Traumatic Brain Injury and Risk of Intracranial Meningioma : A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Meningiomas are the most common primary intracranial tumors, but the role of traumatic brain injury (TBI) as a risk factor remains unclear. This study aimed to systematically review and quantitatively synthesize the available observational evidence on the association between TBI and subsequent meningioma risk. We conducted a systematic review and meta-analysis of observational studies following PRISMA guidelines. PubMed, Scopus, Web of Science, and Cochrane databases were searched through December 5, 2025. Studies comparing meningioma incidence in individuals with and without a history of TBI were included. Risk of bias was assessed using the Newcastle-Ottawa Scale. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using a random-effects models. Heterogeneity and sensitivity analyses were performed. In results, ten observational studies (seven case-control and three cohort studies) were included in the systematic review, with eight contributing to the quantitative synthesis. The pooled analysis demonstrated a statistically significant association between TBI and meningioma (OR = 1.96; 95% CI [1.31 to 2.95]; p = 0.0012) with moderate heterogeneity (I² = 65.6%). Sensitivity analyses confirmed the robustness of the findings, although funnel plot asymmetry suggested potential publication bias. We concluded that although a statistical association between prior TBI and meningioma diagnosis was observed, the current evidence does not support a clear causal relationship. The pooled effect appears to be driven mainly by retrospective case-control studies, which are particularly vulnerable to recall and detection bias, whereas cohort studies provide less consistent support for a direct etiological link. Further large-scale prospective studies with long-term follow-up are needed to clarify this relationship.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".