The Role of Histology Alongside Clinical and Endoscopic Evaluation in the Management of IBD—A Narrative Review
Bibliographic record
Abstract
Inflammatory bowel diseases (IBD), including Crohn's disease (CD) and ulcerative colitis (UC), are chronic inflammatory conditions requiring continuous monitoring. Today, endoscopy is the gold standard for assessing disease activity, with histological evaluation providing additional insights. Studies suggest that persistent histological inflammation, despite endoscopic remission, may be associated with a higher risk of relapse in UC, suggesting its role in treatment decisions. In CD, histological assessment is limited by its patchy nature, transmural inflammation and lack of validated scoring systems. Few retrospective studies with conflicting results have examined the prognostic value of histological remission in CD, and its role in predicting long-term outcomes remains unclear. This narrative review aims to summarize and discuss the available evidence regarding the additional value of histological assessment in IBD management. In UC, the ongoing VERDICT study is expected to provide evidence on the impact of incorporating histological remission as a treatment target compared to a strategy based on clinical and endoscopic activity. Recently published interim results indicate that targeting histological remission does not lead to better clinical/biochemical disease activity. Thus, while patients achieving histological healing are associated with better outcomes, the question arises whether achieving histological remission is an intrinsic (biological) characteristic of the patient and indicator of an easier to treat patient group or a result of more effective therapy.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".