The safety of ustekinumab treatment in patients with moderate-to-severe psoriasis and latent tuberculosis infection
Bibliographic record
Abstract
BACKGROUND: Ustekinumab is a monoclonal antibody that targets interleukin (IL)-12/23 p40 to treat psoriasis. The IL-12 pathway is also important in regulating immunity to Mycobacterium tuberculosis. OBJECTIVES: To evaluate the safety of isoniazid (INH) prophylaxis for newly identified latent tuberculosis infection (LTBI) in ustekinumab-treated patients with psoriasis. METHODS: Safety data from 3177 psoriasis patients evaluated across five phase III trials of ustekinumab (45 or 90 mg) conducted in North America, Europe and Asia were analysed. LTBI was diagnosed based on positive tuberculin skin test or QuantiFERON(®) -TB test (Cellestis, Carnegie, Vic., Australia) without evidence of active tuberculosis. RESULTS: At baseline, 101/2898 (3·5%) non-Asian and 66/279 (23·7%) Asian patients were newly identified with LTBI, and all were treated with INH. Through week 12, among patients who received INH, rates of adverse events (AEs) representative of INH toxicity were generally comparable between control and ustekinumab-treated patients, as well as between ustekinumab dose groups. Markedly abnormal alanine transaminase values occurred with comparable incidences between control and ustekinumab-treated patients. The rate of study agent discontinuation due to INH toxicity was low (5/167, 3·0%) and comparable between control and ustekinumab groups through week 12. The rate of INH-related AEs did not increase disproportionately through week 28. No cases of active tuberculosis were reported in patients who received concomitant INH starting at baseline. CONCLUSIONS: Across five trials of ustekinumab-treated patients with psoriasis, no cases of LTBI reactivation were observed in patients receiving concomitant INH prophylaxis for LTBI. INH prophylaxis was generally well tolerated by these patients with psoriasis.
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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 | 0.000 | 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 | 0.000 |
| 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".