Hypofractionated stereotactic radiotherapy for intracranial meningioma: a systematic review
Bibliographic record
Abstract
BACKGROUND: The availability of image guidance and intensity modulation has led to the increasing use of hypofractionated stereotactic radiotherapy (hSRT) as an alternative to conventionally fractionated radiotherapy or radiosurgery for intracranial meningiomas (ICMs). As the safety and efficacy of this approach is not well characterized, we conducted a systematic review of the literature to assess the clinical outcomes of hSRT in the setting of ICMs. METHODS: A systematic review of Medline and EMBASE databases was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Included studies were retrospective or prospective series that examined an ICM population of ≥10 patients, delivered >1 fraction of photon hSRT (≥2.5 Gy per fraction), and had a median follow-up of ≥2 years. Descriptive statistics were generated for included studies. RESULTS: Of 1480 initial studies, 14 met eligibility criteria for inclusion, reporting on 630 patients (age range, 18-90) treated for 638 tumors. Primary radiotherapy was delivered in 37% of patients, 36% had radiation following surgery, and surgical details were unavailable for 27%. In 474 tumors assessed for radiologic response, 78% remained stable, 18% decreased in size, and 4% increased in size. Crude local control was 90%-100% as reported in 10 studies. The median late toxicity rate was 10%. The most common significant late toxicities were decreased visual acuity and new cranial neuropathy. CONCLUSIONS: With limited follow-up, the available literature suggests hSRT for ICMs has local control and toxicity profiles comparable to other radiotherapy approaches. Confirmation in larger patient cohorts with a longer duration of follow-up is required.
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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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".