Uveal melanoma incidence trends in Canada: a national comprehensive population-based study
Bibliographic record
Abstract
BACKGROUND: In the developed countries, uveal melanoma is the most common primary intraocular malignancy in adults. Little is known about the epidemiological and geographical distribution of uveal melanoma in Canada. METHODS: To determine the incidence patterns and geographical distribution of uveal melanoma cases in Canada, we conducted the first comprehensive, population-based national study of this malignancy across all Canadian provinces and territories during 1992-2010 years. We examined two independent population-based registries: the Canadian Cancer Registry and Le Registre Québécois du Cancer using corresponding International Classification of Diseases for Oncology-3rd edition codes for all histological subtypes of uveal melanoma. RESULTS: We report that 2215 patients were diagnosed with uveal melanoma, of which 52.1% were males. The average -annual incidence rate of uveal melanoma in Canada was 3.75 cases per million individuals per year (95% CI 3.60 to 3.91). Overall, we report a steady increase in uveal melanoma incidence with an annual increase of 0.074 cases per million individuals per year. Significant differences in the incidence rates of uveal melanoma between Canadian provinces and territories were noted, where the highest crude incidence was in British Columbia and Saskatchewan with rates of 6.38 and 5.47 cases per million individuals per year, respectively. CONCLUSIONS: This work, for the first time, defines the disease burden of uveal melanoma in Canada and highlights important longitudinal, geographical and spatial differences in the distribution of uveal melanoma in Canada.
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 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) | 0.000 | 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) | 0.001 | 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 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".