Association between Bacillus Calmette-Guérin (BCG) vaccination and inflammatory bowel disease: A two-stage sampling design within the Quebec Birth Cohort on Immunity and Health (CO·MMUNITY)
Bibliographic record
Abstract
BACKGROUND: Bacillus Calmette-Guérin (BCG) vaccination, primarily administered to prevent tuberculosis, exhibits nonspecific immune effects and could play a role in inflammatory bowel disease prevention. We investigated the associations of BCG with Crohn's disease and ulcerative colitis, and assessed sex-differences. METHODS: This two-stage study included 365,206 Canadians from the Quebec Birth Cohort on Immunity and Health (1970-2014; stage 1). Vaccination status was registry-based and inflammatory bowel disease cases were identified from health services with validated algorithms. We documented additional factors among 2644 participants in a nested case-control study in 2021 (stage 2). A two-stage logistic regression analysis was applied to estimate the odds ratios (OR), corrected for sampling fractions and adjusted for confounding factors. We used interaction terms to assess sex-differences on the multiplicative scale. RESULTS: In the stage 1 sample, 2419 cases of Crohn's disease and 1079 of ulcerative colitis were included. Forty-six percent of non-cases received the BCG vaccine as compared to 47% for Crohn's disease and 49% for ulcerative colitis. Associations differed by sex. BCG vaccination was not associated with Crohn's disease among men (OR = 0.91; 95% CI: 0.79-1.04) but was related to an increased risk among women (OR = 1.13; 95% CI: 1.00-1.28, P interaction: 0.001). For ulcerative colitis, there was a tendency toward a slightly elevated risk among men (OR = 1.09; 95%CI: 0.90-1.32), whereas the risk was more substantial for women (OR = 1.17; 95% CI:0.99-1.39, P interaction: <0.001). CONCLUSION: BCG vaccination does not play a preventive role in inflammatory bowel disease. Our results point to distinct associations between men and women.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".