ArticleBMC neurology2020
Establishment of age group classification for risk stratification in glioma patients.
Article in BMC neurology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
58 citing papers in PubMed, 110 citations in OpenAlex.
- Age-related risk factors and treatment outcomes in geriatric patients with spinal low-grade glioma: A nationwide analysis.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2026Article
- Association of Autophagy-Related Gene Expression Profiles with Survival in Diffuse Astrocytic Tumors.Cancers · 2026Article
- Competing subclones and fitness diversity shape tumor evolution across cancer types.Bioinformatics (Oxford, England) · 2026Article
- Age-dependent differences in survival of patients with early breast cancer: analysis of SUCCESS A, B, C trials.Archives of gynecology and obstetrics · 2026Article
- Age-Stratified Modeling of Clinical Heterogeneity in Polycystic Ovary Morphology Using Ultrasound-Based Machine Learning.International journal of women's health · 2026Article
- Mapping the global research landscape and innovations on elderly glioma: a bibliometric analysis.Frontiers in oncology · 2026Article
- GlioSurv: interpretable transformer for multimodal, individualized survival prediction in diffuse glioma.NPJ digital medicine · 2025Article
- Clinical and VASARI Features to PredictAJNR. American journal of neuroradiology · 2025Article
- Comparative performance of logistic regression, multilayer perceptron and decision tree models for predicting surgical pressure injuries: a retrospective cohort study.BMJ health & care informatics · 2025Article
- Predicting p53 Status in IDH-Mutant Gliomas Using MRI-Based Radiomic Model.Cancer medicine · 2025Article
- The impact of sociodemographic background on clinical presentation of high-grade gliomas: a multi-institutional retrospective analysis.Journal of neuro-oncology · 2025Article
- FANCI is involved in the malignant progression of glioma cells by regulating the Akt/Bcl-2 signaling pathway.Discover oncology · 2025Article
- Correlation between Isocitrate Dehydrogenase Mutation and Immunohistochemical Expression of DNA Mismatch Repair Proteins in the Prognosis of Gliomas.Asian Pacific journal of cancer prevention : APJCP · 2025Article
- Mutant IDH impairs chromatin binding by PDGFB to promote chromosome instability.bioRxiv : the preprint server for biology · 2025Article
- Multicenter Surveillance ofInfection and drug resistance · 2025Article
- Elevated glioma-related cortical glutamateBrain communications · 2025Article
- How Does Subjective Social Status Associate With Depression Among the Labor Force Population in China? - Analysis of the Mediation Effect Based on the Sense of Social Equity.International journal of public health · 2025Article
- [A predictive model for survival outcomes of glioma patients based on multi-parametric, multi-regional MRI radiomics features and clinical features].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2024Article
- Pediatric Desmoid Tumor of the Head and Neck: A Systematic Review and Modified Framework for Management by Age Group.Plastic and reconstructive surgery. Global open · 2024Article
- Utilizing the amide proton transfer technique to characterize diffuse gliomas based on the WHO 2021 classification of CNS tumors.The neuroradiology journal · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAge is associated with the prognosis of glioma patients, but there is no uniform standard of age-group classification to evaluate the prognosis of glioma patients. In this study, we aimed to establish an age group classification for risk stratification in glioma patients.
methods1502 patients diagnosed with gliomas at Nanfang Hospital between 2000 and 2018 were enrolled. The WHO grade of glioma was used as a dependent variable to evaluate the effect of age on risk stratification. The evaluation model was established by logistic regression, and the Akaike information criterion (AIC) value of the model was used to determine the optimal cutoff points for age-classification. The differences in gender, WHO grade, pathological subtype, tumor cell differentiation, tumor size, tumor location, and molecular markers between different age groups were analyzed. The molecular markers included GFAP, EMA, MGMT, P53, NeuN, Oligo2, EGFR, VEGF, IDH1, Ki-67, PR, CD3, H3K27M, TS, and 1p/19q status.
resultsThe proportion of men with glioma was higher than that of women with glioma (58.3% vs 41.7%). Analysis of age showed that appropriate classifications of age group were 0-14 years old (pediatric group), 15-47 years old (youth group), 48-63 years old (middle-aged group), and ≥ 64 years old (elderly group).The proportions of glioblastoma and large tumor size (4-6 cm) increased with age (p = 0.000, p = 0.018, respectively). Analysis of the pathological molecular markers across the four age groups showed that the proportion of patients with larger than 10% area of Ki-67 expression or positive PR expression increased with age (p = 0.000, p = 0.017, respectively).
conclusionsAppropriate classifications of the age group for risk stratification are 0-14 years old (pediatric group), 15-47 years old (young group), 48-63 years old (middle age group) and ≥ 64 years old (elderly group). This age group classification is effective in evaluating the risk of glioblastoma in glioma patients.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.