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Development and Validation of Nomograms Predicting the 5- and 8-Year Overall and Cancer-Specific Survival of Bladder Cancer Patients Based on SEER Program

Background: Bladder cancer is often prone to recurrence and metastasis. We sought to construct nomogram models to predict the overall survival (OS) and cancer-specific survival (CSS) of bladder cancer patients. Methods: A reliable random split-sample approach was used to divide patients into two gro...

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Detalles Bibliográficos
Autores principales: Wen, Peng, Wen, Jiao, Huang, Xiaolong, Wang, Fengze
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9962885/
https://www.ncbi.nlm.nih.gov/pubmed/36835849
http://dx.doi.org/10.3390/jcm12041314
Descripción
Sumario:Background: Bladder cancer is often prone to recurrence and metastasis. We sought to construct nomogram models to predict the overall survival (OS) and cancer-specific survival (CSS) of bladder cancer patients. Methods: A reliable random split-sample approach was used to divide patients into two groups: modeling and validation cohorts. Uni-variate and multivariate survival analyses were used to obtain the independent prognostic risk factors based on the modeling cohort. A nomogram was constructed using the R package, “rms”. Harrell’s concordance index (C-index), calibration curves and receiver operating characteristic (ROC) curves were applied to evaluate the discrimination, sensitivity and specificity of the nomograms using the R packages “hmisc”, “rms” and “timeROC”. A decision curve analysis (DCA) was used to evaluate the clinical value of the nomograms via R package “stdca.R”. Results: 10,478 and 10,379 patients were assigned into nomogram modeling and validation cohorts, respectively (split ratio ≈ 1:1). For OS and CSS, the C-index values for internal validation were 0.738 and 0.780, respectively, and the C-index values for external validation were 0.739 and 0.784, respectively. The area under the ROC curve (AUC) values for 5- and 8-year OS and CSS were all greater than 0.7. The calibration curves show that the predicted probability values of 5- and 8-year OS and CSS are close to the actual OS and CSS. The decision curve analysis revealed that the two nomograms have a positive clinical benefit. Conclusion: We successfully constructed two nomograms to forecast OS and CSS for bladder cancer patients. This information can help clinicians conduct prognostic evaluations in an individualized manner and tailor personalized treatment plans.