Metastasis in patients with hepatocellular carcinoma: Prevalence, determinants, prognostic impact and ability to improve the Barcelona Clinic Liver Cancer system
Bibliographic record
Abstract
BACKGROUND & AIM: Patients with hepatocellular carcinoma and metastasis are classified as advanced or terminal stage by the Barcelona Clinic Liver Cancer system. This study investigates the prevalence, determinants, and prognostic effect of metastasis and its ability to improve the Barcelona Clinic Liver Cancer system. METHODS: A total of 3414 patients were enrolled. The Kaplan-Meier and Cox regression methods were used to determine survival predictors. Akaike information criterion was used to compare the prognostic performance of staging systems. RESULTS: There were 357 (10%) patients having extrahepatic metastasis at the time of diagnosis. Metastases were associated with old age, alcoholism, hepatitis B, poorer liver function, higher α-foetoprotein level and larger tumour burden (all P < .05). Vascular invasion was associated with metastasis regardless of total tumour volume, and higher α-foetoprotein level and multiple tumours were associated with metastasis in patients with smaller tumour volume (all P < .05). Patients with both vascular invasion and metastasis had significantly worse outcome compared to patients with either vascular invasion or metastasis (P < .05). In the Cox proportional model, the co-existence of vascular invasion and metastasis was an independent predictor of decreased survival (P < .05). Re-allocating 181 Barcelona Clinic Liver Cancer stage C patients with both vascular invasion and metastasis into stage D was associated with lower Akaike information criterion, indicating enhanced prognostic power of the Barcelona Clinic Liver Cancer. CONCLUSIONS: Metastasis is not uncommon, and is strongly associated with tumoural factors and poor long-term survival in hepatocellular carcinoma. Modification of the Barcelona Clinic Liver Cancer system based on vascular invasion and metastasis may further improve its predictive accuracy in advanced stage patients.
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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".