Increasing survival from leukemia among adolescents and adults in Canada: A closer look.
Bibliographic record
Abstract
BACKGROUND: Survival from adult onset leukemia has increased substantially in Canada since at least the early 1990s. However, an analysis of the extent of this improvement by type of leukemia is lacking. DATA AND METHODS: Data are from the Canadian Cancer Registry, with mortality follow-up through record linkage to the Canadian Vital Statistics Death Database. Increases in five-year relative survival ratios (RSRs) between 1992-to-1994 and 2006-to-2008 were calculated by age and sex for all leukemias combined and for each of the main types. RESULTS: Increases in five-year RSRs were significant for all leukemia types studied, ranging from 9.2 percentage units for acute myeloid leukemia (AML) to 24.9 percentage units for chronic myeloid leukemia (CML). For all leukemias combined, additional adjustment for case-mix reduced the increase in survival from 14.6 to 11.8 units; increases were significant among both sexes and each age group. Improvement in survival for chronic lymphocytic leukemia (CLL) was greater at older ages. For AML, improvements were greater among people younger than age 55; no significant change was detected among those diagnosed at ages 75 to 99. A significant survival advantage for women relative to men was apparent in the 2006-to-2008 period for all leukemias combined and for CLL and CML. INTERPRETATION: Despite recent significant gains in survival for each main type of leukemia, room remains for improvement.
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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 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".