Recommendations for Standardizing MRI-based Evaluation of Perianal Fistulizing Disease Activity in Pediatric Crohn’s Disease Clinical Trials
Bibliographic record
Abstract
BACKGROUND: Perianal fistulas and abscesses occur commonly as complications of pediatric Crohn's disease (CD). A validated imaging assessment tool for quantification of perianal disease severity and activity is needed to evaluate treatment response. We aimed to identify magnetic resonance imaging (MRI)-based measures of perianal fistulizing disease activity and study design features appropriate for pediatric patients. METHODS: Seventy-nine statements relevant to MRI-based assessment of pediatric perianal fistulizing CD activity and clinical trial design were generated from literature review and expert opinion. Statement appropriateness was rated by a panel (N = 15) of gastroenterologists, radiologists, and surgeons using modified RAND/University of California Los Angeles appropriateness methodology. RESULTS: The modified Van Assche Index (mVAI) and the Magnetic Resonance Novel Index for Fistula Imaging in CD (MAGNIFI-CD) were considered appropriate instruments for use in pediatric perianal fistulizing disease clinical trials. Although there was concern regarding the use of intravascular contrast material in pediatric patients, its use in clinical trials was considered appropriate. A clinically evident fistula tract and radiologic disease defined as at least 1 fistula or abscess on pelvic MRI were considered appropriate trial inclusion criteria. A coprimary clinical and radiologic end point and inclusion of a patient-reported outcome were also considered appropriate. CONCLUSION: Outcomes of treatment of perianal fistulizing disease in children must include MRI. Existing multi-item measures, specifically the mVAI and MAGNIFI-CD, can be adapted and used for children. Further research to assess the operating properties of the indices when used in a pediatric patient population is ongoing.
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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 | 0.599 | 0.759 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.008 | 0.014 |
| Bibliometrics | 0.014 | 0.016 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.017 | 0.012 |
| Open science | 0.013 | 0.007 |
| Research integrity | 0.024 | 0.026 |
| Insufficient payload (model declined to judge) | 0.005 | 0.006 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".