The Current State of Pancreatic Cancer in Canada
Bibliographic record
Abstract
OBJECTIVE: This study aimed to evaluate the trends in the incidence, survival, and surgical therapy for Canadian patients affected by pancreatic cancer (PC). METHODS: The incidence, mortality, number of resections, and outcomes of patients with PC stratified by year, sex, and province were extracted from Canadian cancer databases. RESULTS: In 2012, PC was diagnosed in 4600 Canadians and it was responsible for 4300 deaths. The age-standardized incidence was 9 to 10 new cases per 100,000 individuals. The mortality rate remained the highest among all the solid tumors with a case-to-fatality ratio of 0.93. The age-standardized 5-year relative survival was 9.1% (95% confidence interval [CI], 8.3-10). There were geographic variations among provinces with the highest survival registered in Ontario (10.9%; 95% CI, 9.9-12) and the lowest survival reported in Nova Scotia (4.7%; 95% CI, 2.8-7.2). The percentage of patients who underwent surgery decreased from 19% (2006-2007) to 17% (2009-2010). Pancreatic resections were performed in high-volume centers in 74% of cases. In-hospital mortality was 5%, 93% of patients were discharged home, and 36% of patients required home support after discharge. CONCLUSIONS: Long-term outcomes of Canadian patients affected by PC remain unsatisfactory, with only 9% of the patients surviving at 5 years. Surgical therapy was performed only in 17% to 19% of patients.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".