Disparities in Hepatocellular Carcinoma Incidence, Stage, and Survival: A Large Population-Based Study
Bibliographic record
Abstract
Abstract Background: Liver cancer is one of the most rapidly increasing cancers in the United States, and hepatocellular carcinoma (HCC) is its most common form. Disease burden and risk factors differ by sex and race/ethnicity, but a comprehensive analysis of disparities by socioeconomic status (SES) is lacking. We examined the relative impact of race/ethnicity, sex, and SES on HCC incidence, stage, and survival. Methods: We used Surveillance, Epidemiology, and End Results (SEER) 18 data to identify histologically confirmed cases of HCC diagnosed between January 1, 2000 and December 31, 2015. We calculated age-adjusted HCC incidence, stage at diagnosis (local, regional, distant, unstaged), and 5-year survival, by race/ethnicity, SES and sex, using SEER*Stat version 8.3.5. Results: We identified 45,789 cases of HCC. Incidence was highest among low-SES Asian/Pacific Islanders (API; 12.1) and lowest in high-SES Whites (3.2). Incidence was significantly higher among those with low-SES compared with high-SES for each racial/ethnic group (P < 0.001), except American Indian/Alaska Natives (AI/AN). High-SES API had the highest percentage of HCC diagnosed at the local stage. Of all race/ethnicities, Blacks had the highest proportion of distant stage disease in the low- and high-SES groups. Survival was greater in all high-SES racial/ethnic groups compared with low-SES (P < 0.001), except among AI/ANs. Black, low-SES males had the lowest 5-year survival. Conclusions: With few exceptions, HCC incidence, distant stage at diagnosis, and poor survival were highest among the low-SES groups for all race/ethnicities in this national sample. Impact: HCC prevention and control efforts should target low SES populations, in addition to specific racial/ethnic groups.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".