ArticleCancer medicine2020
Personalizing age-specific survival prediction and risk stratification in intracranial grade II/III ependymoma.
Article in Cancer medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Clinical Features and Prognostic Indicators for Brainstem Ependymomas : A Population-Based Retrospective Surveillance, Epidemiology, and End Results Database Analysis.Journal of Korean Neurosurgical Society · 2026Article
- Prognostic Factors and Nomogram for Malignant Brainstem Ependymoma: A Population-Based Retrospective Surveillance, Epidemiology, and End Results Database Analysis.Cancer medicine · 2025Article
- Epidemiological characteristics of myxopapillary ependymoma and factors affecting overall survival: a SEER-based analysis.Translational cancer research · 2024Article
- Conditional survival estimates for ependymomas reveal the dynamic nature of prognostication.Discover oncology · 2024Article
- Whole-tumor histogram analysis of postcontrast T1-weighted and apparent diffusion coefficient in predicting the grade and proliferative activity of adult intracranial ependymomas.Neuroradiology · 2024Article
- Disease characteristics and clinical specific survival prediction of spinal ependymoma: a genetic and population-based study.Frontiers in neurology · 2024Article
- An Overview of Intracranial Ependymomas in Adults.Cancers · 2021Review
- Development and validation of prognostic nomogram in ependymoma: A retrospective analysis of the SEER database.Cancer medicine · 2021Article
- Personalizing age-specific survival prediction and risk stratification in intracranial grade II/III ependymoma.Cancer medicine · 2020Article
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Authors and funding
11 authors.
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Abstract
backgroundModels for estimation of survival rates of patients with intracranial grade II/III ependymoma (EPN) are scarce. Considering the heterogeneity in prognostic factors between pediatric and adult patients, we aimed to develop age-specific nomograms for predicting 3-, 5-, and 8-year survival for these patients.
methodsA total of 1390 cases (667 children; 723 adults) of intracranial grade II/III EPNs diagnosed between 1988 and 2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database for our study. Univariable and multivariable Cox analyses were employed to identify independent prognostic predictors. Age-specific nomograms were developed based on the results of multivariate Cox analyses. We also evaluated the performance of these predictive models by concordance index, calibration curves, time-dependent receiver operating characteristic curves, and decision curve analyses.
resultsConsiderable heterogeneity in prognostic factors was highlighted between pediatric and adult patients. Age, sex, tumor grade, surgery treatment and radiotherapy were identified as significant predictors of overall survival for children, and age, tumor grade, tumor size, surgery treatment, and marital status for adult. Based on these factors, age-specific nomogram models were established and internally validated. These models exhibited favorable discrimination and calibration characteristics. Nomogram-based risk classification systems were also constructed to facilitate risk stratification in EPNs for optimization of clinical management.
conclusionsWe developed the first nomograms and corresponding risk classification systems for predicting survival in patients with intracranial grade II/III EPN. These easily used tools can assist oncologists in making accurate survival evaluation.
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