Predictors of survival following liver transplantation for pediatric hepatoblastoma and hepatocellular carcinoma: Experience from the Society of Pediatric Liver Transplantation (SPLIT)
Bibliographic record
Abstract
Management of unresectable pediatric hepatoblastoma (HB) and hepatocellular carcinoma (HCC) remains challenging. The Society of Pediatric Liver Transplantation (SPLIT) database was used to study survival predictors in pediatric liver transplantation (LT) for HB and HCC. Event-free survival (EFS), associated risk factors, and postoperative complications were studied in children requiring LT for HB/HCC at 16 SPLIT centers. Three-year EFS was 81% for HB (n = 157) and 62% for HCC (n = 18) transplants. Of HB transplants, 6.9% were PRETEXT II and 15.3% were POST-TEXT I/II. Tumor extent did not impact survival (p = NS). Salvage (n = 13) and primary HB transplants had similar 3-year EFS (62% versus 78%, p = NS). Among HCC transplants, 3-year EFS was poorer in older patients (38% in ≥8-year-olds vs 86% <8-year-olds) and those with larger tumors (48% for those beyond versus 83% within Milan criteria, p = NS). Risk of infection (HR 1.5, 95% CI 1.1-2.2, p = .02) and renal injury (HR 2.4, 95% CI 1.7-3.3, p < .001) were higher in malignant versus nonmalignant LT. Survival is favorable for pediatric HB and HCC LT, including outcomes after salvage transplant. Unexpected numbers of LTs occurred in PRE/POST-TEXT I/II tumors. Judicious patient selection is critical to distinguish tumors that are potentially resectable; simultaneously, we must advocate for patients with unresectable malignancies to receive organs.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".