Outcomes of Patients With Prior Biologic Intolerance Are Better Than Those With Biologic Failure in Clinical Trials of Inflammatory Bowel Disease
Bibliographic record
Abstract
BACKGROUND AND AIMS: Inflammatory bowel disease (IBD) trials often stratify patients by prior biologic exposure, including prior biologic failure or intolerance. This study aimed to assess clinical outcomes in IBD patients with prior biologic failure vs intolerance treated with ustekinumab or vedolizumab. METHODS: A post-hoc analysis of ulcerative colitis (UC) and Crohn's disease (CD) clinical trials for ustekinumab (UNITI and UNIFI) and vedolizumab (GEMINI-1 and GEMINI-2) was performed. Clinical response, clinical remission, and endoscopic improvement (for UC) were compared among biologic naïve, biologic failure, and biologic intolerant patients. Statistical analyses, including chi-square tests and logistic regression, were performed. RESULTS: A total of 1178 UC and 1439 CD patients received either ustekinumab or vedolizumab. In UC, biologic intolerant patients exhibited higher clinical response (54.7% vs 38.8%, aOR 1.87 [95% CI, 0.93-3.73]), clinical remission (25.0% vs 11.0%, aOR 2.84 [95% CI, 1.47-5.49]), and endoscopic improvement (40.6% vs 24.8%, aOR 2.76 [95% CI, 1.28-5.94]) compared to biologic failure, with outcomes similar to biologic naïve patients. In biologic intolerant CD patients, clinical response was similar between prior biologic failure and intolerance (34.2% vs 32.8%), but after adjustment for potential confounders, biologic intolerance was associated with higher odds of clinical response (aOR: 1.67, 95% CI, 1.09-2.55), with no significant difference observed for clinical remission (aOR: 1.48, 95% CI, 0.88-2.49). CONCLUSIONS: Improved treatment outcomes were generally observed in patients with biologic intolerance compared to failure, especially in UC, where outcomes were similar to biologic naïve patients. Future clinical trials should meticulously differentiate prior biologic failure vs intolerance to mitigate potential bias.
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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 | 0.019 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".