Canstaging+ and staging childhood cancer for population-based cancer registries
Bibliographic record
Abstract
Background In 2018 the WHO launched the Global Initiative for Childhood Cancer to address global inequality in childhood cancer survival. Cancer staging is important for treatment planning and discussion with patients and to facilitate monitoring of cancer outcomes at population level. Population based cancer registries (PBCRs) are key partners in assigning stage at diagnosis yet it is complex and required adherence to international standards and regular updates. Methods We developed a user-friendly electronic staging tool, CanStaging+, for PBCRs based on UICC TNM classifications for adult cancers and on Toronto Paediatric Cancer Stage guidelines for childhood cancers, publicly available both online and as an offline tool, which will be demonstrated during the presentation. Results CanStaging+ with anatomical drawings is designed to help maximise availability, standardisation and comparability of cancer staging internationally. The tool provides automatic calculation of the TNM staging classification for a variety of tumour sites. CanStaging+ also provides the two-tiered approach of Toronto childhood cancer staging for fifteen cancer types including the complete guideline of the Toronto Paediatric Cancer Stage. A batch function exists to allow registries to stage or derive stage groups of each case recorded. Additionally it hosts guideline for the Essential TNM including its diagram. Today the tool is available in English, and an expansion including translation to Spanish, French, Italian, Turkish and Japan is ongoing, with a view to expand this to other languages in the future. Discussion and Conclusion CanStaging+ is a tool for PBCR available on and offline to enhance the completeness and comparability of cancer staging internationally. Specifically, for this conference we will present the new updates on the childhood cancer staging tool. The project has been a true international collaborative effort, and continued collaboration is seek to join different sub-works of CanStaging+ e.g., expansion, implementation or capacity building.
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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 | 0.022 | 0.100 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.064 | 0.019 |
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".