Incidence of chronic myeloid leukemia in Calgary, Alberta, Canada
Bibliographic record
Abstract
OBJECTIVE: The epidemiology of chronic myeloid leukemia is shifting due to the aging global population and the recent discovery and availability of targeted treatment options. This study provides recent data regarding the incidence of CML in Calgary, a major Canadian city. Data from patients diagnosed with CML by bone marrow sample analysis from 2011 to 2015 were collected from the database of the sole centralized cytogenetics facility in service of Calgary and its surrounding area. RESULTS: With an average of 10.2 newly diagnosed cases per year in Calgary from 2011 to 2015, the incidence rate was calculated to be 0.75 cases per 100,000 person-years (95% CI 0.57-0.99). With age standardization, the incidence was 0.87 cases per 100,000 person-years (95% CI 0.82-0.91) for the Canadian population, which was low compared to other developed Western nations. The highest incidence rates were observed in the older patient categories, however there was a broad age distribution for incident cases and the median age at diagnosis was 48. There was a general male bias for CML most pronounced at the younger ages. Our description of CML incidence will help to inform healthcare planners amidst the dramatically altered treatment of this hematological neoplasm.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 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) | 0.003 | 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".