Effect of socioeconomic status on hepatocellular carcinoma incidence and stage at diagnosis, a population‐based cohort study
Bibliographic record
Abstract
BACKGROUND & AIMS: Hepatocellular carcinoma (HCC) incidence is increasing worldwide and cirrhosis is the most important risk factor predominantly caused by chronic viral hepatitis infection. We studied the impact of socioeconomic status (SES) on HCC incidence and stage at diagnosis among viral hepatitis cases. METHODS: A population-based retrospective cohort study was conducted through the Ontario Cancer Registry linked data. Incidence rates were calculated using person-time methodology. Association between SES (income quintile) and HCC incidence was assessed using proportional-hazards regression. The impact of SES on HCC stage was investigated using logistic regression. RESULTS: Among 11 350 individuals diagnosed with viral hepatitis between 1991 and 2010, a crude HCC incidence rate of 21.4 cases per 1000 person-years was observed. Adjusting for age, gender, urban/rural residence and year of viral hepatitis diagnosis, a significant association was found between SES and HCC incidence, with an increased risk among individuals in the lowest three income quintiles (incidence rate ratio, IRR = 1.235; 95% CI: 1.074-1.420; IRR = 1.183; 95% CI: 1.026-1.364; IRR = 1.158; 95% CI: 1.000-1.340 respectively). No significant association between SES and HCC incidence was found after additionally adjusting for risk factors associated with HCC. However, HCC risk factors such as cirrhosis and HIV are associated with SES. Furthermore, no association was found between SES and HCC stage. CONCLUSIONS: The association between SES and HCC incidence is likely because of differences in risk factors across income quintiles. Investigating how SES affects HCC incidence facilitates an understanding of which populations are at elevated risk for HCC.
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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 | 0.001 | 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".