Survival of Patients with Hepatooellular Carcinoma In Manitoba after the introduction of Transarterial Chemoembollzation
Bibliographic record
Abstract
Hepatocellular carcinoma (HCC) is the most common type of primary liver tumor. It is the second fastest growing cancer in incidence. The 5 year survival in Manitoba for those dignosed between 2011 and 2015 was 14%. This poor outcome was thought to be due to lack of treatment options. The aims of this study were to look at changes in survival after the Introduction of Transarterial Chemoembolization (T ACE) and to study the characteristics of three groups; those who received curative treatment, those who received noncurative treatment, and those who received supportive care. This was a retrospective study of patients diagnosed between 2011 and 2019 and Included 572 patients. There has been a significant improvement in survival from 2011 to 2019. The 5 year OS has increased from 14% to 21% between the 2011 to 2015 and the 2011 to 2019 cohorts . Patients with ascites, portal vein thrombosis or multiple focal disease are significantly more likely to .get supportive care only. Therefore, early identification and maintenance of liver function are paramount to providing curative and noncurative treatments . Cirrhosis and portal hypertension do not affect treatment options . Consequently, primary care providers should be aware that cirrhosis and portal hypertension do not exclude their patients from treatment In conclusion , our study indicates that adopting new proven treatments has a positive effect on survival of patients. Additionally, developing provincial guidelines that include clear criteria for use of local therapies ls likely to continue the trend of Improving survival.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".