Selection of patients of hepatocellular carcinoma beyond the Milan criteria for liver transplantation.
Bibliographic record
Abstract
The Milan criteria have been proven to be reliable and easily applicable in selection of patients with small unresectable hepatocellular carcinomas for liver transplantation. It has been repeatedly shown that patients who met these criteria had a 5-year survival of over 70% after transplantation. Such a result is remarkably good for an otherwise incurable malignancy. The main disadvantage of this set of criteria is that it is rather restrictive. Following it religiously denies transplantation to many patients who have tumor stage slightly more advanced. There have been many attempts to extend the criteria to include tumors with larger sizes (as in the UCSF criteria) or with a larger number (as in the Kyoto criteria). Alpha-fetoprotein and PIVKA-II, two biological markers in more aggressive tumors, have also been employed in the selection of patients, and biopsies have been used by the University of Toronto to determine tumor aggressiveness before deciding on transplantation. Patients with tumors beyond the Milan criteria yet not of a high grade have been accepted for transplantation and their survival is comparable to that of transplant recipients who were within the Milan criteria. Preoperative dual-tracer ((11)C-acetate and FDG) positron emission tomography has been used to determine tumor grade, and transarterial chemoembolization has been used to downstage tumors, rendering them meeting the Milan criteria. Patients with downstaged tumors have excellent survival after transplantation. Partial response to chemical treatment is a reflection of less aggressive tumor behavior. Careful selection of patients beyond the Milan criteria with the aid of serum tumor marker assay, positron emission tomography or tumor biopsy allows transplanting more patients without compromising survival. The use of liver grafts either from the deceased or from living donors could thus be justified.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".