Malignant primary brain and other central nervous system tumors diagnosed in Canada from 2009 to 2013
Bibliographic record
Abstract
BACKGROUND: We present a national surveillance report on malignant primary brain and other central nervous system (CNS) tumors diagnosed in the Canadian population in 2009-2013. METHODS: Patients were identified through the Canadian Cancer Registry, an administrative dataset that includes cancer incidence data from all provinces/territories in Canada. Tumor types were classified by site and histology using the definitions from the Central Brain Tumor Registry of the United States (CBTRUS). Incidence rates (IRs) and 95% confidence intervals (CIs) were calculated per 100000 person-years (py) and age-standardized to the 2011 Canadian population for comparisons within Canada and to the 2000 United States population for comparisons with the US. RESULTS: Overall, 12515 malignant brain and other CNS tumors were diagnosed in the Canadian population in 2009-2013 (IR: 8.71/100000 py; 95% CI: 8.56, 8.86); 7085 were among males (IR: 10.06/100000 py; 95% CI: 9.82, 10.29) and 5430 among females (IR: 7.41/100000 py; 95% CI: 7.22, 7.61). Of these, 12115 were classifiable according to histological subgroups defined by CBTRUS. The most common histology was glioblastoma (IR: 4.06/100000 py; 95% CI: 3.95, 4.16). Among those aged 0-19 years, 1130 malignant brain and CNS tumors were diagnosed in 2009-2013 (IR: 3.36/100000 py; 95% CI: 3.16, 3.56). The most common histology among the pediatric population was embryonal tumor (IR: 0.74/100000 py; 95% CI: 0.65, 0.84). CONCLUSIONS: These data represent an initial detailed report on the frequency and distribution of primary malignant brain and other CNS tumors diagnosed in the Canadian population in 2009-2013. The reported distributions of tumor diagnoses by sex and age reflected expected patterns based on the literature from similar populations. A report incorporating data on nonmalignant primary brain tumors is forthcoming.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".