Literature DB >> 28370267

External validation of a nomogram for identification of pathologically favorable disease in intermediate risk prostate cancer patients.

Jean-Baptiste Beauval1, Bastien Cabarrou2, Giorgio Gandaglia3, Pierre-Marie Patard1, Adil Ouzzane4, Alexandre de la Taille5, Michel Soulié1, Alberto Briganti6, Guillaume Ploussard7, François Rozet8, Mathieu Roumiguié1.   

Abstract

OBJECTIVE: To establish an external validation of the new nomogram from Gandaglia et al which provides estimates of the probability of pathological favorable disease in pre-operatively defined intermediate-risk PCa. PATIENTS AND METHODS: Overall, 2928 intermediate-risk PCa patients according to the D'Amico classification undergoing RP and bilateral lymph node dissection in seven academic centres between 2000 and 2011. Pathologically favorable PCa was defined as low-grade organ-confined disease. The Receiver Operating Characteristic (ROC) curve was obtained to quantify the overall accuracy (Area Under the Curve, AUC) of the model to predict specimen-confined (SC) disease. Calibration curve was then constructed to illustrate the relationship between the risk-estimates obtained by the model and the observed proportion of SC disease. Kaplan-Meier method was used for PSA recurrence-free survival (PSA-RFS) assessment.
RESULTS: Median age was 68 years. 10.6% patients finally presented pathologically favorable disease characteristics at RP. A higher PSAD (OR = 0.01; 95%CI = 0.00-0.04; P < 0.0001) and percentage of positive cores (OR = 0.97; 95%CI = 0.96-0.98; P < 0.0001) were associated with a reduced probability of favorable disease at RP in multivariate analysis. ROC curve analysis showed strongest accuracy of the model (AUC = 0.82; 95%CI = 0.79-0.84). Favorable PCa had a significantly better PSA recurrence-free survival rates as compared to unfavorable PCa after RP (94.2% vs 74.4% at 4 years, P < 0.0001).
CONCLUSIONS: This external validation of the Gandaglia nomogram shows relevant accuracy with one out of ten patients in this intermediate risk PCa group with pathologically proven organ-confined disease. This validated risk calculator can help physician to distinguish favorable intermediate risk PCa that can be treated by conservative approach or safer nerve-sparing surgery.
© 2017 Wiley Periodicals, Inc.

Entities:  

Keywords:  biochemical recurrence; disease; favorable; final pathology; intermediate-risk prostate cancer; nomogram; radical prostatectomy

Mesh:

Year:  2017        PMID: 28370267     DOI: 10.1002/pros.23348

Source DB:  PubMed          Journal:  Prostate        ISSN: 0270-4137            Impact factor:   4.104


  4 in total

1.  External evaluation of the Briganti nomogram to predict lymph node metastases in intermediate-risk prostate cancer patients.

Authors:  Nicolas Peilleron; Arnaud Seigneurin; Caroline Herault; Camille Verry; Michel Bolla; Jean-Jacques Rambeaud; Jean-Luc Descotes; Jean-Alexandre Long; Gaelle Fiard
Journal:  World J Urol       Date:  2020-06-24       Impact factor: 4.226

2.  The Ability of Prostate Health Index (PHI) to Predict Gleason Score in Patients With Prostate Cancer and Discriminate Patients Between Gleason Score 6 and Gleason Score Higher Than 6-A Study on 320 Patients After Radical Prostatectomy.

Authors:  Olga Dolejsova; Radek Kucera; Radka Fuchsova; Ondrej Topolcan; Hana Svobodova; Ondrej Hes; Viktor Eret; Ladislav Pecen; Milan Hora
Journal:  Technol Cancer Res Treat       Date:  2018-01-01

Review 3.  Biochemical recurrence after radical prostatectomy: Current status of its use as a treatment endpoint and early management strategies.

Authors:  Barrett Z McCormick; Ali M Mahmoud; Stephen B Williams; John W Davis
Journal:  Indian J Urol       Date:  2019 Jan-Mar

4.  Deep Neural Networks Outperform the CAPRA Score in Predicting Biochemical Recurrence After Prostatectomy.

Authors:  Paul Sargos; Nicolas Leduc; Nicolas Giraud; Giorgio Gandaglia; Mathieu Roumiguié; Guillaume Ploussard; Francois Rozet; Michel Soulié; Romain Mathieu; Pierre Mongiat Artus; Tamim Niazi; Vincent Vinh-Hung; Jean-Baptiste Beauval
Journal:  Front Oncol       Date:  2021-02-11       Impact factor: 6.244

  4 in total

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