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A prognostic model for predicting urinary incontinence after robot‐assisted radical prostatectomy
Author(s) -
Honda Masashi,
Kawamoto Bunya,
Morizane Shuichi,
Hikita Katsuya,
Muraoka Kuniyasu,
Sejima Takehiro,
Takenaka Atsushi
Publication year - 2017
Publication title -
the international journal of medical robotics and computer assisted surgery
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.556
H-Index - 53
eISSN - 1478-596X
pISSN - 1478-5951
DOI - 10.1002/rcs.1780
Subject(s) - medicine , prostatectomy , urinary incontinence , urology , logistic regression , cystometry , magnetic resonance imaging , proportional hazards model , urodynamic testing , surgery , radiology , prostate , urinary bladder , cancer
Background The aim of this study is to develop a novel prognostic model for estimating the risk of postoperative urinary incontinence (UI) after robot‐assisted radical prostatectomy (RARP). Methods Participants comprised 131 men who underwent RARP at our hospital from 2011 to 2013. Cox regression analyses were performed to evaluate associations between UI and preoperative factors including filling cystometry and pressure‐flow study results and magnetic resonance imaging. Results Logistic regression analyses revealed significant associations between membranous urethral length or levator thickness and UI at 3 and 6 months. Stratification produced high (membranous urethral length < 9.5 mm or levator thickness < 9.0 mm) and low (membranous urethral length ≥ 9.5 mm and levator thickness ≥ 9.0 mm) UI risk groups. These inter‐group differences in UI rate were significant. Conclusions We developed a novel prognostic model based on preoperative patient data that can be used for patient counselling.