Hypofractionated Stereotactic Radiotherapy for Low Grade Glioma at McGill University: Long-term Follow-up
Bibliographic record
Abstract
Small, well-defined, unresectable low-grade gliomas are attractive targets for stereotactic irradiation. Fractionated stereotactic irradiation of these targets has the theoretical benefit of increased normal tissue sparing beyond that provided by the physical characteristics of stereotactic radiosurgery. From July 1987 to November 1992, 21 patients were treated for low-grade glioma at our institution using a hypofractionated regimen of stereotactic radiotherapy. All patients had well-circumscribed, < 40 mm tumors. No patient had had prior radiotherapy. All lesions were histologically proven WHO grade I or II glial tumors. Lesions involved sensitive brain structures and were deemed unresectable. A typical dose of 42 Gy was delivered in 6 fractions over a two-week period using rigid immobilization and a linac-based dynamic stereotactic radiosurgical technique. Patients had a median age of 23 years (9-74) and were predominantly female (60%). Median tumor diameter was 20 mm. With a median follow-up for living patients of 13.3 years, the actuarial 5, 10, and 15-year overall survival rates are 76%, 71%, and 63%, respectively. Treatment was acutely well tolerated although three patients experienced late post-therapy complications. Our results and those of 241 patients treated in nine other institutional series are reviewed. Despite some examples of favorable short-term outcomes, all reported series are highly selected and thus likely biased. The data regarding the use of SRS is limited and, in our opinion, insufficient to claim a clear therapeutic advantage to SRS in the initial management of low-grade glioma. Our own results with hypofractionated stereotactic radiotherapy are similar to those expected with standard therapy.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".