Sex differences in melanoma survival—a GEM study
Bibliographic record
Abstract
Sex differences in melanoma are prominent, with female having a significant survival advantage. However, it is unclear why we see this survival advantage. Here, we investigate the relationship between sex, clinicopathologic variables, and melanoma specific survival in 1753 single primary melanomas from patients in the GEM (Genes, Environment, and Melanoma) study. Using Cox proportional hazard models and formal mediation analysis, the effect of sex on survival is explained largely by differences in the clinicopathologic features of tumors at diagnosis. Specifically, we find evidence that 86.5% of the effect of sex on melanoma survival is mediated by differences in age at diagnosis, Breslow thickness, ulceration, mitoses, and site (hazard ratio [HR] = 1.85, P < .001). This analysis indicates that the female survival advantage in melanoma is not primarily due to a direct effect of sex (HR = 1.19, P = .42) but is largely a result of an indirect effect of sex mediated by clinicopathologic features.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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 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".