Efficacy of early biologic therapy versus late/conventional therapy in children and adolescents with Crohn’s disease: A systematic review and meta-analysis
Bibliographic record
Abstract
Background: The objective of this study was to estimate the effectiveness of early biologics compared to conventional treatment in the management of Crohn's disease among pediatric and adolescent patients. Methods: A comprehensive literature search was conducted in four electronic databases to identify relevant studies published from inception to 2023. The inclusion criteria comprised randomized controlled trials (RCTs) and cohort studies that reported on the efficacy and clinical outcomes of early biologic therapy compared to late/conventional therapy in children with Crohn's disease. The quality of the studies was assessed using the Cochrane Risk of Bias tool and the Newcastle Ottawa scale. Results: A total of 13 studies (2 RCTs and 11 cohort studies), involving 861 patients, were included in the meta-analysis. The results demonstrated that early biologic therapy was associated with a significantly higher rate of clinical remission (risk ratio [RR] 1.30, 95% confidence interval [CI] 1.10-1.54), lower relapse rates (RR 0.33, 95% CI 0.21-0.53), and improved mucosal healing (RR 1.47, 95% CI 1.10-1.97) compared to late/conventional therapy. However, it should be noted that there was evidence of publication bias among studies reporting clinical remission. Conclusion: In conclusion, early biologic therapy is significantly more effective in achieving clinical remission (within two years of diagnosis), promoting mucosal healing, and reducing relapse rates in pediatric and adolescent patients with Crohn's disease, compared to late/conventional therapy. These findings emphasize the importance of initiating biological therapy early in the treatment of Crohn's disease in this patient population.
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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 | 0.019 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.043 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 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".