Molecular Testing of Central Nervous System Tumours: Recommendations of the Canadian Association of Neuropathologists
Bibliographic record
Abstract
The diagnosis of central nervous system tumours has been transformed in recent years from a microscopic morphology-based process to one dominated by the identification of somatic genetic alterations in tumour cells. This switch requires implementing radically different methods, for which appropriate training and financial resources must be allocated. The Canadian Association of Neuropathologists (CANP) has followed a process based on the scientific literature and consensus to develop recommendations for molecular testing of tumours of the brain and spinal cord, aiming to balance the need for treatment-determinant accurate diagnosis and the current limitations inherent in the transition to a new paradigm. The Professional Affairs Committee was charged with this task. A draft was discussed during the CANP general assembly, along with presentations from groups who had implemented molecular technologies, as well as others who relied on external laboratories. The Professional Affairs Committee summarised the consensus and submitted their recommendation to the CANP's Executive Committee. A final report was posted on the CANP website for a month to allow all members to comment. The recommendations below apply to intrinsic tumours of the central nervous system and do not include metastatic disease or tumours impinging upon the nervous system from outside. These recommendations should be considered clinically relevant, as the results have direct consequences on the patient's treatment, either through the use of targeted therapies or the trial-proven best application of radiation and/or chemotherapy.
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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 | 0.031 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.013 | 0.011 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.007 | 0.003 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.005 | 0.005 |
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".