Incidence of Pregnancy-Associated Cancer in Two Canadian Provinces: A Population-Based Study
Bibliographic record
Abstract
Pregnancy-associated cancer—that is diagnosed in pregnancy or within 365 days after delivery—is increasingly common as cancer therapy evolves and survivorship increases. This study assessed the incidence and temporal trends of pregnancy-associated cancer in Alberta and Ontario—together accounting for 50% of Canada’s entire population. Linked data from the two provincial cancer registries and health administrative data were used to ascertain new diagnoses of cancer, livebirths, stillbirths and induced abortions among women aged 18–50 years, from 2003 to 2015. The annual crude incidence rate (IR) was calculated as the number of women with a pregnancy-associated cancer per 100,000 deliveries. A nonparametric test for trend assessed for any temporal trends. In Alberta, the crude IR of pregnancy-associated cancer was 156.2 per 100,000 deliveries (95% CI 145.8–166.7), and in Ontario, the IR was 149.4 per 100,000 deliveries (95% CI 143.3–155.4). While no statistically significant temporal trend in the IR of pregnancy-associated cancer was seen in Alberta, there was a rise in Ontario (p = 0.01). Pregnancy-associated cancer is common enough to warrant more detailed research on maternal, pregnancy and child outcomes, especially as cancer therapies continue to evolve.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".