Eight‐year nationwide survival analysis in relatives of patients with hepatocellular carcinoma: Role of viral infection
Bibliographic record
Abstract
BACKGROUND: Families of patients with hepatocellular carcinoma (HCC) carry a high risk of developing HCC. We determine the number of fatalities in relatives of HCC patients during an 8-year period to understand the risk and cause of HCC in relatives of patients with HCC. METHODS: From 1992 to 1997, 15 410 relatives of HCC patients in three generations were screened prospectively for HCC by ultrasonography, alpha-fetoprotein, liver biochemistry and viral markers. By using national citizen identification numbers, we searched the total fatalities in relatives of HCC patients between 1992 and 1999 from the national mortality data bank. The results were compared among different viral infection groups. RESULTS: Of the relatives studied, 37.8% were hepatitis B s antigen (HBsAg) positive (+), 4.3% were anti-hepatitis C virus (HCV) (+) and 1.7% were both HBsAg (+) and anti-HCV (+). A total of 399 fatalities, including 139 because of HCC (34.8%), 37 because of liver diseases (9.3%), 88 because of other cancers (22.1%) and 135 because of other diseases (33.8%), were found. Relatives who were HBsAg (+) or anti-HCV (+)showed a lower cumulative survival than did relatives who were negative for both HBsAg and anti-HCV. Relatives with dual infection of hepatitis B and C virus showed the highest mortality due to HCC or terminal liver diseases. CONCLUSIONS: Chronic viral infection rather than a hereditary factor is the main cause of a familial tendency for HCC. Dual infection of hepatitis B and C virus increases the risk of HCC or decompensated liver diseases.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".