Predicting outcomes in patients with urologic cancers

Abstract

To review the available predictive and prognostic models addressing oncological outcomes in patients with bladder, kidney and prostate cancer. A systematic review of the English literature on the discussed topics was performed. All manuscripts were retrieved from PubMed, and restricted to entries with an abstract. Keywords were 'diagnosis', 'stage', 'prognosis' and 'nomograms' for bladder, kidney and prostate cancer, respectively. Of these, 70 were selected for inclusion, based on content, clinical relevance, quality, level of evidence, and year of publication. We identified six models for prediction of the natural history of treated bladder cancer. We report on 15 models for patients with kidney cancer. Of these, two preoperative prognostic models predict recurrence-free survival, three postoperative models address disease recurrence, five postoperative models predict disease-specific survival, and, finally, five models predict overall survival in patients with metastatic kidney cancer. For prostate cancer, we found eight models predicting biopsy outcome, 17 models for pretreatment prediction of pathologic stage of clinically localized disease, eight models for prediction of biochemical recurrence, and, finally, six models predicting cancer control outcomes in relapsed or hormone-refractory metastatic prostate cancer. In patients with urologic malignancies, cancer control outcomes can be predicted in a highly accurate and evidence-based fashion.