Pathological features determining recurrence and radioresistance in cerebral atypical meningioma
Bibliographic record
Abstract
We examined recurrence after gross total resection (GTR) or subtotal resection (STR) at St. Michael’s Hospital, Toronto, of 181 cases of atypical meningioma (WHO grade II). In the entire group, Kaplan-Meier survival curves showed that combined necrosis and brain invasion was the feature associated with the worst outcome, followed in order by necrosis, histological variants (clear cell, rhabdoid, and chordoid), high mitotic count, and brain invasion. The highly significant difference between necrosis and brain invasion and necrosis was seen only in patients receiving GTR, and lost in those treated with STR. Adjuvant radiotherapy was associated with worse outcome, more so in patients receiving GTR. In the presence of high mitotic count (defined as >4/10HPF) radiation did not affect recurrence, but necrosis and specially combined necrosis and brain invasion magnified the apparent deleterious effect of adjuvant radiotherapy. In the presence of brain invasion, radiotherapy’s small effect did not reach significance. Since patients were not randomized to adjuvant radiotherapy, these results should not be construed as indicating that this treatment is injurious. It can be stated that in the presence of necrosis and particularly necrosis and brain invasion, but not brain invasion alone, or high mitotic count, atypical meningiomas are more resistant to any possible beneficial effect of radiation in delaying recurrence. LEARNING OBJECTIVES This presentation will enable the learner to: 1. Describe histological and treatment factors determining recurrence in atypical meningioma. 2. List histological factors associated with radioresistance in atypical meningioma.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".