PWE-260 Optimal C reactive protein cut-off point for predicting hospitalisation in patients with moderately active Crohn's disease
Bibliographic record
Abstract
Introduction To identify high risk patients among patients with moderate Crohn's disease (CD), we explored the association between C reactive protein (CRP) concentration and hospitalisation risk for patients with moderately active CD and identified the optimal CRP cut-off point as a marker to predict CD-related hospitalisation. CRP is a well-studied and commonly used laboratory marker of inflammation in CD. 1 The relationship between CRP and hospitalisation risk given the same Crohn's Disease Activity Impairment (CDAI) score in patients with moderate CD has not been studied. Methods Data from CHARM, a 56-week (wk), randomised, placebo-controlled trial of adalimumab maintenance therapy, were analysed. All patients received adalimumab during a 4-wk, open-label induction period; patients were then randomised to adalimumab or placebo for a 52-wk double-blind period. For this analysis, only patients who were randomised to placebo at Wk 4 and had moderate CD, defined as CDAI ≤300 at Wk 4, were analysed. A Cox model was applied to analyse the association between Wk-4 CRP concentration and the probability of having a CD-related hospitalisation during the 52-wk double-blind period. Wk-4 CDAI score, Wk-4 steroid use, age, sex, weight, body mass index, and prior anti–tumour necrosis factor use were also adjusted in the model. Patients were censored if they switched to open-label adalimumab or dropped out. A receiver operating characteristic (ROC) curve was used to identify the optimal CRP cut-off point to best predict the 52-wk CD-related hospitalisation rate. Results The analysis population included 214 patients randomised to placebo with Wk-4 CDAI ≤300. An elevated Wk-4 CRP concentration was associated with a greater chance of CD-related hospitalisation (HR=1.24; p=0.002). The ROC curve identified a CRP concentration =1.41 mg/dl as the dichotomising point (area under the curve=0.68; sensitivity=0.58; specificity=0.80). Risk of CD-related hospitalisation during the double-blind period was 3.4 times greater for patients with CRP concentrations ≥1.41 mg/dl at Wk 4 vs patients with CRP concentrations <1.41 mg/dl (p=0.015), with control for CDAI and other covariates. Conclusion Early CRP concentration represents a moderate to good marker to predict CD-related hospitalisation for patients with moderately active CD given the same CDAI score. CRP concentration of 1.41 mg/dl was the optimal cut-off point for predicting long-term CD-related hospitalisation. Competing interests J-F Colombel Consultant for: Abbott, Speaker bureau with: Abbott, W Sandborn Grant/Research Support from: Abbott, Consultant for: Abbott, E Louis Speaker bureau with: Abbott, Conflict with: Abbott, R Panaccione Grant/Research Support from: Abbott, Consultant for: Abbott, Speaker bureau with: Abbott, Conflict with: Abbott, R Thakkar Shareholder with: Abbott, Employee of: Abbott, M Castillo Shareholder with: Abbott, Employee of: Abbott, M Yang Shareholder with: Abbott, Employee of: Abbott, T Finney-Hayward Shareholder with: Abbott, Employee of: Abbott, J Chao Shareholder with: Abbott, Employee of: Abbott, P Mulani Shareholder with: Abbott, Employee of: Abbott. Reference 1. Henriksen M , et al . Gut 2008; 57 :1518–23.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".