrated against the original model, the predicted number of events generated by the augmented version marginally over-estimated the true number observed. Conclusions The addition of a depression variable to the FRE equation improves the overall accuracy of the model for predicting 10-year CHD events in women, however may over-estimate the number of events that actually occur. This model now requires validation in larger samples as it could form a new CHD risk equation for women. |
| Databáze: | OpenAIRE |
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