The Sclerosing Cholangitis Outcomes in Pediatrics (SCOPE) Index: A Prognostic Tool for Children
Bibliographic record
Abstract
BACKGROUND AND AIMS: Disease progression in children with primary sclerosing cholangitis (PSC) is variable. Prognostic and risk-stratification tools exist for adult-onset PSC, but not for children. We aimed to create a tool that accounts for the biochemical and phenotypic features and early disease stage of pediatric PSC. APPROACH AND RESULTS: We used retrospective data from the Pediatric PSC Consortium. The training cohort contained 1,012 patients from 40 centers. We generated a multivariate risk index (Sclerosing Cholangitis Outcomes in Pediatrics [SCOPE] index) that contained total bilirubin, albumin, platelet count, gamma glutamyltransferase, and cholangiography to predict a primary outcome of liver transplantation or death (TD) and a broader secondary outcome that included portal hypertensive, biliary, and cancer complications termed hepatobiliary complications (HBCs). The model stratified patients as low, medium, or high risk based on progression to TD at rates of <1%, 3%, and 9% annually and to HBCs at rates of 2%, 6%, and 13% annually, respectively (P < 0.001). C-statistics to discriminate outcomes at 1 and 5 years were 0.95 and 0.82 for TD and 0.80 and 0.76 for HBCs, respectively. Baseline hepatic fibrosis stage was worse with increasing risk score, with extensive fibrosis in 8% of the lowest versus 100% with the highest risk index (P < 0.001). The model was validated in 240 children from 11 additional centers and performed well. CONCLUSIONS: The SCOPE index is a pediatric-specific prognostic tool for PSC. It uses routinely obtained, objective data to predict a complicated clinical course. It correlates strongly with biopsy-proven liver fibrosis. SCOPE can be used with families for shared decision making on clinical care based on a patient's individual risk, and to account for variable disease progression when designing future clinical trials.
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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 | 0.000 | 0.001 |
| 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".