Screening for Hepatitis B Virus Prior to Initiating Tocilizumab and Tofacitinib in Patients With Rheumatic Diseases: A Cross-sectional Study
Bibliographic record
Abstract
OBJECTIVE: Hepatitis B virus (HBV) can reactivate among rheumatology patients initiating tocilizumab (TCZ) or tofacitinib (TOF). HBV screening is recommended by the Centers for Disease Control and Prevention (CDC), the American Association for the Study of Liver Diseases (AASLD), and the Canadian Rheumatology Association, but it is not explicitly recommended by the American College of Rheumatology. METHODS: We conducted a cross-sectional study to characterize HBV screening practices for adult rheumatology patients initiating TCZ or TOF before December 31, 2018, in the Greater Boston area. We classified appropriate HBV screening patterns prior to TCZ or TOF (i.e., HBV surface antigen [HBsAg], total core antibody [anti-HBcAb], and surface antibody [HBsAb]) as follows: complete (all 3 tested), partial (any 1 or 2 tests), or none. We determined the frequency of inappropriate HBV testing (HBV e-antigen, anti-HBcAb IgM, or HBV DNA without a positive HBsAg or total anti-HBcAb) and used multivariable regression to assess factors associated with complete HBV screening. RESULTS: Among 678 subjects initiating TCZ, 194 (29%) completed appropriate HBV screening, 307 (45%) had partial screening, and 177 (26%) had none. Among 391 subjects initiating TOF, 94 (24%) completed appropriate HBV screening, 195 (50%) had partial screening, and 102 (26%) had none. Inappropriate testing was performed in 22% of subjects. Race was associated with complete HBV screening (White vs non-White: OR 0.74, 95% CI 0.57-0.95), whereas prior immunosuppression was not (conventional synthetic disease-modifying antirheumatic drugs [DMARDs]: OR 1.05, 95% CI 0.72-1.55; biologic DMARDs: OR 0.73, 95% CI 0.48-1.12). CONCLUSION: Patients initiating TCZ or TOF are infrequently screened for HBV despite recommendations from the AASLD and CDC.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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".