213: Serial Magnetic Resonance Spectroscopy Imaging Predicts Clinical Outcomes in High-Grade Glioma During and After Post-Operative Radiotherapy
Bibliographic record
Abstract
Results: The study population consisted of 206 patients treated with surgery and 136 patients treated with RT.Median follow up was 6.6 years.Patients in the surgical cohort were younger, with mean age: 48.9 versus 60.7 years, p < 0.001, and had larger tumours, with mean maximum dimension: 25.7 +/-10.3mm versus 20.3 +/-6.6 mm, p < 0.001.After all VS treatments, the population's PFS was 92.8 +/-1.5% at five years and 83.7% +/-2.9% at 10 years.The population's SH preservation at last follow up was 34.2%.SAEs occurred in 4.7% of patients.In the radiotherapy cohort of 136 patients, 17% had previous surgery (four complete resection, five planned subtotal resection and 14 unplanned partial resection).Sixty-seven percent had singlefraction stereotactic radiosurgery and 33% had fractionated stereotactic radiotherapy.Seven percent had progressive disease requiring salvage surgery.Eighteen percent had FND (HB Grade 2 or more) at presentation.No patients had improvement in FND after RT and 17% had new or worsened FND after treatment.SAEs were: hydrocephalus requiring ventriculoperitoneal shunt 1.5%, radionecrosis 0.7%, hospitalization for steroid myopathy 0.7%, and death from complications of disease 0.7%.In the surgical cohort of 206 patients, 8% had previous treatment (eight radiation, nine surgery).The most common surgical approaches were retrosigmoid (89%) and translabyrinthine (6%).Two percent had planned post-op RT and 12% had disease progression requiring salvage: 19 RT, three surgery, two unknown.Twelve percent had FND at presentation.FND improved in 4.4% and worsened in 12.6% after surgery.SAEs were: increased intracranial pressure requiring external ventricular drain 2.9%, dural fistula requiring lumbar drain 1.5%, evacuation of hematoma 1.0%, and perioperative death 0.5%.Conclusions: Multidisciplinary management of VS provides excellent disease control at a population level with hearing preservation in a minority of patients and a low-risk of serious adverse events.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".