Comprehensive prediction model of urinary incontinence one year following robot-assisted radical prostatectomy - Abstract

Objectives: Urinary incontinence (UI) still remains one of the major functional complications after robot-assisted radical prostatectomy (RARP).

As the cause for UI is multifactorial, it is quite difficult to make a prediction preoperatively. Considering intraoperative and postoperative risk factors, besides the preoperative ones, we designed an incontinence prediction model, administered 1 month after the surgery, in order to identify incontinent patients at 1 year.

Patients and Methods: We retrospectively reviewed 244 patients who underwent RARP at our institution. Only 209 patients had sufficient data, a 1-year follow-up and were continent preoperatively. The association of UI with the risk factors was assessed by univariable and multivariable regression models.

Results: There was a 17.2% global UI rate at 1 year after RARP. Only age-adjusted Charlson comorbidity index, erectile function assessed by International Index of Erectile Function-5, prostate volume, nerve-sparing status and 24-hour urine loss at 1 month correlated with UI (p = 0.032, 0.009, 0.031, 0.018 and < 0.001, respectively). The accuracy of the prediction model of UI was 92.8% (c-index), with an area under the curve of 91.9%.

Conclusion: Age-adjusted Charlson comorbidity index, International Index of Erectile Function-5, prostate volume, nerve-sparing status and 24-hour urine loss at 1 month after RARP can predict an individual's risk of UI at 1 year after RARP with good accuracy. Further external validation is required in order to generalize the use of this model.

Written by:
Barnoiu OS, Baron Lopez F, Garcia Galisteo E, Soler Martinez J, Vozmediano Chicharro R, Del Rosal Samaniego JM, Machuca Santacruz J, Navarro Vilchez P, Sanchez Luque J, Bautista Vidal C, Gomez Lechuga P, Baena Gonzalez V.   Are you the author?
Carlos Haya Hospital, Malaga, Spain.

Reference: Urol Int. 2013;90(1):31-5.
doi: 10.1159/000343735


PubMed Abstract
PMID: 23207744

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