Risk of autoimmune diseases and human papilloma virus (HPV) vaccines: Six years of case-referent surveillance
Bibliographic record
Abstract
BACKGROUND: Safety of HPV vaccines is still in question due to reports of autoimmune diseases (ADs) following HPV immunization. OBJECTIVES: To assess the risk of ADs associated with HPV vaccination of female adolescents/young adults in France. METHODS: Systematic prospective case-referent study conducted to assess the risks associated with real-life use of HPV vaccines. Cases were female 11-25 years old with incident ADs [central demyelination/multiple sclerosis (CD/MS), connective tissue disease (CTD), Guillain-Barré syndrome (GBS), type-1 diabetes (T1D), autoimmune thyroiditis (AT), and idiopathic thrombocytopenic purpura (ITP)]. Cases were consecutively and prospectively identified at specialized centers across France (2008-2014) and individually matched by age and place of residence to referents recruited in general practice. Risk was computed using multivariate conditional logistic regression models adjusted for family history of ADs, living in France (north/south), co-medications and co-vaccinations. RESULTS: With a total of 478 definite cases matched to 1869 referents, all ADs combined were negatively associated to HPV vaccination with an adjusted odds ratio of 0.58 (95% confidence interval: 0.41-0.83). Similar results were obtained for CD/MS, AT, CT, and T1D, the last two not reaching statistical significance. No association was found for ITP and GBS. Sensitivity analyses combining definite and possible cases with secondary time window showed similar results. CONCLUSION: Exposure to HPV vaccines was not associated with an increased risk of ADs within the time period studied. Results were robust to case definitions and time windows of exposure. Continued active surveillance is needed to confirm this finding for individual ADs.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".