Prediction of recovery time of urinary incontinence following robot‐assisted laparoscopic prostatectomy

Abstract

Objectives Postoperative urinary incontinence recovery following robot‐assisted laparoscopic prostatectomy is an important outcome. We investigated whether factors that affect urinary incontinence can predict the duration of postoperative incontinence recovery. Methods A total of 310 patients underwent robot‐assisted laparoscopic prostatectomy. Continence recovery was defined as either pad‐free or a safety pad only status. Univariate and multivariate analyses were performed on clinical variables to identify those that were associated with continence recovery. A scoring system to predict recovered continence was constructed using statistically significant variables. The validity of this tool was tested in a new cohort of 273 patients. Results Factors associated with recovery of urinary incontinence were membranous urethral length, preservation of bilateral neurovascular bundles, and a preoperative Prostate Imaging Reporting and Data System score of ≥3 in the apex. Age was related only to incontinence recovery at 1 month. To prepare the score, weighting was performed using the estimated values. Using the developed scoring system, participants in the verification set were divided into three groups. The early recovery group had a median incontinence recovery of 4 (4–12) weeks, the medium recovery group, 12 (4–24) weeks, and the late recovery group, 24 (24–48) weeks, which was a significant difference (p < 0.001). Conclusions The applied scoring system based on preoperative factors related to incontinence and derived from patient groups was significantly associated with continence recovery time. In patients undergoing robot‐assisted laparoscopic prostatectomy, our unit‐weighted regression model of clinical variables can predict the duration of continence recovery.

Cribriform pattern 4/intraductal carcinoma of the prostate and persistent prostate‐specific antigen after radical prostatectomy

“…[β]-coefficient) was determined, and a formula for calculating the persistent PSA prediction score (multiple regression formula) was created. 12 To keep the scores close to integers and intuitive for the user, all β-coefficients were standardized with the lowest having a value of respectively (Figure S1A; P < 0.001). Three year castration-resistant PCa-free survival rates were 93.0% and 99.1% for persistent and without persistent PSA levels, respectively (Figure S1B; P = 0.003).…”

“…Using factors from logistic regression analysis, models were developed to predict persistent PSA levels after RARP. The contribution of each variable to persistent PSA prediction (standardized coefficient: beta [β]‐coefficient) was determined, and a formula for calculating the persistent PSA prediction score (multiple regression formula) was created 12 . To keep the scores close to integers and intuitive for the user, all β‐coefficients were standardized with the lowest having a value of 1.…”

“…The contribution of each variable to persistent PSA prediction (standardized coefficient: beta [β]‐coefficient) was determined, and a formula for calculating the persistent PSA prediction score (multiple regression formula) was created. 12 To keep the scores close to integers and intuitive for the user, all β‐coefficients were standardized with the lowest having a value of 1. Individual risk scores were obtained by summing up the risk factors.…”