Geographic Variations in Cutaneous Melanoma Distribution in the Russian Federation
Bibliographic record
Abstract
BACKGROUND: Cutaneous melanoma (CM) incidence has been increasing around the world. The goal of this study is to describe geographic trends in incidence and mortality of CM in Russia between 2001 and 2017. METHODS: To achieve this we used geo-informatic technique (mapping) and descriptive statistical analysis. Additionally, we studied the associations between ethnicity, geographic latitude/longitude, and CM incidence/mortality rates. We retrospectively analyzed the data from the Moscow Oncology Research Institute, Ministry of Health of the Russian Federation, for the period of the study. Routine methods of descriptive epidemiology were used to study incidence and mortality rates by age groups, years, and jurisdictions (i.e., Federal Districts and Federal Subjects of Russia). RESULTS: In total, 141,597 patients were diagnosed with melanoma in Russia over the period 2001-2017, of whom 62% were women. The overall age-standardized incidence and mortality rates were 4.27/100,000 and 1.62/100,000, respectively. Geographic mapping revealed north-to-south and east-to-west gradients. As the study was fully descriptive, retrospective, and based on official statistical reports, detailed characteristics of clinical forms, anatomic sites, Breslow depth, and treatments could not be analyzed. CONCLUSIONS: This study outlined the burden of melanoma in the Russian Federation, and the trends were similar to those observed in countries with similar latitudes and skin phenotype. The importance of the skin color gradient and recreational/cultural practices were some of the most important risk factors highlighted in this study for the development of melanoma in Russia.
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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) | 0.000 | 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) | 0.000 | 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".