Implementation of the 2016 WHO CNS Classification for infiltrating glioma: the VGH experience
Bibliographic record
Abstract
The classification system for gliomas has undergone significant revisions in the last several years, with the incorporation of molecular criteria and removal of mixed histologic diagnoses. Large-scale molecular studies have elucidated the biological characteristics of low grade gliomas, and enabled grouping based on IDH mutational and 1p19q codeletion status that outperforms histology in predicting patient outcomes. Mutations in ATRX and TP53 are largely mutually exclusive of 1p19q- codeletion in the context of mutant IDH, and are useful in screening patients for further molecular studies. At our institution, new testing methods for 1p19q codeletion and ATRX were implemented in 2014, and in this presentation we review all cases submitted for 1p19q testing since this time. In comparing histologic to molecular diagnoses, the majority of histologic oligodendrogliomas indeed have 1p19q codeletion, while oligoastrocytomas and GBMOs largely are re-classified as astrocytomas and glioblastomas, respectively. We have also found that loss of ATRX nuclear expression associated with ATRX mutation is highly indicative of 1p19q retention, however the immunohistochemical test can be challenging to interpret and there have been a small number of discordant results.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".