Factors predicting survival after post‐transplant hepatocellular carcinoma recurrence
Bibliographic record
Abstract
BACKGROUND: Although factors associated with an increased risk of recurrence after liver transplantation for hepatocellular carcinoma (HCC) have been extensively studied, the history of patients with a post-transplant recurrence is poorly known. METHODS: Patients experiencing a post-transplant HCC recurrence from 1996 to 2011 in two transplant programs were included. Demographic, transplant, and post-recurrence variables were assessed. RESULTS: Thirty patients experienced an HCC recurrence-22 men and 8 women with a mean age of 55 ± 6 years. Sixteen (53 %) were outside the Milan criteria at the time of transplantation. Most recurrences (60 %) appeared within the first 18 months after transplantation, ranging between 1.7 and 109 months (median 14.2 months). Mean post-recurrence survival was 33 ± 31 months. On univariate analysis, total tumor volume (TTV; p = 0.047), microvascular invasion (p = 0.011), and time from transplant to recurrence (p = 0.001) predicted post-recurrence survival. On multivariate analysis, both time from transplant to recurrence (p = 0.001) and history of rejection (p = 0.043), but not the location of the recurrence or the type of recurrence treatment, predicted post-recurrence survival. CONCLUSION: This study suggests that patients with early post-transplant HCC recurrence have worse outcomes. Those with a history of graft rejection have better survivals, possibly due to more active anti-cancer immunity.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".