A Novel Tool For Predicting Extracapsular Extension During Graded Partial Nerve Sparing In Radical Prostatectomy

Keywords

extracapsular extension; nomogram; prostate; prostate cancer; robotic prostatectomy; staging

Abstract

Objectives: To create a statistical tool for the estimation of extracapsular extension (ECE) level of prostate cancer and determine the nerve-sparing (NS) approach that can be safely performed during radical prostatectomy (RP). Patients and Methods: A total of 11 794 lobes, from 6 360 patients who underwent robot-assisted RP between 2008 and 2016 were evaluated. Clinicopathological features were included in a statistical algorithm for the prediction of the maximum ECE width. Five multivariable logistic models were estimated for: presence of ECE and ECE width of >1, >2, >3, and >4 mm. A five-zone decision rule based on a lower and upper threshold is proposed. Using a graphical interface, surgeons can view patient's pre-treatment characteristics and a curve showing the estimated probabilities for ECE amount together with the areas identified by the decision rule. Results: Of the 6 360 patients, 1 803 (28.4%) were affected by non-organ-confined disease. ECE was present in 1 351 lobes (11.4%) and extended beyond the capsule for >1, >2, >3, and >4 mm in 498 (4.2%), 261 (2.2%), 148 (1.3%), 99 (0.8%) cases, respectively. ECE width was up to 15 mm (interquartile range 1.00–2.00). The five logistic models showed good predictive performance, the area under the receiver operating characteristic curve was: 0.81 for ECE, and 0.84, 0.85, 0.88, and 0.90 for ECE width of >1, >2, >3, and >4 mm, respectively. Conclusion: This novel tool predicts with good accuracy the presence and amount of ECE. Furthermore, the graphical interface available at www.prece.it can support surgeons in patient counselling and preoperative planning.

Publication Date

3-1-2018

Publication Title

BJU International

Volume

121

Issue

3

Number of Pages

373-382

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1111/bju.14026

Socpus ID

85042466978 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85042466978

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