Downstaging prior to liver transplantation for hepatocellular carcinoma: advisable but at the price of an increased risk of cancer recurrence - a retrospective study
Bibliographic record
Abstract
and alpha fetoprotein (AFP) ≤400 ng/ml criteria, with and without previous downstaging. Overall, 455 patients were listed, and 286 transplanted. Post-transplant follow-up was 38.5 ± 1.7 months. Patients downstaged to TTV115/AFP400 (n = 29) demonstrated similar disease-free survivals (DFS, 74% vs. 80% at 5 years, P = 0.949), but a trend to more recurrences (14% vs. 5.8%, P = 0.10) than those always within TTV115/AFP400 (n = 257). Similarly, patients downstaged to Milan criteria (n = 80) demonstrated similar DFS (76% vs. 86% at 5 years, P = 0.258), but more recurrences (11% vs. 1.7%, P = 0.001) than those always within Milan (n = 177). Among patients downstaged to Milan, those originally beyond TTV115/AFP400 (n = 27) had similar outcomes as those originally beyond Milan, but within TTV115/AFP400 (n = 53). However, the likelihood of being within Milan at transplant was lower for patients with more advanced original HCCs (P < 0.0001). Overall, despite an expected increase in post-transplant HCC recurrence, similar survivals can be achieved with and without downstaging, using the TTV115/AFP400 transplantation criteria, and including patients with advanced original HCCs. Downstaging should continue to be performed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".