Vaccination and rheumatoid arthritis: an updated systematic review and meta-analysis of data from 25,949,597 participants
Bibliographic record
Abstract
OBJECTIVES: This systematic review and meta-analysis aimed to investigate the association between vaccinations and the risk of rheumatoid arthritis (RA), specifically addressing concerns about a potential increased risk among vaccinated individuals. METHODS: A systematic search for cohort studies and case-control studies examining the association between vaccinations and RA was conducted using Medical Subject Headings and relevant keywords across PubMed, EMBASE, and Cochrane Library databases from inception to September 2024. The risk of bias of included studies was assessed using the Newcastle-Ottawa Scale. The Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system was employed to evaluate the overall certainty of evidence. Statistical analyses, i.e., pooling of relative risk (RR) and corresponding 95% confidence intervals (CI), were performed using a random-effects model on STATA software (version 14.0). Due to the I² value exceeding 50%, we did not perform an asymmetry test to assess publication bias. RESULTS: This meta-analysis included 16 observational studies conducted between 2008 and 2024 and involving a total of 25,949,597 participants. The follow-up duration ranged from 0.03 to 9 years, while the data collection period varied from 2.75 to 9.5 years. The analysis found no significant association between vaccination exposure and RA [RR = 1.03, 95% CI (0.95-1.11), I²=93.4%, P = 0.456, low level of evidence]. Sensitivity analyses confirmed the robustness of this result. Subgroup analyses revealed no significant risk of RA associated with HPV vaccination [RR = 1.27 95% CI (0.78-2.08), I²=81.4%, P = 0.339], influenza vaccination [RR = 1.10, 95% CI (0.98-1.23), I²=52.4%, P = 0.112], Anthrax vaccination [RR = 2.21, 95% CI (0.75-6.52)], Herpes Zoster vaccination [RR = 2.70, 95% CI (1.70-4.29)], or COVID-19 vaccination [RR = 0.94, 95% CI (0.82-1.07), I²=97.4%, P = 0.340]. However, the subgroup with a follow-up duration varying between 0.5 and 1.8 years showed that (HPV & COVID-19) vaccination had a significant protective effect on RA [RR = 0.92, 95% CI (0.87-0.98), I²=95.3%, P = 0.005]. CONCLUSION: The evidence for the association between vaccination and RA risk is insufficient, and vaccination may serve as a protective factor for RA over a less than one year follow-up duration.
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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 | 0.019 | 0.045 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.036 |
| Bibliometrics | 0.014 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".