TY - JOUR
T1 - Prediction of cancer specific survival after radical nephroureterectomy for upper tract urothelial carcinoma
T2 - Development of an optimized postoperative nomogram using decision curve analysis
AU - Rouprêt, Morgan
AU - Hupertan, Vincent
AU - Seisen, Thomas
AU - Colin, Pierre
AU - Xylinas, Evanguelos
AU - Yates, David R.
AU - Fajkovic, Harun
AU - Lotan, Yair
AU - Raman, Jay D.
AU - Zigeuner, Richard
AU - Remzi, Mesut
AU - Bolenz, Christian
AU - Novara, Giacomo
AU - Kassouf, Wassim
AU - Ouzzane, Adil
AU - Rozet, François
AU - Cussenot, Olivier
AU - Martinez-Salamanca, Juan I.
AU - Fritsche, Hans Martin
AU - Walton, Thomas J.
AU - Wood, Christopher G.
AU - Bensalah, Karim
AU - Karakiewicz, Pierre I.
AU - Montorsi, Francesco
AU - Margulis, Vitaly
AU - Shariat, Shahrokh F.
PY - 2013/5
Y1 - 2013/5
N2 - 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.
AB - 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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U2 - 10.1016/j.juro.2012.10.057
DO - 10.1016/j.juro.2012.10.057
M3 - Article
C2 - 23103802
AN - SCOPUS:84876291753
SN - 0022-5347
VL - 189
SP - 1662
EP - 1669
JO - Journal of Urology
JF - Journal of Urology
IS - 5
ER -