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Clin Cancer Res. 2006 Nov 15;12(22):6663-76.

Nomograms provide improved accuracy for predicting survival after radical cystectomy.

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  • 1Department of Urology, University of Texas Southwestern Medical Center, Dallas, Texas, and The Brady Urological Institute, The Johns Hopkins Hospital, Baltimore, MD, USA.



To develop multivariate nomograms that determine the probabilities of all-cause and bladder cancer-specific survival after radical cystectomy and to compare their predictive accuracy to that of American Joint Committee on Cancer (AJCC) staging.


We used Cox proportional hazards regression analyses to model variables of 731 consecutive patients treated with radical cystectomy and bilateral pelvic lymphadenectomy for bladder transitional cell carcinoma. Variables included age of patient, gender, pathologic stage (pT), pathologic grade, carcinoma in situ, lymphovascular invasion (LVI), lymph node status (pN), neoadjuvant chemotherapy (NACH), adjuvant chemotherapy (ACH), and adjuvant external beam radiotherapy (AXRT). Two hundred bootstrap resamples were used to reduce overfit bias and for internal validation.


During a mean follow-up of 36.4 months, 290 of 731 (39.7%) patients died; 196 of 290 patients (67.6%) died of bladder cancer. Actuarial all-cause survival estimates were 56.3% [95% confidence interval (95% CI), 51.8-60.6%] and 42.9% (95% CI, 37.3-48.4%) at 5 and 8 years after cystectomy, respectively. Actuarial cancer-specific survival estimates were 67.3% (62.9-71.3%) and 58.7% (52.7-64.2%) at 5 and 8 years, respectively. The accuracy of a nomogram for prediction of all-cause survival (0.732) that included patient age, pT, pN, LVI, NACH, ACH, and AXRT was significantly superior (P=0.001) to that of AJCC staging-based risk grouping (0.615). Similarly, the accuracy of a nomogram for prediction of cancer-specific survival that included pT, pN, LVI, NACH, and AXRT (0.791) was significantly superior (P=0.001) to that of AJCC staging-based risk grouping (0.663).


Multivariate nomograms provide a more accurate and relevant individualized prediction of survival after cystectomy compared with conventional prediction models, thereby allowing for improved patient counseling and treatment selection.

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