Canadian Consensus for Biomarker Testing and Treatment of TRK Fusion Cancer in Pediatric Patients
Bibliographic record
Abstract
Neurotrophic tyrosine receptor kinase gene fusions (NTRK) are oncogenic drivers present at a low frequency in most tumour types (<5%), and at a higher frequency (>80%) in a small number of rare tumours (e.g., infantile fibrosarcoma [IFS]) and considered mutually exclusive with other common oncogenic drivers. Health Canada recently approved two tyrosine receptor kinase (TRK) inhibitors, larotrectinib (for adults and children) and entrectinib (for adults), for the treatment of solid tumours harbouring NTRK gene fusions. In Phase I/II trials, these TRK inhibitors have demonstrated promising overall response rates and tolerability in patients with TRK fusion cancer who have exhausted other treatment options. In these studies, children appear to have similar responses and tolerability to adults. In this report, we provide a Canadian consensus on when and how to test for NTRK gene fusions and when to consider treatment with a TRK inhibitor for pediatric patients with solid tumours. We focus on three pediatric tumour types: non-rhabdomyosarcoma soft tissue sarcoma/unspecified spindle cell tumours including IFS, differentiated thyroid carcinoma, and glioma. We also propose a tumour-agnostic consensus based on the probability of the tumour harbouring an NTRK gene fusion. For children with locally advanced or metastatic TRK fusion cancer who have either failed upfront therapy or lack satisfactory treatment options, TRK inhibitor therapy should be considered.
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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 | 0.010 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".