Factors Affecting the Prognosis of Small Hepatocellular Carcinoma in Taiwanese Patients Following Hepatic Resection
Bibliographic record
Abstract
BACKGROUND: Small hepatocellular carcinoma (HCC) affects millions of individuals worldwide. Surveillance of high-risk patients increases the early detection of small HCC. OBJECTIVE: To identify prognostic factors affecting the overall survival (OS) and recurrence-free survival (RFS) of patients with small HCC. METHODS: The present prospective study enrolled 140 Taiwanese patients with stage I or stage II small HCC. Clinical parameters of interest included operation type, tumour size, tumour histology, Child- Pugh class, presence of hepatitis B surface antigen and liver cirrhosis, hepatitis C status, alpha-fetoprotein, total bilirubin and serum albumin levels, and administration of antiviral and salvage therapies. RESULTS: Tumour size correlated significantly with poorer OS in patients with stage I small HCC (P=0.014); however, patients with stage II small HCC experienced a significantly poorer RFS (P=0.033). OS rates did not differ significantly between patients with stage I and stage II small HCC. Tumour margins, tumour histology and cirrhosis did not significantly affect OS or RFS (P>0.05). DISCUSSION: Increasing tumour size has generally been associated with poorer prognoses in cases of HCC. The present study verified the relationship between small HCC tumour size and OS; however, a reduction in OS with increasing tumour size was demonstrated for patients with stage I - but not for stage II - small HCC. CONCLUSION: Patients with stage II small HCC may benefit from aggressive surveillance for tumour recurrence and appropriate salvage treatment. Further studies are needed for additional stratification of stage I patients to identify those at increased risk of death.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 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".