Serum protein profiles differ with adalimumab and ustekinumab treatment in moderately to severely active Crohn’s disease
Bibliographic record
Abstract
BACKGROUND AND AIMS: Adalimumab and ustekinumab are approved for the treatment of moderately to severely active Crohn's disease (CD); however, comparative data assessing the mechanism of action of tumor necrosis factor (TNFα) and interleukin (IL)-12/23p40 blockade in a head-to-head, double-blind CD trial are not available. Here we compared inflammatory serum proteins of biologic-naive patients with moderately to severely active CD treated with adalimumab or ustekinumab who participated in the SEAVUE trial (NCT03464136). METHODS: Serum from CD patients receiving adalimumab (n = 195) or ustekinumab (n = 191), and from a separate cohort of healthy controls (n = 40) was evaluated with a targeted inflammation panel, and a high sensitivity IL-22 assay. Differences in temporally regulated proteins were assessed at Weeks 16 and 52 in the context of study endpoints including clinical and endoscopic response. RESULTS: Expression levels of 79 inflammatory proteins were reliably measured in serum. At Week 0, before receiving study intervention, the overall cohort had similar serum proteomic expression profiles. At Weeks 16 and 52, following treatment with adalimumab or ustekinumab, distinct changes in serum proteins associated with inflammation were observed, including broader suppression of inflammation-related proteins by adalimumab and a reduction of IL-22 observed only with ustekinumab. Reduction of interferon-γ levels by ustekinumab at Week 52 was greater than by adalimumab and associated with a decrease in fatigue. CONCLUSIONS: Although patients receiving either adalimumab or ustekinumab reached similar rates of clinical remission at Week 52, the two therapies resulted in unique serum proteomic expression profiles, reflecting mechanistic differences. Long-term treatment data are necessary to understand how differences in therapeutic mechanisms are associated with maintenance of remission and changes in patient-reported outcomes in the context of inflammatory biomarkers.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".