1. Integrating clinical and image-based parameters for prediction of early post-prostatectomy incontinence recovery: simplified nomogram approach
- Author
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I-Hung Shao, Sy-Yuan Chen, Hung-Yi Chen, Ting-Wen Sheng, Ying-Hsu Chang, Chung-Yi Liu, Liang-Kang Huang, Hung-Chen Kan, Po-Hung Lin, Kai-Jie Yu, Cheng-Keng Chuang, See-Tong Pang, and Chun-Te Wu
- Subjects
Robotic assisted radical prostatectomy ,RARP ,Prostate cancer ,Urinary incontinence ,Post-prostatectomy incontinence ,Nomogram ,Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,RC254-282 - Abstract
Abstract Purpose This study aimed to develop a novel model that combines both clinical and image-based parameters to predict early recovery of urinary incontinence after robotic-assisted radical prostatectomy (RARP) more easily and precisely. Materials and methods We retrospectively enrolled data from patients who underwent RARP performed by a single surgeon. Clinical parameters were collected through medical chart review. All patients received cystography one week after RARP to evaluate the anastomosis healing condition. All cystography images were analyzed by a single radiologist who was blinded to the clinical status of the patients. Multivariate analysis was performed to select significant predictors for early post-prostatectomy incontinence (PPI) recovery, defined as being pad-free within four weeks after surgery. Results A total of 293 patients were enrolled in this study. Among them, 26.7% experienced immediate dryness after surgery, while 47.6% achieved being pad-free within one month. The overall continence rate was over 90% six months after surgery. In univariate analysis, factors associated with early PPI recovery were BMI, T stage, NVB preservation, surgical margin status, downward bladder neck, and bladder neck angle on cystography. BMI, NVB preservation, and downward bladder neck remained significant in multivariate analysis (p-values = 0.041, 0.027, and 0.023, respectively). A nomogram model was established based on these three predictors. Conclusion This is the first model to combine preoperative clinical factors, peri-surgical factors, and postoperative image-based factors to predict PPI recovery after RARP. This model can assist clinicians in taking optimal actions for PPI and also reduce patient anxiety.
- Published
- 2024
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