A Population‐Based Matched Cohort Study of Extra‐Digestive Cancer Incidence and Mortality in Individuals With and Without Inflammatory Bowel Disease
Bibliographic record
Abstract
BACKGROUND: Trends in extra-digestive (ED) cancer incidence and mortality in inflammatory bowel diseases (IBD) may be changing with newer approaches to management. AIMS: To study temporal trends and contemporary risks of ED cancers in individuals with and without IBD. METHODS: Using population-level administrative data from Ontario, Canada, we studied ED cancer rates among individuals with IBD and age-sex-matched controls (1:10) without IBD between 1994 and 2020. We modelled age-sex-standardised annual cancer incidence (per 100,000 person-years) over time by first-order linear autoregression, and standardised cancer incidence and mortality rate ratios (SIR, SMR) by quasi-Poisson regression. RESULTS: The average annual percentage change (AAPC) in ED cancer incidence was stable among 110,919 people with IBD (0.108%/year; 95% CI, -0.380, 0.599) but declined among 1,109,190 matched controls (-1.39%/year; 95% CI, -1.57, -1.21). Among those with IBD, AAPC was significant for non-Hodgkin's lymphoma (1.48%/year; 95% CI, 0.161, 2.82), melanoma (1.77%/year; 95% CI, 0.781, 2.77), cervical (2.31%/year; 95% CI, 0.602, 4.10), uterine (4.41%/year; 95% CI, 0.045, 8.96) and thyroid (8.10%/year; 95% CI, 4.31, 12.0) cancers, and statistically greater than controls for cervical, ovarian, lung, and bladder cancers. During 2010-2020, ED cancer incidence was higher in those with IBD (SIR 1.20; 95% CI 1.15, 1.26), while ED cancer-related mortality was specifically higher in those with Crohn's disease (CD; SMR 1.31; 95% CI 1.14, 1.51), as compared to matched controls. CONCLUSIONS: ED cancer incidence has not changed among those with IBD but has declined among matched controls. Beyond 2010, ED cancer incidence is higher among those with IBD and cancer-related mortality is higher among those with CD, relative to matched controls.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".