You have accessJournal of UrologyGeneral & Epidemiological Trends & Socioeconomics: Evidence-based Medicine & Outcomes1 Apr 201155 AN INNOVATIVE WEB TOOL FOR OBJECTIFYING CRITICAL DECISION-MAKING IN PATIENTS WITH UROLOGIC CANCERS Alexander Kutikov, Joseph Bland, Daniel Canter, Boris Rozenfeld, Steven Sterious, David Y.T. Chen, and Robert G. Uzzo Alexander KutikovAlexander Kutikov Philadelphia, PA More articles by this author , Joseph BlandJoseph Bland Philadelphia, PA More articles by this author , Daniel CanterDaniel Canter Philadelphia, PA More articles by this author , Boris RozenfeldBoris Rozenfeld Philadelphia, PA More articles by this author , Steven SteriousSteven Sterious Philadelphia, PA More articles by this author , David Y.T. ChenDavid Y.T. Chen Philadelphia, PA More articles by this author , and Robert G. UzzoRobert G. Uzzo Philadelphia, PA More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2011.02.2657AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Despite the development of treatment guidelines, quantitative risk stratification and management of urologic malignancies remains overly subjective. Nomograms and statistical algorithms offer an objective basis for critical decision-making by both physicians and patients. These tools remain largely underutilized in routine clinical practice due to barriers of access and ease of use. We sought to create a novel internet tool where published urologic cancer risk stratification and predictive models can be easily accessed, interpreted, and applied by physicians and patients. METHODS A MEDLINE review was performed to identify published nomograms/models relevant to prostate, renal, urothelial, testicular and penile cancers. Nomograms were grouped by defining characteristics (pre-operative versus post operative predictive models, predictive models for metastatic disease, etc). Additional operationalized models included staging tools, NCCN surveillance models and ACS cancer statistics. Nomograms were selected based on predictive accuracy, applicability, and ability to objectify risk stratification. Only nomograms with an AUC of greater than 0.7 were operationalized. Redundant nomograms were excluded. RESULTS www.cancernomograms.com organizes and operationalizes over 40 interactive predictive models for urologic malignancies. Each model was developed as an independent software program and deployed as an interactive flash object embedded in an HTML page allowing point of care risk calculation (Fig. 1). The website decreased calculation of nomogram metrics by 15 subjects (8 scenarios per subject) from minutes to seconds, demonstrating improved efficacy and utilization of a computer-based platform for nomograms (p=0.0003). CONCLUSIONS www.cancernomograms.com is a novel web portal that allows point of care risk quantification using published statistical models. This web tool affords real-time objectification of critical-decision making in a busy clinical setting. Moreover, the portal offers users the opportunity to submit requests to have the latest predictive models operationalized. © 2011 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 185Issue 4SApril 2011Page: e23-e24 Advertisement Copyright & Permissions© 2011 by American Urological Association Education and Research, Inc.MetricsAuthor Information Alexander Kutikov Philadelphia, PA More articles by this author Joseph Bland Philadelphia, PA More articles by this author Daniel Canter Philadelphia, PA More articles by this author Boris Rozenfeld Philadelphia, PA More articles by this author Steven Sterious Philadelphia, PA More articles by this author David Y.T. Chen Philadelphia, PA More articles by this author Robert G. Uzzo Philadelphia, PA More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...
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