ArticleFrontiers in endocrinology2023
Development and external validation of dual online tools for prognostic assessment in elderly patients with high-grade glioma: a comprehensive study using SEER and Chinese cohorts.
Article in Frontiers in endocrinology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed, 5 citations in OpenAlex.
- Mapping the global research landscape and innovations on elderly glioma: a bibliometric analysis.Frontiers in oncology · 2026Article
- Integrated clinicopathological-radiomic-blood model for glioma survival prediction via machine learning: a multicenter cohort study.Neurosurgical review · 2025Article
- Identification of the high-risk population facing early death in older patients with primary intracranial glioma: a retrospective cohort study.Frontiers in endocrinology · 2025Article
- Variable screening and model construction for prognosis of elderly patients with lower-grade gliomas based on LASSO-Cox regression: a population-based cohort study.Frontiers in immunology · 2024Article
- Development and validation of esophageal cancer prediction model based on DeepSurv model: A cohort study.Science progressArticle
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Authors and funding
14 authors at 3 institutions in 2 countries.
Funding
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Abstract
Background: Elderly individuals diagnosed with high-grade gliomas frequently experience unfavorable outcomes. We aimed to design two web-based instruments for prognosis to predict overall survival (OS) and cancer-specific survival (CSS), assisting clinical decision-making. Methods: We scrutinized data from the SEER database on 5,245 elderly patients diagnosed with high-grade glioma between 2000-2020, segmenting them into training (3,672) and validation (1,573) subsets. An additional external validation cohort was obtained from our institution. Prognostic determinants were pinpointed using Cox regression analyses, which facilitated the construction of the nomogram. The nomogram's predictive precision for OS and CSS was gauged using calibration and ROC curves, the C-index, and decision curve analysis (DCA). Based on risk scores, patients were stratified into high or low-risk categories, and survival disparities were explored. Results: Using multivariate Cox regression, we identified several prognostic factors for overall survival (OS) and cancer-specific survival (CSS) in elderly patients with high-grade gliomas, including age, tumor location, size, surgical technique, and therapies. Two digital nomograms were formulated anchored on these determinants. For OS, the C-index values in the training, internal, and external validation cohorts were 0.734, 0.729, and 0.701, respectively. We also derived AUC values for 3-, 6-, and 12-month periods. For CSS, the C-index values for the training and validation groups were 0.733 and 0.727, with analogous AUC metrics. The efficacy and clinical relevance of the nomograms were corroborated via ROC curves, calibration plots, and DCA for both cohorts. Conclusion: Our investigation pinpointed pivotal risk factors in elderly glioma patients, leading to the development of an instrumental prognostic nomogram for OS and CSS. This instrument offers invaluable insights to optimize treatment strategies.
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