An application of the Toronto Childhood Cancer Stage Guidelines in three population‐based cancer registries: The case of central nervous tumors
Bibliographic record
Abstract
BACKGROUND: Cancer stage is a determinant of survival of childhood central nervous system (CNS) cancers and could help the interpretation of survival variability among countries. Consensus guidelines to stage childhood malignancies in population cancer registries ("Toronto Childhood Cancer Stage Guidelines") have been recently proposed with the goal of data comparability. Indeed, stage is not systematically recorded in all registries and, when it is, different classification systems are used. We applied the Toronto Childhood Cancer Stage Guidelines to CNS cancer cases of three population-based cancer registries with the aim of evaluating the feasibility of staging this type of cancer and the critical points in the classification of CNS tumors. PROCEDURES: The Toronto Childhood Cancer Stage Guidelines were applied to 175 CNS patients, diagnosed from January 1, 2002 to December 31, 2014 in three cancer registries in Italy, and the percentage of cases that could be staged was assessed. RESULTS: One hundred eight of 126 (86%) medulloblastomas and other embryonal CNS cancers and 22 of 49 (45%) ependymomas were staged. Using these guidelines, survival of children with localized tumors could be discriminated from that of children with metastatic disease. CONCLUSIONS: The use of the Toronto Childhood Cancer Stage Guidelines is feasible for staging medulloblastoma in Italian population-based cancer registries, whereas it is more difficult for ependymomas. In Italy, cerebrospinal fluid examination, one of the decisive tests to stage CNS tumors, is not routinely performed as a first-line diagnosis procedure in ependymoma pediatric patients. A similar exercise by a larger number of cancer registries in different countries could suggest improvements in the childhood cancer staging system.
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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 | 0.084 | 0.163 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".