ArticleJournal of clinical medicine2023
Web-Based Nomograms for Overall Survival and Cancer-Specific Survival of Bladder Cancer Patients with Bone Metastasis: A Retrospective Cohort Study from SEER Database.
Article in Journal of clinical medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Interpretable machine learning models for bladder cancer overall survival prediction development and external validation via SEER database and Chinese cohort analysis.Discover oncology · 2026Article
- Development and validation of competing risk nomograms for predicting cancer‑specific mortality in non-metastatic patients with non‑muscle invasive urothelial bladder cancer.Scientific reports · 2024Article
- Correlation analysis between BRAFHeliyon · 2024Article
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Authors and funding
10 authors.
Funding
Abstract
backgroundOur study aimed to explore the prognostic factors of bladder cancer with bone metastasis (BCBM) and develop prediction models to predict the overall survival (OS) and cancer-specific survival (CSS) of BCBM patients.
methodsA total of 1438 patients with BCBM were obtained from the SEER database. Patients from 2010 to 2016 were randomly divided into training and validation datasets (7:3), while patients from 2017 were divided for external testing. Nomograms were established using prognostic factors identified through Cox regression analyses and validated internally and externally. The concordance index (C-index), calibration plots, and time-dependent receiver operating characteristic (ROC) curves were used to evaluate the discrimination and calibration of nomogram models, while decision curve analyses (DCA) and Kaplan-Meier (KM) curves were used to estimate the clinical applicability.
resultsMarital status, tumor metastasis (brain, liver, and lung), primary site surgery, and chemotherapy were indicated as independent prognostic factors for OS and CSS. Calibration plots and the overall C-index showed a novel agreement between the observed and predicted outcomes. Nomograms revealed significant advantages in OS and CSS predictions. AUCs for internal and external validation were listed as follows: for OS, 3-month AUCs were 0.853 and 0.849; 6-month AUCs were 0.873 and 0.832; 12-month AUCs were 0.825 and 0.805; for CSS, 3-month AUCs were 0.849 and 0.847; 6-month AUCs were 0.870 and 0.824; 12-month AUCs were 0.815 and 0.797, respectively. DCA curves demonstrated good clinical benefit, and KM curves showed distinct stratification performance.
conclusionThe nomograms as web-based tools were proved to be accurate, efficient, and clinically beneficial, which might help in patient management and clinical decision-making for BCBM patients.
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