Temporal changes in childhood cancer incidence and survival by stage at diagnosis in Australia, 2000–2017
Bibliographic record
Abstract
The Toronto Paediatric Cancer Stage Guidelines are a compendium of staging systems developed to facilitate collection of consistent and comparable data on stage at diagnosis for childhood cancers by cancer registries. This retrospective, observational cohort study investigated changes in stage-specific incidence and survival for children diagnosed between 2000-2008 compared to 2009-2017 using the population-based Australian Childhood Cancer Registry. Information on mortality for each patient was available to 31st December 2020. Shifts in incidence by stage were evaluated using chi-square tests, and differences in stage-specific five-year observed survival for all causes of death over time were assessed using flexible parametric models. Stage was assigned according to the Toronto Guidelines for 96% (n = 7944) of the total study cohort (n = 8292). Changes in the distribution of incidence by stage between the two diagnosis periods were observed for retinoblastoma, with stage 0 increasing from 26% to 37% of cases (p = 0.02), and hepatoblastoma, with metastatic disease increasing from 22% to 39% of cases (p = 0.04). There were large gains in stage-specific survival over time for stage IV rhabdomyosarcoma (five-year adjusted mortality hazard ratio for 2009–2017 compared to 2000–2008 of 0.38, 95% CI 0.19–0.77; p = 0.01), stage M3 for medulloblastoma (HR = 0.41, 95% CI 0.21–0.79; p = 0.01) and metastatic neuroblastoma excluding stage MS (HR = 0.61, 95% CI 0.44-0.84; p < 0.01). These results indicate that improvements in childhood cancer survival in Australia are most likely due to refined management rather than changes in stage at diagnosis, particularly for metastatic solid tumours. Wide international uptake of the Toronto Guidelines will allow comprehensive evaluation of differences in survival between countries.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".