The Prevalence of <i>CDKN2A</i> Germ-Line Mutations and Relative Risk for Cutaneous Malignant Melanoma: An International Population-Based Study
Bibliographic record
Abstract
Germ-line mutations of CDKN2A have been identified as strong risk factors for melanoma in studies of multiple-case families. However, an assessment of their relative risk for melanoma in the general population has been difficult because they occur infrequently. We addressed this issue using a novel population-based case-control study design in which "cases" have incident second- or higher-order melanomas [multiple primary melanoma (MPM)] and "controls" have incident first primary melanoma [single primary melanoma (SPM)]. Participants were ascertained from nine geographic regions in Australia, Canada, Italy, and United States. In the 1,189 MPM cases and 2,424 SPM controls who were eligible and available for analysis, the relative risk of a subsequent melanoma among patients with functional mutations who have an existing diagnosis of melanoma, after adjustments for age, sex, center, and known phenotypic risk factors, is estimated to be 4.3 (95% confidence interval, 2.3-7.7). The odds ratio varied significantly depending on the type of mutation involved. The results suggest that the relative risk of mutation carriers in the population may be lower than currently believed and that different mutations on the CDKN2A gene may confer substantially different risks of melanoma.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".