Clinical Trial: A Pragmatic Randomised Controlled Study to Assess the Effectiveness of Two Patient Management Strategies in Mild to Moderate Ulcerative Colitis—The OPTIMISE Study
Bibliographic record
Abstract
Background: Current management of mild-to-moderate ulcerative colitis (UC) involves monitoring clinical markers of disease activity, such as stool frequency (SF) and rectal bleeding (RB), and adjusting treatment accordingly. Our aim was to assess whether targeting treatment based on faecal calprotectin (FC) levels (treat-to-target; T2T) provides greater UC disease control versus a symptom-based approach. Methods: This was a pragmatic, randomised (1:1) controlled study of patients with mild-to-moderate UC (global Mayo score 2–6) treated with ≤2.4 g/day 5-aminosalicylic acid that compared the effectiveness of two management strategies with (interventional arm) and without (reference arm) FC home monitoring over 12 months of follow-up. Treatment was optimised in the interventional arm using FC values and clinical symptoms (PRO-2), while the reference arm used only PRO-2. Results: 193 patients completed the study. No significant difference was found for the primary endpoint (Mayo Endoscopic Subscore [MES] = 0 at 12 months). A numerical advantage for the interventional arm over the reference arm for the primary endpoint (37.0% vs. 33.4%, respectively) and for MES ≤ 1, RB = 0, and SF ≤ 1 at 12 months was found following imputation for missing data. The composite endpoint of MES = 0, RB = 0, and SF ≤ 1 at 12 months was achieved at a significantly higher rate in the interventional arm than the reference arm (effect size [ES]: 0.17, 95% CI 0.02–0.32; p < 0.05). A similar result was obtained for MES ≤ 1, RB = 0 and SF ≤ 1 (ES: 0.22; 95% CI 0.07–0.37; p < 0.05). Conclusions: T2T using FC monitoring was effective in patients with mild-to-moderate UC at 12 months. Further longer-term studies are required to confirm the results.
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".