Efficacy, drug sustainability, and safety of ustekinumab treatment in Crohn’s disease patients over three years
Bibliographic record
Abstract
Long-term data on ustekinumab in real-life Crohn's disease patients are still missing, though randomized controlled trials demonstrated it as a favorable therapeutic option. We aimed to evaluate ustekinumab's clinical efficacy, drug sustainability, and safety in a prospective, nationwide, multicenter Crohn's disease patient cohort with a three-year follow-up. Crohn's disease patients on ustekinumab treatment were consecutively enrolled from 9 Hungarian Inflammatory Bowel Disease centers between January 2019 and May 2020. Patient and disease characteristics, treatment history, clinical disease activity (Harvey Bradshaw Index (HBI)), biomarkers, and endoscopic activity (Simple Endoscopic Score for Crohn's Disease (SES-CD)) were collected for three-years' time. A total of 148 patients were included with an overall 48.9% of complex behavior of the Crohn's disease and 97.2% of previous anti-TNF exposure. The pre-induction remission rates were 12.2% (HBI), and 5.1% (SES-CD). Clinical remission rates (HBI) were 52.2%, 55.6%, and 50.9%, whereas criteria of an endoscopic remission were fulfilled in 14.3%, 27.5%, and 35.3% of the subjects at the end of the first, second, and third year, respectively. Dose intensification was high with 84.0% of the patients on an 8-weekly and 29.9% on a 4-weekly regimen at the end of year 3. Drug sustainability was 76.9% during the follow-up period with no serious adverse events observed. Ustekinumab in the long-term is an effective, sustainable, and safe therapeutic option for Crohn's disease patients with severe disease phenotype and high previous anti-TNF biological failure, requiring frequent dose intensifications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 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) | 0.001 | 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".