How achievable are STRIDE-II treatment targets in real-world practice and do they predict long-term treatment outcomes?
Bibliographic record
Abstract
Objective The second iteration of the Selecting Therapeutic Targets in Inflammatory Bowel Disease (STRIDE-II) initiative recommends use of the Simple Endoscopic Score for Crohn’s disease (SES-CD) as a treatment target for patients with CD. We aimed to assess whether the STRIDE-II endoscopic endpoints are achievable and whether the degree of mucosal healing (MH) affects long-term outcomes. Design/method We performed a retrospective observational study between 2015 and 2022. Patients with CD who had baseline and follow-up SES-CD scores after biological therapy initiation were included. The primary outcome was treatment failure, defined as the need for: (1) change of biological therapy for active disease (2) corticosteroid use (3) CD-related hospitalisation or (4) surgery. We compared rates of treatment failure with the degree of MH achieved. Patients were followed up until treatment failure or study end (August 2022). Results 50 patients were included and followed up for median 39.9 (34.6–48.6) months. Baseline characteristics: 62% male, median age 36.4 (27.8–43.9) years, disease distribution (L1: 4, L2: 11, L3: 35, perianal: 18). The proportion of patients achieving STRIDE-II end-points were: SES-CD ≤ 2–25 (50%) and >50% reduction in SES-CD—35 (70%). Failure to achieve SES-CD ≤ 2 (HR 11.62; 95% CI 3.33 to 40.56, p=0.003) or >50% improvement in SES-CD (HR 30.30; 95% CI 6.93 to 132.40, p<0.0001) predicted treatment failure. Conclusion Use of SES-CD is feasible in real-world clinical practice. Achieving an SES-CD ≤ 2 or a greater than 50% reduction, as set out by STRIDE-II, is associated with reduced rates of overall treatment failure including CD-related surgery.
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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 | 0.013 | 0.048 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".