Preoperative Alpha-Fetoprotein Slope is Predictive of Hepatocellular Carcinoma Recurrence after Liver Transplantation
Bibliographic record
Abstract
BACKGROUND: Liver transplantation (LT) offers a possible cure for patients with hepatocellular carcinoma (HCC) and cirrhosis. However, tumour progression while on the waiting list and tumour recurrence after LT are common. The prognostic significance of various pre- and postoperative variables were investigated in regard to tumour recurrence, with an emphasis on the slope of preoperative serum alpha-fetoprotein (AFP) levels. patients and METHODS: Data from 48 patients who had HCC diagnosed preoperatively and underwent LT at the McGill University Health Centre (Montreal, Quebec) were reviewed retrospectively, and possible risk factors for tumour recurrence were examined. RESULTS: Univariate analysis revealed a positive correlation between the preoperative AFP slope and vascular invasion (P = 0.045), total tumour diameter at explant (P = 0.040), Cancer of the Liver Italian Program score (P = 0.017) and recurrence-free survival (P = 0.028). Of the preoperative variables examined, only the preoperative AFP slope was identified as an independent predictor of tumour recurrence by multivariate analysis. Receiver operating characteristic analysis showed that the best discriminant cut-off value, calculated as the value of the maximized likelihood ratio, was preoperative AFP slope greater than 50 microg/L per month. At this cut-off, sensitivity was 36%, and specificity was 97%. Patients with a preoperative AFP slope greater than 50 microg/L per month had a much worse one-year recurrence-free survival rate than those with a preoperative AFP slope 50 microg/L per month or less (40% versus 90%, P < 0.001). CONCLUSIONS: These results suggest that the preoperative AFP slope is an important predictor of HCC recurrence after LT and should be examined in future studies of patients receiving LT for HCC.
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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) | 0.001 | 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 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".