Treatment for Glioblastoma Multiforme: Current Guidelines and Canadian Practice
Bibliographic record
Abstract
PURPOSE: Our survey aimed to document variability in the practice patterns of Canadian radiation oncologists treating high-grade brain tumours. MATERIALS AND METHODS: A 20-question survey was developed to address various aspects of treatment: Guidelines usedTypes of fusion protocols usedNumber of treatment phasesMargins for volume delineationDose constraintsThe survey was sent to Canadian radiation oncologists currently treating the central nervous system (cns) as one of their primary sites. RESULTS: We attained a 56% response rate from radiation oncologists across Canada treating cns sites. In their practice, 14% of respondents reported following guidelines from the European Organisation for Research and Treatment of Cancer; 32%, from the Radiation Therapy Oncology Group; and 56%, centre-specific guidelines. Single-phase treatment was reported by 60% of clinicians, and two-phase or multi-phase treatments, by 37%. For clinicians treating in single phase, margins from the gross treatment volume (gtv) to the planning treatment volume (ptv) included 0.5 cm (6%), 1 cm (6%), 1.5 cm (25%), 2.0 cm (56%), 2.5 cm (25%), and 3 cm (12.5%), with some respondents selecting more than one standard margin. For clinicians treating in multiple phases, margins from gtv to ptv in phase 2 included 1 cm (10%), 2.0 cm (40%), 2.5 cm (30%), and 3.0 cm (20%). Variability was also observed in dose constraints to critical structures. All respondents trimmed their margins to bony structures. CONCLUSIONS: Our survey shows considerable variation in the current treatment by Canadian radiation oncologists of high-grade brain tumours, especially with respect to guidelines followed, number of phases, and overall volume treated. Further studies are thus required to establish the evidence for optimal radiation volumes and phases, especially as brain tumour treatments evolve in the age of mr imaging and chemotherapy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| 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 | 0.000 | 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".