Network Meta‐Analysis: Comparative Efficacy of Biologics and Small Molecules in the Induction and Maintenance of Remission in Crohn's Disease
Bibliographic record
Abstract
BACKGROUND: Advances in medical management of Crohn's disease (CD) have transformed therapeutic goals. Clinical and endoscopic remission are important endpoints. AIM: To compare the efficacy of different advanced therapies in patients with CD. METHODS: We performed a literature search up to January 2025. We included phase 3 randomised controlled trials (RCTs) against placebo or an active comparator. The primary endpoint was induction and maintenance of clinical remission (CD Activity Index [CDAI] < 150 points). Secondary endpoints included induction and maintenance of endoscopic remission (Simple Endoscopic Score for CD (SES-CD) of ≤ 4 or CD Endoscopic Index of Severity (CDEIS) of ≤ 4). We performed network meta-analysis (NMA) using the Frequentist method. RESULTS: We included 39 studies. Induction of clinical remission analysis showed that infliximab combination with azathioprine ranked highest (93.2%), followed by guselkumab (88.6%) and adalimumab (76.9%). Guselkumab was superior to most interventions in inducing clinical remission. In maintenance of clinical remission, combination of infliximab and azathioprine ranked highest (75.7%) followed by mirikizumab (71.8%) and guselkumab (71.5%). There was no statistically significant difference between therapies in maintaining clinical remission. In induction of endoscopic remission, upadacitinib (88.5%) ranked highest, followed by risankizumab (73.7%) and guselkumab (73.4%). Guselkumab (74%) ranked highest in maintaining endoscopic remission, followed by adalimumab (67%) and mirikizumab (64%). CONCLUSION: Novel IL-23 inhibitors (such as mirikizumab, risankizumab and guselkumab) and anti-TNFs (such as infliximab and adalimumab) ranked high in the induction of clinical and endoscopic remission. This highlights the potential of novel advanced therapies for 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 | 0.027 | 0.053 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.042 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".