54 DOES ERECTILE DYSFUNCTION IMPROVE CARDIOVASCULAR DISEASE RISK PREDICTION?

Abstract

You have accessJournal of UrologyGeneral & Epidemiological Trends & Socioeconomics: Evidence-based Medicine & Outcomes II1 Apr 201054 DOES ERECTILE DYSFUNCTION IMPROVE CARDIOVASCULAR DISEASE RISK PREDICTION? Andre Araujo, Susan Hall, Peter Ganz, Gretchen Chiu, Raymond Rosen, Varant Kupelian, and John McKinlay Andre AraujoAndre Araujo Watertown, MA More articles by this author , Susan HallSusan Hall Watertown, MA More articles by this author , Peter GanzPeter Ganz San Francisco, CA More articles by this author , Gretchen ChiuGretchen Chiu Watertown, MA More articles by this author , Raymond RosenRaymond Rosen Watertown, MA More articles by this author , Varant KupelianVarant Kupelian Watertown, MA More articles by this author , and John McKinlayJohn McKinlay Watertown, MA More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2010.02.100AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Erectile dysfunction (ED) and cardiovascular disease (CVD) share pathophysiological mechanisms and often co-occur. It is unknown whether ED improves the prediction of CVD beyond traditional risk factors. We sought to determine whether ED predicts CVD beyond traditional risk factors METHODS The Massachusetts Male Aging Study (MMAS) is a population-based, prospective study of 1,709 men aged 40-70 y. ED was measured by self-report. Data on CVD were obtained from 3 sources: questionnaire, linkage of the MMAS database with the National Death Index (NDI), and medical records. CVD was defined by ICD-9/ICD-10 codes 390-459/I00-I99. Subjects were followed for CVD for an average follow-up of 11.7 years. The association between ED and CVD was examined using the Cox proportional hazards regression model. The reclassification of CVD risk associated with ED was assessed using a method that quantifies net reclassification improvement (NRI). This involved the fitting of two statistical models with CVD as the outcome: one including age and Framingham risk score, and a second that added ED. Based on this, we evaluated changes in risk category classification separately for CVD cases and non-cases that occurred during the first 10 years of follow-up, with results expressed in the NRI. RESULTS 1,057 men with complete data who were free of CVD and diabetes at baseline were included. During follow-up, 261 new cases of CVD occurred (200 of these were confirmed by NDI or medical record). ED was associated with CVD incidence controlling for age (Hazard Ratio (HR): 1.42 (95% Confidence Interval (CI)): 1.05, 1.90), age and traditional CVD risk factors (HR: 1.41, 95% CI: 1.05, 1.90), as well as age and Framingham risk score (HR: 1.40, 95% CI: 1.04-1.88). Despite these significant findings, ED did not significantly improve the prediction of CVD incidence beyond traditional risk factors. Specifically, based on the data presented in the Table, the NRI for ED was calculated as 3.1% (95% CI: -2.4%, 8.5%), which was not statistically significant (p = .27). CONCLUSIONS Independent of established CVD risk factors, ED is significantly associated with increased CVD incidence. Nonetheless, ED does not improve the prediction of who will and will not develop CVD beyond that offered by traditional risk factors. © 2010 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 183Issue 4SApril 2010Page: e23 Advertisement Copyright & Permissions© 2010 by American Urological Association Education and Research, Inc.MetricsAuthor Information Andre Araujo Watertown, MA More articles by this author Susan Hall Watertown, MA More articles by this author Peter Ganz San Francisco, CA More articles by this author Gretchen Chiu Watertown, MA More articles by this author Raymond Rosen Watertown, MA More articles by this author Varant Kupelian Watertown, MA More articles by this author John McKinlay Watertown, MA More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...