Epidemiology, clinical treatment patterns, and survival of hepatocellular carcinoma in Manitoba
Bibliographic record
Abstract
Background: Hepatocellular carcinoma (HCC) has a very poor survival rate, especially for those who do not receive a potentially curative therapy. Methods: Treatment details were collected for 320 HCC patients diagnosed in Manitoba between January 2011 and December 2015. Patients had a mean age of 67.3 years, and 71.6% were men. Of these patients, 67 (20.9%) received curative treatment, 36 (11.3%) received non-curative treatment, and 217 (67.8%) received supportive care only; 71.3% of patients had liver cirrhosis. Alcoholic cirrhosis was the most common etiology of chronic liver disease (22.2%). Results: Those who received curative treatment had a significantly lower incidence of portal vein thrombosis and multinodular disease than those in other groups. Patients who received supportive care only had a higher incidence of ascites. We found no difference in the distribution of cirrhosis or portal hypertension among the treatment groups. The 2- and 5-year overall survival rates for the whole cohort were 27% and 14%, respectively. No significant change was found in 2-year survival for patients diagnosed in each year from 2011 to 2015 ( p = 0.250). Also, we found no significant change in proportion of treatment given to patients over the same period ( p = 0.432). Conclusion: The poor survival rate of HCC patients in Manitoba could potentially be improved by maximizing the use of local therapy and by implementing multidisciplinary–based case discussion. Efforts should also be directed toward early management of infective, alcoholic, and non-alcoholic steatohepatitis, which will, we hope, lead to a reduction in the incidence of HCC.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".