Therapeutic Drug Monitoring for Dose Optimization of Infliximab in Patients With Inflammatory Bowel Disease: An Analysis of Canadian Real‐World Data
Bibliographic record
Abstract
Background: Although it is generally believed that infliximab dose optimization in patients with inflammatory bowel disease with low serum infliximab concentration at trough results in increased treatment persistence, empirical data to support this notion are lacking. This study evaluated the association of infliximab therapeutic drug monitoring (TDM) and TDM‐associated dose optimization with persistence in real‐world practice. Methods: Data from adults with Crohn’s disease (CD) or ulcerative colitis (UC) who participated in a national patient support program (PSP) in Canada were analyzed. Participants who had a first TDM evaluation (with a recorded infliximab trough concentration) in the maintenance phase of treatment were assessed (excluding those who underwent prior dose optimization). Persistence was evaluated using time‐dependent Cox proportional hazards models. Results: In the overall population of patients with CD or UC, TDM was not associated with longer persistence ( n = 13,203). In patients with no prior dose optimization ( n = 2729) who had a serum infliximab concentration of < 3 μg/mL, dose optimization within 9 weeks of TDM was associated with significantly longer persistence (HR: 0.36; 95% CI: 0.26, 0.50 for CD [ n = 711] and HR: 0.30, 95% CI: 0.21, 0.43 for UC [ n = 501]). Sensitivity analyses yielded similar results when using a threshold concentration of < 5 μg/mL. In an analysis excluding patients who received no further treatment after TDM, the association between dose optimization and longer persistence was not confirmed in patients with CD, and mostly confirmed in patients with UC at a threshold concentration of < 3 μg/mL. Conclusion: TDM‐associated dose optimization in patients with UC with low serum infliximab concentrations was associated with longer persistence. This association was not confirmed in patients with CD. This study demonstrated that real‐world data from a PSP‐generated cohort can be evaluated to inform clinical practice and that this approach may be complementary to other types of cohort 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 | 0.014 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".