Natural history of liver disease in a large international cohort of children with Alagille syndrome: Results from the GALA study
Bibliographic record
Abstract
BACKGROUND AND AIMS: Alagille syndrome (ALGS) is a multisystem disorder, characterized by cholestasis. Existing outcome data are largely derived from tertiary centers, and real-world data are lacking. This study aimed to elucidate the natural history of liver disease in a contemporary, international cohort of children with ALGS. APPROACH AND RESULTS: This was a multicenter retrospective study of children with a clinically and/or genetically confirmed ALGS diagnosis, born between January 1997 and August 2019. Native liver survival (NLS) and event-free survival rates were assessed. Cox models were constructed to identify early biochemical predictors of clinically evident portal hypertension (CEPH) and NLS. In total, 1433 children (57% male) from 67 centers in 29 countries were included. The 10 and 18-year NLS rates were 54.4% and 40.3%. By 10 and 18 years, 51.5% and 66.0% of children with ALGS experienced ≥1 adverse liver-related event (CEPH, transplant, or death). Children (>6 and ≤12 months) with median total bilirubin (TB) levels between ≥5.0 and <10.0 mg/dl had a 4.1-fold (95% confidence interval [CI], 1.6-10.8), and those ≥10.0 mg/dl had an 8.0-fold (95% CI, 3.4-18.4) increased risk of developing CEPH compared with those <5.0 mg/dl. Median TB levels between ≥5.0 and <10.0 mg/dl and >10.0 mg/dl were associated with a 4.8 (95% CI, 2.4-9.7) and 15.6 (95% CI, 8.7-28.2) increased risk of transplantation relative to <5.0 mg/dl. Median TB <5.0 mg/dl were associated with higher NLS rates relative to ≥5.0 mg/dl, with 79% reaching adulthood with native liver ( p < 0.001). CONCLUSIONS: In this large international cohort of ALGS, only 40.3% of children reach adulthood with their native liver. A TB <5.0 mg/dl between 6 and 12 months of age is associated with better hepatic outcomes. These thresholds provide clinicians with an objective tool to assist with clinical decision-making and in the evaluation of therapies.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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".