Association of Early Postinduction Adalimumab Exposure With Subsequent Clinical and Biomarker Remission in Children with Crohn’s Disease
Bibliographic record
Abstract
BACKGROUND: Data on the association between early postinduction serum adalimumab (ADA) trough levels (TLs) and objective outcomes are scarce. The aim of this study was to investigate whether early ADA TLs at weeks 4 and 8 are associated with clinical and biomarker remission at week 24 in pediatric Crohn's disease (CD). METHODS: Adalimumab TLs at weeks 4 and 8 were prospectively measured in anti-TNF-naïve children initiating treatment with ADA monotherapy for luminal inflammatory CD. The primary outcome was combined clinical and biomarker remission at week 24, defined as achieving steroid-free clinical remission (Pediatric CD activity index <10) and biomarker remission (fecal calprotectin <250 µg/g and CRP <5 µg/mL). RESULTS: Among 65 patients, 39 (60%) achieved combined clinical/biomarker remission at week 24 without dose escalation. Adalimumab TLs at both weeks 4 and 8 were significantly higher in remitters vs nonremitters at week 24 (P < 0.001 and P = 0.002, respectively). Adalimumab levels at weeks 4 and 8 were good predictors of combined clinical/biomarker remission at week 24 (area under the curve, 0.887, 95% CI, 0.798-0.942; and area under the curve, 0.761, 95% CI, 0.632-0.899, respectively). The best ADA TL cutoffs at weeks 4 and 8 for predicting clinical/biomarker remission at week 24 were 22.5 µg/mL (80% sensitivity, 90% specificity, positive likelihood ratio [LR+] 8.0, negative LR [LR-] 0.2) and 12.5 µg/mL (94% sensitivity, 60% specificity, LR+ 2.4, LR- 0.1), respectively. Higher induction doses per m2 correlated positively with TLs at weeks 4 and 8. CONCLUSION: Greater early ADA exposure is associated with superior clinical/biomarker outcomes at week 24.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| 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".