Incidence, Characteristics, and Prognosis of Incidentally Discovered Hepatocellular Carcinoma after Liver Transplantation
Bibliographic record
Abstract
Background. We aimed to assess incidentally discovered hepatocellular carcinoma (iHCC) over time and to compare outcome to preoperatively diagnosed hepatocellular carcinoma (pdHCC) and nontumor liver transplants. Methods. We studied adults transplanted with a follow-up of at least one year. Patients were divided into 3 groups according to diagnosis of hepatocellular carcinoma. Results. Between 1990 and 2010, 887 adults were transplanted. Among them, 121 patients (13.6%) had pdHCC and 32 patients (3.6%) had iHCC; frequency of iHCC decreased markedly over years, in parallel with significant increase in pdHCC. Between 1990 and 1995, 120 patients had liver transplants, 4 (3.3%) of them had iHCC, and only 3 (2.5%) had pdHCC, while in the last 5 years, 263 patients were transplanted, 7 (0.03%) of them had iHCC, and 66 (25.1%) had pdHCC (P < 0.001). There was no significant difference between groups regarding patient survival; 5-year survival was 74%, 75.5%, and 77.3% in iHCC, pdHCC, and non-HCC groups, respectively (P = 0.702). Patients with iHCC had no recurrences after transplant, while pdHCC patients experienced 17 recurrences (15.3%) (P = 0.016). Conclusions. iHCC has significantly decreased despite steady increase in number of transplants for hepatocellular carcinoma. Patients with iHCC had excellent outcomes with no tumor recurrence and survival comparable to pdHCC.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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 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".