Introduction: Accurate estimates of risk are essential for physicians if they are to
recommend a specific management to patients with bladder cancer. In this review, we
discuss the criteria for the evaluation of nomograms and review current available
nomograms for advanced bladder cancer.
Methods: A retrospective review of the Pubmed database between 2002 and 2008 was
performed using the keywords `nomogram' and `bladder'. We limited the articles to
advanced bladder cancer. We recorded input variables, prediction form, number of
patients used to develop the prediction tools, the outcome being predicted,
prediction tool-specific features, predictive accuracy, and whether validation was
performed.
Results: We discuss the characteristics needed to evaluate nomograms such as
predictive accuracy, calibration, generalizability, level of complexity, effect of
competing risks, conditional probabilities, and head-to-head comparison with other
prediction methods. The predictive accuracies of the pre-cystectomy tools (n = 2)
range from ~65—75% and that of the post-cystectomy tools (n = 5) range
from ~75—80%. While some of these nomograms are well-calibrated and
outperform AJCC staging, none has been externally validated. To date, four studies
demonstrated a statistically significant improvement in predictive accuracy of
nomograms by including biomarkers.
Conclusions: Nomograms provide accurate individualized estimates of outcomes. They
currently represent the most accurate and discriminatory decision-making aids tools
for predicting outcomes in patients with bladder cancer. Use of current nomograms
could improve current selection of patients for standard therapy and investigational
trial design by ensuring homogeneous groups. The addition of biological markers to
the currently available nomograms using clinical and pathologic data holds the
promise of improving prediction and refining management of patients with bladder
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