SURVEY OF CANADIAN NEURO-ONCOLOGY CLINICIANS ABOUT THE TREATMENT OF ADULT MEDULLOBLASTOMA
Bibliographic record
Abstract
Abstract Given the rarity of adult medulloblastoma, the optimal chemotherapy strategy is unknown and its management is thought to vary from institution to institution. Guidelines often omit suggestions for specific chemotherapy regimens, reflecting the lack of high-quality evidence in this population. We sought to understand Canadian adult medulloblastoma practice patterns, hoping to inform future quality metrics and guidelines. METHODS: In March 2022, a 30-question survey was sent out to 71 adult neuro-oncology clinicians on the Canadian Adolescent and Young Adult national rounds mailing list. Snowball sampling was permitted. RESULTS: The response rate was 35%. Radiation oncologists (11), neuro-oncologists (8), medical oncologists (4), and neurosurgeons (2) responded from 6/10 Canadian provinces. They each treated on average 1.6 medulloblastoma patients per year. Most (61%) said that molecular subgrouping was always done at their centre. Half indicated that cerebrospinal fluid testing was always done at diagnosis. The most common (64%) radiation regimen was 36 Gy (in 20 fractions) craniospinal irradiation + 18 Gy (in 10 fractions) boost. Concomitant chemotherapy was rarely given while adjuvant chemotherapy was frequently administered. The most common adjuvant chemotherapy was Cisplatin/Lomustine/Vincristine (57%), but other regimens included Cisplatin/ Lomustine/ Vincristine alternating with Cyclophosphamide/ Vincristine (21%), Cisplatin/ Cyclophosphamide/ Vincristine (14%), and carboplatin-based regimens (14%). Respondents noted challenges prescribing chemotherapy in this population: drug toxicities, limited resources, and clinical uncertainty. There was support for standard-of-care adult medulloblastoma guidelines in 92%. CONCLUSIONS: There is significant practice variation among Canadian neuro-oncology centres treating adult medulloblastoma. This variation can serve as an opportunity for quality improvement and clinical research.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".