Robot-Assisted Radical Prostatectomy After Prior Transurethral Resection of Prostate: An Analysis of Perioperative, Functional, Pathologic, and Oncologic Outcomes.
Rajesh Raj BajpaiShirin RazdanMarcos A SanchezBalaji N ReddySanjay RazdanPublished in: Journal of endourology (2022)
Background: We performed a retrospective comparison of surgical, oncologic, and functional outcomes after robot-assisted radical prostatectomy between patients who have undergone prior transurethral resection of prostate (TURP) to TURP-naive patients. Methods: Past robotic prostatectomy hospital data were scrutinized to form two matched groups of patients: those who have undergone prior TURP and TURP-naive patients. The perioperative and pathologic data along with functional and oncologic outcomes for a period of 3 years were compared between groups. Results: Compared with TURP-naive patients, prior TURP patients experienced longer robot-assisted laparoscopic prostatectomy times ( p < 0.001), increased incidence of bladder neck reconstruction ( p = 0.03), greater blood loss ( p = 0.0001), and lesser nerve sparing ( p < 0.01). Complication rates ( p = 0.3), positive surgical margin ( p = 0.4), extracapsular disease ( p = 0.3), or seminal vesicle invasion ( p = 0.1) were comparable between groups. Continence ( p = 0.5) and potency ( p = 0.1) at 1 year were not different between groups. Biochemical recurrence rates were not different at 3 years ( p = 0.9). Diabetes slowed recovery of continence in patients with prior TURP compared with TURP-naive patients until 6 months after surgery. Conclusion: Although prior TURP makes subsequent robotic prostatectomy more technically demanding, it can be safely performed by experienced surgeons without compromising long-term functional or oncologic outcomes.
Keyphrases
- robot assisted
- end stage renal disease
- prostate cancer
- radical prostatectomy
- newly diagnosed
- ejection fraction
- chronic kidney disease
- peritoneal dialysis
- healthcare
- emergency department
- prognostic factors
- skeletal muscle
- acute kidney injury
- patient reported outcomes
- machine learning
- radiation therapy
- metabolic syndrome
- electronic health record
- neoadjuvant chemotherapy
- big data
- weight loss