Subcutaneous ustekinumab for the treatment of anti-TNF resistant Crohn's disease—The McGill experience
Bibliographic record
Abstract
BACKGROUND: Ustekinumab is a fully human IgG1κ monoclonal antibody that blocks the biologic activity of interleukin-12/23. Ustekinumab is approved for treatment of plaque psoriasis and has been shown to be effective for induction and maintenance of clinical response in anti-TNF resistant Crohn's disease (CD). The aim of the study was to describe the real-life experience with open-label use of ustekinumab in anti-TNF resistant CD patients. METHODS: A retrospective observational open-label study. Clinical response was defined by physician's global assessment combined with decision to continue therapy. The clinical response was evaluated at 3, 6, 12months and last follow-up. RESULTS: Thirty-eight patients were included in the study. Initial clinical response was achieved in 28/38 (73.7%) of the patients. Among the initial responders, 80% with follow-up data maintained their response for 6months. At 12months of follow-up, 88.9% of patients responding at 6months maintained their response. At the last follow-up (7.9±5.2 mo) 27/38 (71%) of the patients were responding, and 73.3% were able to discontinue corticosteroids. Dose escalation was required in 47.7% of the patients and was successful in 61.1% of them. SUMMARY: In this real-life cohort of severe anti-TNF resistant CD, an initial clinical response to subcutaneous ustekinumab was observed in 73.7% of the patients. The initial response was successfully maintained in the majority of patients for up to 12months. Subcutaneous ustekinumab is an effective therapeutic option in this challenging patient cohort. The optimal dosing and injection schedule remain to be established in future studies.
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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 | 0.001 |
| 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".