Ustekinumab Safety in Pregnancy: A Comprehensive Review
Bibliographic record
Abstract
Chronic inflammatory conditions, including inflammatory bowel diseases (IBD), psoriasis, and psoriatic arthritis, are prevalent among women of reproductive age; patients with active disease during pregnancy may be at an increased risk of adverse birth outcomes. For this reason, physicians are focused on approaches to controlling disease activity prior to and during pregnancy. The safety profile of many therapies used for these conditions has been relatively well established, though evidence on newer therapies is lacking. Ustekinumab is a relatively new interleukin-12/23 inhibitor approved for IBD, psoriasis, and psoriatic arthritis, whose safety in pregnancy is not yet fully understood. In this comprehensive review, we critically assess the available evidence on ustekinumab in pregnancy across animal studies and human case reports, case series, observational studies, and clinical practice guidelines. We show that, to date, studies have not identified an excess risk of adverse pregnancy outcomes among women exposed to ustekinumab in pregnancy, with few exposed pregnancies and potential for some bias. Clinical guidelines are conflicted regarding whether they recommend continuing or discontinuing ustekinumab, highlighting the paucity of data and need for more research on this issue.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".