The Relationship Between Endoscopic and Clinical Recurrence in Postoperative Crohn’s Disease: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
BACKGROUND AND AIMS: We aimed to quantify the magnitude of the association between endoscopic recurrence and clinical recurrence [symptom relapse] in patients with postoperative Crohn's disease. METHODS: Databases were searched to October 2, 2020, for randomised controlled trials [RCTs] and cohort studies of adult patients with Crohn's disease with ileocolonic resection and anastomosis. Summary effect estimates for the association between clinical recurrence and endoscopic recurrence were quantified by risk ratios [RR] and 95% confidence intervals [95% CI]. Mixed-effects meta-regression evaluated the role of confounders. Spearman correlation coefficients were calculated to assess the relationship between these outcomes as endpoints in RCTs. An exploratory mixed-effects meta-regression model with the logit of the rate of clinical recurrence as the outcome and the rate of endoscopic recurrence as a predictor was also evaluated. RESULTS: In all, 37 studies [N = 4053] were included. For eight RCTs with available data, the RR for clinical recurrence for patients who experienced endoscopic recurrence was 10.77 [95% CI 4.08 to 28.40; GRADE moderate certainty evidence]; the corresponding estimate from 11 cohort studies was 21.33 [95% CI 9.55 to 47.66; GRADE low certainty evidence]. A single cohort study showed a linear relationship between Rutgeerts score and clinical recurrence risk. There was a strong correlation between endoscopic recurrence and clinical recurrence treatment effect estimates as trial outcomes [weighted Spearman correlation coefficient 0.51]. CONCLUSIONS: The associations between endoscopic recurrence and subsequent clinical recurrence lend support to the choice of endoscopic recurrence to monitor postoperative disease activity and as a primary endpoint in clinical trials of postoperative Crohn's disease.
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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 | 0.022 | 0.051 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.039 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".