Treatment Targets in Ulcerative Colitis: Is It Time for All In, including Histology?
Bibliographic record
Abstract
The main therapeutic goal of ulcerative colitis (UC) is to induce and maintain remission to prevent long-term disease progression. Treat-to-target strategies, first introduced by the STRIDE consensus and updated in 2021, have shifted focus from symptomatic control toward more stringent objective endpoints. Today, patient monitoring should be based on a combination of biomarkers and clinical scores, while patient-reported outcomes could be used as short-term targets in monitoring disease activity and therapeutic response. In addition, endoscopic healing was the preferred long-term goal in UC. A Mayo endoscopic score (MES) ≤ 1 can be recommended as a minimum target. However, recent evidence suggests that more stringent endoscopic goals (MES of 0) are associated with superior outcomes. Recently, emerging data support that histological remission (HR) is a superior prognostic factor to endoscopic healing in predicting long-term remission. Despite not yet being recommended as a target, HR may become an important potential therapeutic goal in UC. However, it remains questionable if histological healing should be used as a routine assessment in addition to clinical, biomarker, and endoscopic targets in all patients. Therefore, in this review, our aim was to discuss the current evidence for the different treatment targets and their value in everyday clinical practice.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".