Trends in Cutaneous Melanoma in Nova Scotia With a Focus on 2007 to 2019
Bibliographic record
Abstract
BACKGROUND: Melanoma represents a significant public health challenge in Canada, contributing to the deaths of over 1000 individuals each year. Prince Edward Island and Nova Scotia were previously noted to have the highest incidence rates of melanoma in Canada. METHODS: Data from patients diagnosed with or dying from melanoma was extracted from the Nova Scotia Cancer Registry. TNM stage was available for cases diagnosed 2007 to 2017. Incidence (1992-2019) and mortality (1992-2021) rates were examined using Join Point Trend Analysis Software. RESULTS: Between 2007 and 2019, 2450 cases of in situ and 4063 cases of invasive melanoma were documented, of which 52.8% were male. The largest number of cases was from the 60- to 79-year age group. The most common site in females was upper limbs (in situ) and lower limbs (invasive), and for males, face, and neck (in situ), and trunk (invasive). The majority of invasive cases (71.5%) were diagnosed at stage I. Invasive melanoma incidence has been increasing by 2.7% per year since 1992, while in situ disease has increased at a greater rate (4.9% per year). The current estimate of 92% for 5 years of net survival has not changed appreciably over the same period. Survival for late-stage melanoma has shown a modest improvement for patients diagnosed over the period. CONCLUSION: With increasing rates of melanoma in Nova Scotia, there is a need for informed education, directed at the public and physicians, around pigmented skin lesions. This would allow the patient to detect atypical melanocytic lesions at an early stage. Sun safety practices in Nova Scotia should continue to be encouraged.
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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 | 0.001 |
| Bibliometrics | 0.003 | 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) | 0.003 | 0.001 |
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".