Trends in paediatric cancer survival in Canada, 1992 to 2017
Bibliographic record
Abstract
BACKGROUND: While impressive gains in childhood cancer survival have been reported both in Canada and internationally, it has been almost 15 years since the last comprehensive evaluation of Canadian data. DATA AND METHODS: Data are from the population-based Canadian Cancer Registry, record-linked to the Canadian Vital Statistics Death database. Children aged 0 to 14 diagnosed with new primary malignant cancers from 1992 to 2017 in Canada except Quebec were included. Overall survival was measured using observed survival proportions (OSPs). Estimates for the 2013-to-2017 period were predicted using the period method; otherwise, the cohort method was used. RESULTS: For the 2013-to-2017 period, five-year OSPs were at least 90% for 10 of 24 individual cancer groups or subgroups reported. Survival was highest for thyroid carcinomas (100%) and Hodgkin lymphomas (99%) and lowest for other gliomas (42%). A significant increase in the five-year OSP from the 1992-to-1996 period (77%) to the 2013-to-2017 period (84%) was observed for all childhood cancers combined, but not since the 2003-to-2007 period. The greatest increase was for chronic myeloproliferative diseases (35.4 percentage points); for lymphoid leukemias, survival increased from 85% to 93%. Survival was relatively poor at baseline for hepatic tumours, malignant bone tumours, and soft tissue and other extraosseous sarcomas, and it remained virtually unchanged. Once children survived five years, the probability of surviving another five years exceeded 95% across most diagnoses. DISCUSSION: Significant improvements in both short- and long-term paediatric cancer survival have been made in Canada since the early to mid-1990s. These findings are clinically meaningful and are likely to be reassuring to families.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".