Adrienne O'Neil1, Aaron J Fisher2, Katherine J Kibbey3, Felice N Jacka4, Mark A Kotowicz5, Lana J Williams6, Amanda L Stuart6, Michael Berk7, Paul A Lewandowski6, John J Atherton8, Craig B Taylor9, Julie A Pasco10. 1. Melbourne School of Population & Global Health, University of Melbourne, Carlton, VIC, Australia; School of Medicine, Deakin University, Geelong, VIC, Australia; School of Public Health and Preventive Medicine, Monash University, Prahran, VIC, Australia. Electronic address: adrienne.oneil@unimelb.edu.au. 2. Department of Psychology, University of California Berkeley, CA, USA. 3. Barwon Health, Geelong Hospital, Geelong, VIC, Australia; Monash Health, Melbourne, VIC, Australia; School of Clinical Sciences, Monash University VIC, Australia. 4. School of Medicine, Deakin University, Geelong, VIC, Australia; Department of Psychiatry, The University of Melbourne, Parkville, VIC, Australia; Centre for Adolescent Health, Murdoch Children's Research Centre, Parkville, VIC, Australia; Black Dog Institute, Hospital Road, Prince of Wales Hospital, Randwick, NSW, Australia. 5. School of Medicine, Deakin University, Geelong, VIC, Australia; Barwon Health, Geelong Hospital, Geelong, VIC, Australia; Black Dog Institute, Hospital Road, Prince of Wales Hospital, Randwick, NSW, Australia. 6. School of Medicine, Deakin University, Geelong, VIC, Australia. 7. School of Medicine, Deakin University, Geelong, VIC, Australia; School of Public Health and Preventive Medicine, Monash University, Prahran, VIC, Australia; Department of Psychiatry, The University of Melbourne, Parkville, VIC, Australia; Orygen Youth Health Research Centre, Parkville, VIC, Australia; Mental Health Research Institute, Parkville, VIC, Australia. 8. Department of Cardiology, Royal Brisbane and Women's Hospital, QLD, Australia; School of Medicine, University of Queensland, QLD, Australia. 9. Department of Psychiatry & Behavioral Medicine, Stanford University & Palo Alto University, CA, USA. 10. School of Medicine, Deakin University, Geelong, VIC, Australia; Western Medical School, The University of Melbourne, St Albans, VIC, Australia.
Abstract
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.
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.
Authors: Amjad M Ahmed; Waqas T Qureshi; Sherif Sakr; Michael J Blaha; Clinton A Brawner; Jonathan K Ehrman; Steven J Keteyian; Mouaz H Al-Mallah Journal: Clin Cardiol Date: 2018-04-17 Impact factor: 2.882
Authors: Allison J Carroll; Reto Auer; Laura A Colangelo; Mercedes R Carnethon; David R Jacobs; Jesse C Stewart; Rachel Widome; John Jeffrey Carr; Kiang Liu; Brian Hitsman Journal: J Dual Diagn Date: 2017-01-27
Authors: Roger C M Ho; Anna C Chua; Bach X Tran; Carol C Choo; Syeda Fabeha Husain; Giang T Vu; Roger S McIntyre; Cyrus S H Ho Journal: Int J Environ Res Public Health Date: 2018-09-21 Impact factor: 3.390