Survival patterns for the top four cancers in Canada: the effects of age, region and period
Bibliographic record
Abstract
This study examined the variations in survival rates (1989-1991) and the trends (1969-1991), by sex, age and province, for patients diagnosed with breast, colorectal, lung or prostate cancer in Canada and compared the Canadian rates with those of nine American SEER registries. Five-year age-standardized relative survival rates (ASRs) were calculated, and the trends were estimated from variance-weighted linear regression of the ASRs for five periods of diagnosis (1969-1973, 1974-1978, 1979-1983, 1984-1988 and 1989-1991). In 1989-1991, the ASR varied among provinces for each cancer except female colorectal cancer. The lowest survival rates were observed in the youngest patients (15-44) for breast and prostate cancers, and in the oldest patients (75-99) of both sexes for lung and colorectal cancers. Over the five periods, a major trend toward improved survival was observed for breast, prostate and colorectal cancers (P<0.008), whereas no changes were seen for lung cancer. The ASRs in the western region were higher than in the Atlantic region over time (P<0.02) for each cancer. From the third period onward, the ASRs for Canadian patients with lung cancer were similar to those for the US patients and lower than for Canadian patients with breast, prostate or colorectal cancer. The observed increases in ASR for breast and prostate cancer are likely due to the increased use of screenings and the improved treatment modalities.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| 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".