Association Between Medications and Herpes Zoster in Japanese Patients with Rheumatoid Arthritis: A 5-year Prospective Cohort Study
Bibliographic record
Abstract
OBJECTIVE: To investigate the association between medications and herpes zoster (HZ) in patients with rheumatoid arthritis (RA) given biological disease-modifying antirheumatic drugs (bDMARD) or conventional synthetic DMARD in the clinical setting during 5 years using the Registry of Japanese Rheumatoid Arthritis Patients on Biologics for Longterm Safety (REAL) database. METHODS: We calculated the crude incidence rate (IR) of HZ treated with systemic antiviral medications in 1987 patients from the REAL database. To estimate the association between HZ and medications, a nested case control study was performed with 1:5 case-control pairs matched for age, sex, observation start year, and comorbidity (HZ case group, n = 43; control group, n = 214). We calculated OR and 95% CI of the use of bDMARD, methotrexate (MTX), and corticosteroids for the occurrence of HZ using a conditional logistic regression analysis. RESULTS: The median patient age was 60.0 years, female proportion was 81.5%, and median disease duration was 6.0 years. The crude IR (95% CI) of HZ was 6.66 (4.92-8.83)/1000 person-years. The OR (95% CI) of medication use were 2.28 (1.09-4.76) for tumor necrosis factor inhibitor (TNFi) and 1.13 (1.03-1.23) for oral corticosteroids dosage (per 1 mg prednisolone increment), both of which were significantly elevated. The OR of non-TNFi and MTX usage were not elevated. CONCLUSION: TNFi use and higher corticosteroids dosage were significantly associated with HZ in Japanese patients with RA in the clinical setting.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".