<i>MC1R</i> variants increased the risk of sporadic cutaneous melanoma in darker‐pigmented <scp>C</scp>aucasians: A pooled‐analysis from the M‐SKIP project
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Bibliographic record
Abstract
The MC1R gene is a key regulator of skin pigmentation. We aimed to evaluate the association between MC1R variants and the risk of sporadic cutaneous melanoma (CM) within the M-SKIP project, an international pooled-analysis on MC1R, skin cancer and phenotypic characteristics. Data included 5,160 cases and 12,119 controls from 17 studies. We calculated a summary odds ratio (SOR) for the association of each of the nine most studied MC1R variants and of variants combined with CM by using random-effects models. Stratified analysis by phenotypic characteristics were also performed. Melanoma risk increased with presence of any of the main MC1R variants: the SOR for each variant ranged from 1.47 (95%CI: 1.17-1.84) for V60L to 2.74 (1.53-4.89) for D84E. Carriers of any MC1R variant had a 66% higher risk of developing melanoma compared with wild-type subjects (SOR; 95%CI: 1.66; 1.41-1.96) and the risk attributable to MC1R variants was 28%. When taking into account phenotypic characteristics, we found that MC1R-associated melanoma risk increased only for darker-pigmented Caucasians: SOR (95%CI) was 3.14 (2.06-4.80) for subjects with no freckles, no red hair and skin Type III/IV. Our study documents the important role of all the main MC1R variants in sporadic CM and suggests that they have a direct effect on melanoma risk, independently on the phenotypic characteristics of carriers. This is of particular importance for assessing preventive strategies, which may be directed to darker-pigmented Caucasians with MC1R variants as well as to lightly pigmented, fair-skinned subjects.
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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 | 0.001 | 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 | 0.001 | 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 it