Induction Treatment with Anti-TNF Decreases C-Reactive Protein Levels among Crohnʼs Disease Patients: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
Purpose: C-reactive protein (CRP) is a non-specific marker of inflammation and is used in the monitoring of patients with Crohn's disease (CD). Among CD patients, CRP levels are associated with disease activity and are correlated with endoscopic remission. We conducted a systematic review and meta-analysis to quantify changes in CRP following induction therapy with an anti-TNF agent in CD patients. Methods: MEDLINE, EMBASE, and Cochrane CENTRAL were searched to identify randomized placebo-controlled trials (RCTs) of any anti-TNF agent (adalimumab, infliximab, or certolizumab) used to treat CD. Eligible studies included data on CRP levels at baseline and at any point following induction treatment. Studies reporting both a measure of effect (mean or median) and a corresponding measure of variability at both baseline and follow-up were included in a meta-analysis using a random effects model. Weighted mean differences (WMDs) and 95% confidence intervals (CIs) were calculated to quantify the drop in CRP following induction treatment. Differences were calculated separately for all trial participants receiving an anti-TNF, and for those receiving placebo. Heterogeneity was assessed using the Cochran Q statistic and the I2 statistic. Results: Six RCTs of anti-TNF therapy in CD reported CRP data following induction treatment (one adalimumab, two infliximab, and three certolizumab). Decreases in CRP levels following induction treatment were observed in the treatment arms of all identified trials. In contrast, decreases in CRP among patients receiving placebo were not observed. Two of the trials (both infliximab) provided sufficient data to pool in a meta-analysis. Patients receiving infliximab experienced a significant decrease in CRP concentration (WMD = -1.59; 95% CI -2.25, -0.94). CRP concentrations among patients receiving placebo did not significantly change during the induction period (WMD = 0.17; 95% CI -0.64, 0.98). Significant heterogeneity was not observed for either the treatment (p = 0.300; I2 = 6.9%) or placebo trial arms (p = 0.899; I2 = 0.0%). Conclusion: Induction therapy with an anti-TNF is effective in decreasing CRP concentrations among Crohn's disease patients. CRP may be an effective non-invasive indicator of patients' initial responses to anti-TNF therapy. Disclosure - EK, IAV, YL, SH: None. RP: speaker, a consultant and an advisory board member for Abbott Laboratories, Merck, Schering-Plough, Shire, Centocor, Elan Pharmaceuticals, and Procter and Gamble; consultant and speaker for Astra Zeneca; consultant and an advisory board member for Ferring and UCB; consultant for Glaxo-Smith Kline and Bristol Meyers Squibb; speaker for Byk Solvay, Axcan, Jansen, and Prometheus; research funding from Merck, Schering-Plough, Abbott Laboratories, Elan Pharmaceuticals, Procter and Gamble, Bristol Meyers Squibb, and Millennium Pharmaceuticals; educational support from Merck, Schering-Plough, Ferring, Axcan, and Jansen. CHS: speaker for Janssen Canada; participated in advisory board for Janssen Canada and Abbvie; received research support from Janssen Canada. SG: speaker for Merck, Schering-Plough, Centocor, Abbott, UCB Pharma, Pfizer, Ferring, and Procter and Gamble; participated in ad-hoc advisory board meetings for Centocor, Abbott, Merck, Schering-Plough, Proctor and Gamble, Shire, UCB Pharma, Pfizer, and Millennium; research funding from Procter and Gamble, Merck, and Schering-Plough. GGK: speaker for Merck, Schering-Plough, Abbott, and UCB Pharma; participated in advisory board meetings for Abbott, Merck, Schering-Plough, Shire, and UCB Pharma; research support from Abbott and Shire.
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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 | 0.011 | 0.025 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.036 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".