Assessment of PredictSURE IBD Assay in a Multinational Cohort of Patients With Inflammatory Bowel Disease
Bibliographic record
Abstract
BACKGROUND AND AIMS: PredictSURE IBD is a prognostic blood test that classifies newly diagnosed, treatment-naïve Inflammatory Bowel Disease (IBD) patients into 'IBDhi' (high-risk) or 'IBDlo' (low-risk) groups (risk of future aggressive disease). We evaluated this assay in a multinational cohort and explored the effect of concomitant corticosteroids on its discrimination. METHODS: One hundred thirty-six (71 Ulcerative colitis [UC], 65 Crohn's Disease [CD]) and 41 (15 UC, 26 CD) patients with active IBD were 'unexposed' and 'exposed', respectively, to corticosteroids at baseline blood sampling. The number of treatment escalations, time to first escalation, and need for repeated escalations were compared between the biomarker subgroups. Another 20 patients (13 UC, 7 CD) were longitudinally sampled over 6 weeks after commencing corticosteroids. RESULTS: In corticosteroids-naïve UC and CD patients, all bowel surgeries (n = 6) and multiple therapy escalations (n = 10) occurred in IBDhi patients. IBDhi UC patients required significantly more treatment escalations, had a shorter time to first escalation, and a greater need for multiple escalations than IBDlo patients. No statistically significant differences were observed among CD patients. In corticosteroid-exposed patients, 66.6% of 'misclassifications' were IBDlo patients who required escalations. Among corticosteroid-treated patients with longitudinal sampling, 81.3% of those classified as IBDhi before steroids switched to IBDlo during therapy. CONCLUSIONS: No significant differences in treatment escalations were observed between biomarker-defined subgroups in CD. However, IBDhi UC patients required significantly earlier and more frequent therapy escalations, highlighting the need to further investigate PredictSURE IBD in UC. Notably, the discrimination ability of the biomarker was unreliable in patients receiving corticosteroid therapy.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 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".