Clinical utility of ustekinumab in Crohn’s disease
Bibliographic record
Abstract
Paulo Gustavo Kotze,1,2 Christopher Ma,1 Abdulelah Almutairdi,1,3 Remo Panaccione1 1Inflammatory Bowel Disease Unit, Division of Gastroenterology and Hepatology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada; 2Inflammatory Bowel Disease Outpatient Clinics, Colorectal Surgery Unit, Catholic University of Paraná, Curitiba, Brazil; 3Department of Medicine, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia Abstract: The introduction of anti-tumor necrosis factor (TNF) therapy marked an important milestone in the management of moderate-to-severe Crohn’s disease (CD). However, there remains a pressing demand for alternative therapeutic options for patients with primary nonresponse, secondary loss of response, or intolerable side effects to conventional treatment and TNF antagonists. Ustekinumab (UST) is a fully human IgG1κ monoclonal antibody that inhibits the p40 subunit shared by the proinflammatory cytokines, the interleukin (IL)-12 and -23. This blockade leads to dampening of the inflammatory cascade and differentiation of inflammatory T cells. The clinical development program for UST in CD includes dose finding Phase II (Crohn’s Evaluation of Response to Ustekinumab Anti-Interleukin-12/23 for Induction [CERTIFI]) and the pivotal Phase III (UNITI) trials that demonstrated both the clinical efficacy and safety in anti-TNF-naive and anti-TNF-exposed patients. Real-world evidence has further defined the role of UST in CD management. In this review, we discuss the mechanism of action of UST, describe the results of the randomized controlled trials with this agent, and review the real-world efficacy and safety data from observational cohorts. Finally, we identify areas of future research in the IL-12/23 inflammatory pathway and discuss the positioning of this novel therapeutic option in CD treatment algorithms. Keywords: ustekinumab, Crohn’s disease, interleukin
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".