Epidemiology of Hepatocellular Carcinoma
Bibliographic record
Abstract
Although rare in Canada and the United States, hepatocellular carcinoma (HCC) ranks as the eighth most common cancer in the world. High-risk regions are East and Southeast Asia, and sub-Saharan Africa. Independent of race and geography, rates in men are at least two to three times those in women; this sex ratio is more pronounced in high-risk regions. Rates of HCC in the United States have increased by 70% over the past two decades. Registry data in Canada and Western Europe show similar trends. In contrast, the incidence of HCC in Singapore and Shanghai, China, both high-risk regions, has declined steadily over the past two decades. Among white and black Americans, there is an inverse relationship between social class status and HCC incidence. Chronic infection by the hepatitis B virus (HBV) is by far the most important risk factor for HCC in humans. It is estimated that 80% of HCC worldwide is etiologically associated with HBV. In the United States, although the infection rate in the general population is low, HBV is estimated to account for one in four cases of HCC among non-Asians. Chronic infection by the hepatitis C virus is another important risk factor for HCC in the United States; however, this virus is believed to play a relatively minor role in the development of HCC in Africa and Asia. Dietary aflatoxin exposure is an important codeterminant of HCC risk in Africa and parts of Asia. In Canada and the United States, excessive alcohol intake, cigarette smoking and oral contraceptive use in women also are risk factors for HCC.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".