Bacillus Calmette–Guerin vaccination and multiple sclerosis: A population‐based birth cohort study in Quebec, Canada
Bibliographic record
Abstract
Abstract Background and purpose The bacillus Calmette–Guerin (BCG) vaccine could reduce the incidence of multiple sclerosis (MS) through immunomodulation. Previous studies, presenting some limitations, reported no association. We re‐examined this association in a large cohort focusing on relapsing–remitting MS (RRMS). Methods The cohort included 400,563 individuals, and was linked with the Quebec provincial BCG vaccination registry and administrative health data. Individuals were followed up from 1983 to 2014 and then within Period 1 (1983–1996) and Period 2 (1997–2014), for the occurrence of MS. Incident MS cases were defined as those with ≥3 hospital or physician claims for MS. Subjects with ≥1 drug reimbursement for MS disease‐modifying therapies were classified as RRMS. Cox proportional hazards regression was used to estimate hazard ratios (HRs) over the follow‐ups, adjusting for potential confounders. Possible effect modification due to sex was assessed. Results A total of 178,335 (46%) individuals were BCG vaccinated. There were 274 (0.06%) incident MS cases identified in 1983–1996, and 1433 (0.4%) in 1997–2014. No association was found with RRMS, either in Period 1 (adjusted HR [HR adj ] = 0.96, 95% confidence interval [CI] = 0.63–1.45; 96 cases) or in Period 2 (HR adj = 1.02, 95% CI = 0.85–1.23; 480 cases). The remaining MS cases, for whom the phenotype was unknown, were positively associated with BCG over the entire follow‐up (HR adj = 1.25, 95% CI = 1.10–1.41; 1131 cases) and in Period 2 (HR adj = 1.33, 95% CI = 1.17–1.52; 953 cases). No interaction with sex was found. Conclusions Findings suggest that BCG vaccination does not decrease the risk of RRMS, and that future studies should consider phenotypes of MS.
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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 | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".