Prediction of Cancer Specific Survival After Radical Nephroureterectomy for Upper Tract Urothelial Carcinoma: Development of an Optimized Postoperative Nomogram Using Decision Curve Analysis

Rouprêt, Morgan ; Hupertan, Vincent ; Seisen, Thomas ; Colin, Pierre ; Xylinas, Evanguelos ; Yates, David R. ; Fajkovic, Harun ; Lotan, Yair ; Raman, Jay D. ; Zigeuner, Richard ; Remzi, Mesut ; Bolenz, Christian ; Novara, Giacomo ; Kassouf, Wassim ; Ouzzane, Adil ; Rozet, François ; Cussenot, Olivier ; Martinez-Salamanca, Juan I. ; Fritsche, Hans-Martin ; Walton, Thomas J. ; Wood, Christopher G. ; Bensalah, Karim ; Karakiewicz, Pierre I. ; Montorsi, Francesco ; Margulis, Vitaly ; Shariat, Shahrokh F.

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Details

Item type:	Article
Journal or Publication Title:	Journal of Urology
Publisher:	ELSEVIER SCIENCE INC
Place of Publication:	NEW YORK
Volume:	189
Number of Issue or Book Chapter:	5
Page Range:	pp. 1662-1669
Date:	2013
Institutions:	Medicine > Lehrstuhl für Urologie
Identification Number:	Value Type 10.1016/j.juro.2012.10.057 DOI
Keywords:	PREOPERATIVE NOMOGRAM; PROGNOSTIC MODELS; OUTCOMES; PROSTATECTOMY; VALIDATION; RECURRENCE; ureter; kidney pelvis; carcinoma, transitional cell; survival; nomograms
Dewey Decimal Classification:	600 Technology > 610 Medical sciences Medicine
Status:	Published
Refereed:	Yes, this version has been refereed
Created at the University of Regensburg:	Yes
Item ID:	62583

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Abstract

Purpose: We conceived and proposed a unique and optimized nomogram to predict cancer specific survival after radical nephroureterectomy in patients with upper tract urothelial carcinoma by merging the 2 largest multicenter data sets reported in this population. Materials and Methods: The international and the French national collaborative groups on upper tract urothelial carcinoma pooled data on ...

Abstract

Purpose: We conceived and proposed a unique and optimized nomogram to predict cancer specific survival after radical nephroureterectomy in patients with upper tract urothelial carcinoma by merging the 2 largest multicenter data sets reported in this population. Materials and Methods: The international and the French national collaborative groups on upper tract urothelial carcinoma pooled data on 3,387 patients treated with radical nephroureterectomy for whom full data for nomogram development were available. The merged study population was randomly split into the development cohort (2,371) and the external validation cohort (1,016). Cox regressions were used for univariable and multivariable analyses, and to build different models. The ultimate reduced nomogram was assessed using Harrell's concordance index (c-index) and decision curve analysis. Results: Of the 2,371 patients in the nomogram development cohort 510 (21.5%) died of upper tract urothelial carcinoma during followup. The actuarial cancer specific survival probability at 5 years was 73.7% (95% CI 71.9-75.6). Decision curve analysis revealed that the use of the best model was associated with benefit gains relative to the prediction of cancer specific survival. The optimized nomogram included only 5 variables associated with cancer specific survival on multivariable analysis, those of age (p = 0.001), T stage (p <0.001), N stage (p = 0.001), architecture (p = 0.02) and lymphovascular invasion (p = 0.001). The discriminative accuracy of the nomogram was 0.8 (95% CI 0.77-0.86). Conclusions: Using standard pathological features obtained from the largest data set of upper tract urothelial carcinomas worldwide, we devised and validated an accurate and ultimate nomogram, superior to any single clinical variable, for predicting cancer specific survival after radical nephroureterectomy.

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