Effect of adalimumab on clinical laboratory parameters in patients with Crohnʼs disease: Results from the CHARM trial
Bibliographic record
Abstract
BACKGROUND: Nutritional deficiencies and anemia are common in Crohn's disease (CD). METHODS: We evaluated the effect of adalimumab on changes in laboratory values using data from CHARM, in which patients were randomized to adalimumab 40 mg every other week (eow), adalimumab 40 mg weekly, or placebo for 56 weeks. Mean changes in laboratory values from baseline to Weeks 26 and 56 were compared between adalimumab and placebo using analysis of covariance models. Percentages of patients with suboptimal laboratory values at Weeks 26 and 56 were compared between treatment groups using Cochran-Mantel-Haenszel (CMH) tests. Pearson correlation coefficients for associations between changes in Crohn's Disease Activity Index (CDAI) score and changes in laboratory values were estimated at Weeks 4, 26, and 56. RESULTS: The intention-to-treat analysis included 778 patients randomized to adalimumab eow (N = 260), adalimumab weekly (N = 257), or placebo (N = 261). Baseline abnormalities in laboratory values were common across treatment groups. CMH tests revealed significantly lesser rates of suboptimal laboratory values with adalimumab vs. placebo at Week 26, including hypoalbuminemia, calcium deficiency, low hemoglobin, low hematocrit, low red blood cell count, elevated platelet count, and elevated C-reactive protein concentration (all P < 0.05). These improvements persisted at Week 56. Improvements in CDAI from baseline to Weeks 4, 26, and 56 were significantly correlated with changes from baseline for albumin, hemoglobin, and C-reactive protein (all P < 0.001). CONCLUSIONS: Adalimumab therapy for moderately to severely active CD was associated with significant improvements in nutritional, hematologic, and inflammatory markers.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".