Development and validation of a nomogram for predicting survival in patients with non-metastatic primary adenocarcinoma of the bladder.

backgroundTo develop a nomogram for predicting cancer-specific survival (CSS) of patients with non-metastatic primary adenocarcinoma of the bladder (NMACB).

methodsWe used a retrospective cohort study design. Patient data were obtained from the SEER database, univariate and multivariate Cox regression analyses were performed to identify factors associated with CSS. A nomogram visualization model was established using R language software to predict survival rate. Harrell's concordance index (C-index), area under the receiver operating characteristic (ROC) curve (AUC) in addition to calibration plots were used to assess the performance of the model.

resultsA total of 1,635 patients were included in the study. A multivariate Cox regression model indicated that age, histological type, grade, stage, and surgery were independent covariates associated with CSS. Using these prognostic factors, a nomogram was constructed. Harrell's C indices for CSS were 0.729 in the training cohort and 0.716 in the validation cohort. AUC values were 0.769, 0.735 and 0.724 for 1, 3, and 5-year in the training cohort, and 0.738, 0.727 and 0.713 for 1, 3 and 5-year in the validation cohort, respectively. The AUC values and calibration plots indicated that the nomogram provided good predictive performance.

conclusionsA nomogram for predicting CSS in patients with NMACB was developed to assist clinicians in the accurate prediction of mortality risk to allow them to recommend a personalized treatment modality.