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Integrating clinical and image-based parameters for prediction of early post-prostatectomy incontinence recovery: simplified nomogram approach
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Integrating clinical and image-based parameters for prediction of early post-prostatectomy incontinence recovery: simplified nomogram approach
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Journal Article
Integrating clinical and image-based parameters for prediction of early post-prostatectomy incontinence recovery: simplified nomogram approach
2024
Overview
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.
Publisher
BioMed Central,BioMed Central Ltd,Springer Nature B.V,BMC
Subject
/ Biomedical and Life Sciences
/ Bladder
/ Complications and side effects
/ Health Promotion and Disease Prevention
/ Humans
/ Male
/ Nomogram
/ Oncology
/ Patients
/ Post-prostatectomy incontinence
/ Postoperative Complications - diagnostic imaging
/ Postoperative Complications - etiology
/ Prostatectomy - adverse effects
/ Prostatic Neoplasms - surgery
/ RARP
/ Robotic assisted radical prostatectomy
/ Robotic Surgical Procedures - adverse effects
/ Robotic Surgical Procedures - methods
/ Surgeons
/ Surgery
