Prediction of Hepatocellular Carcinoma Recurrence Beyond Milan Criteria After Resection
Bibliographic record
Abstract
OBJECTIVE: This study aims to validate a previously reported recurrence clinical risk score (CRS). SUMMARY OF BACKGROUND DATA: Salvage transplantation after hepatocellular carcinoma (HCC) resection is limited to patients who recur within Milan criteria (MC). Predicting recurrence patterns may guide treatment recommendations. METHODS: An international, multicenter cohort of R0 resected HCC patients were categorized by MC status at presentation. CRS was calculated by assigning 1 point each for initial disease beyond MC, multinodularity, and microvascular invasion. Recurrence incidences were estimated using competing risks methodology, and conditional recurrence probabilities were estimated using the Bayes theorem. RESULTS: From 1992 to 2015, 1023 patients were identified, of whom 613 (60%) recurred at a median follow-up of 50 months. CRS was well validated in that all 3 factors remained independent predictors of recurrence beyond MC (hazard ratio 1.5-2.1, all P < 0.001) and accurately stratified recurrence risk beyond MC, ranging from 19% (CRS 0) to 67% (CRS 3) at 5 years. Among patients with CRS 0, no other factors were significantly associated with recurrence beyond MC. The majority recurred within 2 years. After 2 years of recurrence-free survival, the cumulative risk of recurrence beyond MC within the next 5 years for all patients was 14%. This risk was 12% for patients with initial disease within MC and 17% for patients with initial disease beyond MC. CONCLUSIONS: CRS accurately predicted HCC recurrence beyond MC in this international validation. Although the risk of recurrence beyond MC decreased over time, it never reached zero.
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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 | 0.001 | 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".