Incidence trends and projections for childhood cancer in Ontario
Bibliographic record
Abstract
Studies of cancer incidence patterns and trends can provide useful measures of health burden and possible disease etiology, which can aid the planning of cancer care services. This report aims to characterize trends in incidence of childhood cancer, and to assess the implications of these trends by generating incidence projections to 2015. Cancer incidence data were obtained from the database of the Pediatric Oncology Group of Ontario (POGO), which has registered all cancer cases in Ontario since 1985. Annual incidence rates were calculated with census-based population estimates for the 1986-2001 period. Poisson regression models were used to analyze trends, and to calculate projected numbers of cases up to the year 2015. From 1986 to 2001, 5,163 cancer cases occurred among children aged 0-14. Leukemia, CNS tumors and lymphomas were the most common cancers. The number of incident cases increased by 14%, from 296 in 1986 to 336 in 2001. For all cancers, average annual age-standardized rates increased from 147 per million in 1991 to 157 per million in 2001. Over the next 15 years, the 0-14 year population is expected to decrease from 2.28 million in 2000 to 2.13 million in 2015. A marginally statistically significant trend in incidence was projected for all cancers combined (0.5% increase per year p < 0.10) and a statistically significant increase for lymphomas, (1.2% per year 95% CI = 0.0-3.9%). During this period, the number of cases of leukemia and CNS tumors is expected to remain relatively stable. The number of cases of all cancers is expected to increase by 8%, from the average of 320 in 1995 to approximately 347 in 2015. Understanding of these projections will facilitate health care resource planning.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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 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".