Surgically resected skull base meningiomas demonstrate a divergent postoperative recurrence pattern compared with non–skull base meningiomas
Bibliographic record
Abstract
OBJECTIVE The objective of this study was to identify the natural history and clinical predictors of postoperative recurrence of skull base and non-skull base meningiomas. METHODS The authors performed a retrospective hospital-based study of all patients with meningioma referred to their institution from September 1993 to January 2014. The cohort constituted both patients with a first-time presentation and those with evidence of recurrence. Kaplan-Meier curves were constructed for analysis of recurrence and differences were assessed using the log-rank test. Cox proportional hazard regression was used to identify potential predictors of recurrence. RESULTS Overall, 398 intracranial meningiomas were reviewed, including 269 (68%) non-skull base and 129 (32%) skull base meningiomas (median follow-up 30.2 months, interquartile range [IQR] 8.5-76 months). The 10-year recurrence-free survival rates for patients with gross-total resection (GTR) and subtotal resection (STR) were 90% and 43%, respectively. Skull base tumors were associated with a lower proliferation index (0.041 vs 0.062, p = 0.001), higher likelihood of WHO Grade I (85.3% vs 69.1%, p = 0.003), and younger patient age (55.2 vs 58.3 years, p = 0.01). Meningiomas in all locations demonstrated an average recurrence rate of 30% at 100 months of follow-up. Subsequently, the recurrence of skull base meningiomas plateaued whereas non-skull base lesions had an 80% recurrence rate at 230 months follow-up (p = 0.02). On univariate analysis, a prior history of recurrence (p < 0.001), initial WHO grade following resection (p < 0.001), and the inability to obtain GTR (p < 0.001) were predictors of future recurrence. On multivariate analysis a prior history of recurrence (p = 0.02) and an STR (p < 0.01) were independent predictors of a recurrence. Assessing only patients with primary presentations, STR and WHO Grades II and III were independent predictors of recurrence (p < 0.001 for both). CONCLUSIONS Patients with skull base meningiomas present at a younger age and have less aggressive lesions overall. Extent of resection is a key predictor of recurrence and long-term follow-up of meningiomas is necessary, especially for non-skull base tumors. In skull base meningiomas, recurrence risk plateaus approximately 100 months after surgery, suggesting that for this specific cohort, follow-up after 100 months can be less frequent.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".