Factors Associated With Outcomes of Patients With Primary Sclerosing Cholangitis and Development and Validation of a Risk Scoring System
Bibliographic record
Abstract
We sought to identify factors that are predictive of liver transplantation or death in patients with primary sclerosing cholangitis (PSC), and to develop and validate a contemporaneous risk score for use in a real-world clinical setting. Analyzing data from 1,001 patients recruited to the UK-PSC research cohort, we evaluated clinical variables for their association with 2-year and 10-year outcome through Cox-proportional hazards and C-statistic analyses. We generated risk scores for short-term and long-term outcome prediction, validating their use in two independent cohorts totaling 451 patients. Thirty-six percent of the derivation cohort were transplanted or died over a cumulative follow-up of 7,904 years. Serum alkaline phosphatase of at least 2.4 × upper limit of normal at 1 year after diagnosis was predictive of 10-year outcome (hazard ratio [HR] = 3.05; C = 0.63; median transplant-free survival 63 versus 108 months; P < 0.0001), as was the presence of extrahepatic biliary disease (HR = 1.45; P = 0.01). We developed two risk scoring systems based on age, values of bilirubin, alkaline phosphatase, albumin, platelets, presence of extrahepatic biliary disease, and variceal hemorrhage, which predicted 2-year and 10-year outcomes with good discrimination (C statistic = 0.81 and 0.80, respectively). Both UK-PSC risk scores were well-validated in our external cohort and outperformed the Mayo Clinic and aspartate aminotransferase-to-platelet ratio index (APRI) scores (C statistic = 0.75 and 0.63, respectively). Although heterozygosity for the previously validated human leukocyte antigen (HLA)-DR*03:01 risk allele predicted increased risk of adverse outcome (HR = 1.33; P = 0.001), its addition did not improve the predictive accuracy of the UK-PSC risk scores. Conclusion: Our analyses, based on a detailed clinical evaluation of a large representative cohort of participants with PSC, furthers our understanding of clinical risk markers and reports the development and validation of a real-world scoring system to identify those patients most likely to die or require liver transplantation.
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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 | 0.000 |
| 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".