Infliximab Tissue Concentrations in Patients With Stable Ulcerative Colitis Are Correlated With More Durable Infliximab-associated Disease Remission
Bibliographic record
Abstract
BACKGROUND: We aimed to determine the correlation between tissue and plasma infliximab concentrations in an outpatient ulcerative colitis (UC) cohort based on histologic disease activity in addition to their relationship with long-term clinical outcomes. We assessed intraparticipant variability in infliximab concentrations between adjacent intestinal samples and the correlation between disease activity and tumor necrosis factor-α (TNF-α). METHODS: A prospective cohort study was conducted in participants with UC receiving infliximab. Blood and 2 sigmoid colon biopsies were obtained at the index colonoscopy for infliximab and TNF-α quantification. Histological disease activity was assessed. Participants were followed for 2 years for the occurrence of hospitalization, surgery, disease relapse, and infliximab discontinuation. RESULTS: A positive correlation was observed between mean plasma and uninflamed tissue infliximab concentrations only (Rs = 0.75, P = .0071). Lower mean tissue infliximab concentrations correlated with a shorter time to disease relapse vs those with higher mean tissue concentrations (Rs = 0.77, P = .032). This was not seen when using plasma infliximab concentrations. Additionally, no significant intraparticipant variability of infliximab concentrations was observed for all participants independent of disease activity. Neither plasma nor tissue TNF-α correlated with disease activity. CONCLUSIONS: These findings support data generated in patients with Crohn's disease: plasma infliximab concentrations are reflective of infliximab exposure in tissue in the UC patient in remission, but not for those with active disease. Increasing tissue concentrations in the noninflamed tissues may improve durability of infliximab. Neither plasma nor tissue TNF-α appear to correlate with UC disease activity. Larger follow-up studies would be of benefit.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".