Association of Biomarker Cutoffs and Endoscopic Outcomes in Crohn’s Disease: A Post Hoc Analysis From the CALM Study
Bibliographic record
Abstract
BACKGROUND: CALM was a randomized phase 3 trial in patients with Crohn's disease (CD) that demonstrated improved endoscopic outcomes when treatment was escalated based on cutoffs for inflammatory biomarkers, fecal calprotectin (FC), C-reactive protein (CRP), and CD Activity Index (CDAI) remission vs CDAI response alone. The purpose of this post hoc analysis of CALM was to identify drivers of treatment escalation and evaluate the association between biomarker cutoff concentrations and endoscopic end points. METHODS: The proportion of patients achieving CD Endoscopic Index of Severity (CDEIS) <4 and no deep ulcers 48 weeks after randomization was evaluated according to CRP <5 mg/L or ≥5 mg/L and FC <250 μg/g or ≥250 μg/g. Subgroup analyses were performed according to disease location, and sensitivity analyses were conducted in patients with elevated CRP and/or FC at baseline. The association between endoscopic end points and biomarker cutoffs was performed using χ 2 test. RESULTS: The proportion of patients who achieved the primary end point CDEIS <4 and no deep ulcers was significantly greater for those with FC <250 µg/g (74%; P < 0.001), with an additive effect for CRP <5 mg/L. The association of FC <250 µg/g with improved endoscopic outcomes was independent of disease location, although the greatest association was observed for ileocolonic disease. Fecal calprotectin <250 µg/g, CRP <5 mg/L, and CDAI <150 gave a sensitivity/specificity of 72%/63% and positive/negative predictive values of 86%/42% for CDEIS <4 and no deep ulcers 48 weeks after randomization. CONCLUSION: This post hoc analysis of CALM demonstrated that a cutoff of FC <250 µg/g is a useful surrogate marker for mucosal healing in CD.
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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 | 0.015 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".