Certolizumab Trough Levels and Antibodies in Crohn Disease: A Single-Center Experience
Bibliographic record
Abstract
Abstract Background Certolizumab pegol (CZP) has been successfully used for the treatment of Crohn disease (CD); however, real-world data regarding the utility of CZP trough levels (CTLs) are lacking. We aimed to correlate CTL with CD outcomes and to determine frequency of CZP antibodies. Methods Retrospective evaluation of all CD patients on maintenance CZP with CTL obtained between 2016 and 2019. Outcomes included: median CTL, presence of anti-CZP antibodies, biochemical response (BR), clinical response (CR), radiologic response (RR), radiologic healing (RH), and mucosal healing (MH). Results Seventy-seven CD patients were included. Median CTL was 18.9 µg/mL (interquartile range, 7.6–35.4). Twenty-three patients (27.3%) had positive antibody levels, with lower median CTL compared to patients with no antibodies (0.0 vs 29.8; P < 0.0001). Median CTL levels were higher in patients with vs without CR (30.4 vs 10.3 µg/mL; P = 0.0015) and RR (29.6 vs 5.8 µg/mL; P = 0.006). CZP dosing at least every 2 weeks was associated with higher odds of achieving MH (odds ratio, 3.2; 95% confidence interval, 1.03–9.97). CTL resulted in change in clinical management in 62.7% of cases and presence of CMZ antibodies was associated with an odds ratio of 5.83 (95% confidence interval, 1.57–21.73) of change in management. Receiver operating characteristic curve and quartile analysis suggested that CTL >19 µg/mL is associated with increased rates of CR and RR. Conclusions Higher CTL was significantly associated with CR and RR. The rate of CZP antibodies was 27.3%. Our data suggest maintenance CTL of ≥19 µg/mL should be achieved in order to optimize outcomes in clinical practice.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".