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External validation of a prediction model for penile prosthesis implantation for erectile dysfunction management
The James Buchanan Brady Urological Institute and Department of Urology, The Johns Hopkins University School of Medicine, Baltimore,
Dec  2014 (Vol.  21, Issue  6, Pages( 7554 - 7559)
PMID: 25483764

Abstract

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  • INTRODUCTION:

    Penile prosthesis implantation (PPI) is the definitive surgical treatment for erectile dysfunction (ED), yet it is often delayed for a variety of reasons. From commercial and Medicare claims data, we previously developed a tool for determining a patient's likelihood of eventually receiving PPI. We validated this instrument's utility by comparing cohorts receiving surgical (PPI) versus non-surgical ED management at a single institution.

    MATERIAL AND METHODS:

    The prediction model was based on a logistic regression incorporating claims data on demographics, comorbidities and ED therapy. A risk score is calculated from the model as the product of relative risks for the individual variables. The current validation was a retrospective analysis of ED patients seen at this institution from January to December 2012. Inclusion criteria included ED diagnosis and either first-time PPI or non-surgical treatment (controls). Risk scores for patients receiving PPI were compared to those of non-surgical controls.

    RESULTS:

    We established a cohort of 60 PPI patients (mean age 54.4 ± 9.5) and compared them with 120 non-PPI patients (mean age 53.4 ± 11.2 years). The median score of the PPI cohort was 5.7 (IQR 2.8-9.9) versus the non-PPI cohort's 1.8 (IQR 0.9-5.5) (p < 0.0001). The area under the receiver operator characteristic curve for predicting eventual PPI was 0.72 (95% CI, 0.64-0.79) (p < 0.0001).

    CONCLUSION:

    The prediction model risk-stratified men who ultimately underwent PPI compared to non-surgically managed controls. This external validation study suggests that the prediction model may be used on an individual patient basis to support a recommendation of PPI for managing ED