Long-term safety of ustekinumab in patients with moderate-to-severe psoriasis: final results from 5 years of follow-up
Bibliographic record
Abstract
BACKGROUND: Long-term safety evaluations of biologics are needed to inform patient management decisions. OBJECTIVES: To evaluate the safety of ustekinumab in patients with moderate-to-severe psoriasis treated for up to 5 years. METHODS: Safety data were pooled from four studies of ustekinumab for psoriasis. Rates of adverse events (AEs), serious AEs (SAEs) and AEs of interest [infections, nonmelanoma skin cancers (NMSCs), other malignancies and major adverse cardiovascular events (MACE)] per 100 patient-years (PY) of follow-up were analysed by ustekinumab dose (45 or 90 mg) and by year of follow-up (years 1-5) to evaluate the dose response and impact of cumulative exposure. Observed rates of overall mortality and other malignancies were compared with those expected in the general U.S. population. RESULTS: Analyses included 3117 patients (8998 PY) who received one or more doses of ustekinumab, with 1482 patients treated for ≥4 years (including 838 patients ≥5 years). At year 5, event rates (45 mg, 90 mg, respectively) for overall AEs (242·6, 225·3), SAEs (7·0, 7·2), serious infections (0·98, 1·19), NMSCs (0·64, 0·44), other malignancies (0·59, 0·61) and MACE (0·56, 0·36) were comparable between dose groups. Year-to-year variability was observed, but no increasing trend was evident. Rates of overall mortality and other malignancies were comparable with those expected in the general U.S. population. CONCLUSIONS: No dose-related or cumulative toxicity was observed with increasing duration of ustekinumab exposure for up to 5 years. Rates of AEs reported in ustekinumab psoriasis trials are generally comparable with those reported for other biologics approved for the treatment of moderate-to-severe psoriasis.
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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 | 0.016 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".