Stage at diagnosis for childhood solid cancers in Australia: A population-based study
Bibliographic record
Abstract
BACKGROUND: Stage of cancer at diagnosis is one of the strongest predictors of survival and is essential for population cancer surveillance, comparison of cancer outcomes and to guide national cancer control strategies. Our aim was to describe, for the first time, the distribution of cases by stage at diagnosis and differences in stage-specific survival on a population basis for a range of childhood solid cancers in Australia. METHODS: The study cohort was drawn from the population-based Australian Childhood Cancer Registry and comprised children (<15 years) diagnosed with one of 12 solid malignancies between 2006 and 2014. Stage at diagnosis was assigned according to the Toronto Paediatric Cancer Stage Guidelines. Observed (all cause) survival was calculated using the Kaplan-Meier method, with follow-up on mortality available to 31 December 2015. RESULTS: Almost three-quarters (1256 of 1760 cases, 71%) of children in the study had localised or regional disease at diagnosis, varying from 43% for neuroblastoma to 99% for retinoblastoma. Differences in 5-year observed survival by stage were greatest for osteosarcoma (localised 85% (95% CI = 72%-93%) versus metastatic 37% (15%-59%)), neuroblastoma (localised 98% (91%-99%) versus metastatic 60% (52%-67%)), rhabdomyosarcoma (localised 85% (71%-93%) versus metastatic 53% (34%-69%)), and medulloblastoma (localised 69% (61%-75%) versus metastases to spine 42% (27%-57%)). CONCLUSION: The stage-specific information presented here provides a basis for comparison with other international population cancer registries. Understanding variations in survival by stage at diagnosis will help with the targeted formation of initiatives to improve outcomes for children with cancer.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".