Accuracy of PanMayo endoscopic score in predicting long-term disease outcomes in ulcerative colitis – a promising scoring system
Bibliographic record
Abstract
Aims Colonoscopy plays a crucial role in management of ulcerative colitis (UC) that helps to assess mucosal healing. Different scoring systems are available to assess severity, however most of them do not correlate with disease extent. Our study aimed to assess the predictive value and accuracy of PanMayo score compared to MES, UCEIS and Dublin in mid- and long-term disease outcomes. Methods This is a retrospective, two-center study. UC patients, who underwent colonoscopy due to any reason between 2016 and 2018, were consecutively enrolled. PanMayo, MES, UCEIS and Dublin scores were recorded with clinical and demographical data at baseline. Disease flare, need for change in therapy (incl. initiation of biologicals, need for systemic steroids), hospitalisations and colectomy were collected during an at least 3-years follow-. Patients were stratified by using baseline clinical activity (pMayo>1). Log-rank, logistic regression and Chi 2 tests were used to analyze outcomes and Kaplan Meier curves were plotted. Results A total of 250 UC patients (Table 1.) were enrolled. 157 (male ratio 0.49; mean age 46 IQR 19.5 years) UC patients had clinical remission, while 93 had active disease at baseline (male ratio 0.43; mean age 42 IQR 25 years). PanMayo, MES, and Dublin scores were positively associated with risk of flare-up (p=0.002; p<0.01; p=0.003). Increasing MES score was coupled with risk of relapse. PanMayo score (above 12 points), but not MES or UCEIS, was associated with the need of new biological (p<0.001) and treatment escalation (p=0.018), similar trend was found for the Dublin score for need for new biologicals in the remission cohort. All scores were strongly associated with the need for systemic steroids in patients with baseline remission. In the cohort with active disease at baseline, PanMayo (p=0.016) and Dublin (p=0.009) scores were associated to colectomy risk. Conclusions Our study suggests that combined endoscopic assessment of the extent and severity may be more precise in predicting disease outcomes in UC. PanMayo score may be an alternative of the existing scoring systems and was associated more granularly with disease outcomes. [ 1 ] [ 2 ] [ 3 ] [ 4 ] Publication History Article published online: 15 April 2024 © 2024. European Society of Gastrointestinal Endoscopy. All rights reserved. Georg Thieme Verlag KG Rüdigerstraße 14, 70469 Stuttgart, Germany
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".