Prediction of cancer specific survival after radical nephroureterectomy for upper tract urothelial carcinoma: Development of an optimized postoperative nomogram using decision curve analysis

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

Research output: Contribution to journalArticle

80 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)1662-1669
Number of pages8
JournalJournal of Urology
Issue number5
Publication statusPublished - May 2013



  • carcinoma, transitional cell
  • kidney pelvis
  • nomograms
  • survival
  • ureter

ASJC Scopus subject areas

  • Urology

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