The available prognostic models for overall survival (OS) in patients with metastatic urothelial carcinoma (UC) have been derived from clinical trial populations of cisplatin-treated patients.To develop a new model based on real-world patients.Individual patient-level data from 29 centers were collected, including metastatic UC and first-line cisplatin- or carboplatin-based chemotherapy administered between January 2006 and January 2011.First-line, platinum-based, combination chemotherapy.The population was randomly split into a development and a validation cohort. Generalized boosted regression modelling was used to screen out irrelevant variables and address multivariable analyses. Two nomograms were built to estimate OS probability, the first based on baseline factors and platinum agent, the second incorporating objective response (OR). The performance of the above nomograms and that of other available models was assessed. We plotted decision curves to evaluate the clinical usefulness of the two nomograms.A total of 1020 patients were analyzed (development: 687, validation: 333). In a platinum-stratified Cox model, significant variables for OS were performance status (p<0.001), white blood cell count (p=0.013), body mass index (p=0.003), ethnicity (p=0.012), lung, liver, or bone metastases (p<0.001), and prior perioperative chemotherapy (p=0.012). The c-index was 0.660. The distribution of the nomogram scores was associated with OR (p<0.001), and incorporating OR into the model further improved the c-index in the validation cohort (0.670).We developed and validated two nomograms for OS to be used before and after completion of first-line chemotherapy for metastatic UC.We proposed two models for estimating overall survival of patients with metastatic urothelial carcinoma receiving first-line, platinum-based chemotherapy. These nomograms have been developed on real-world patients who were treated outside of clinical trials and may be used irrespective of the chemotherapeutic platinum agent used.
View details for DOI 10.1016/j.eururo.2016.09.042
View details for Web of Science ID 000390565700047