Heterogeneity of risk for melanoma and pancreatic and digestive malignancies
Bibliographic record
Abstract
BACKGROUND: Data addressing the interfamilial heterogeneity of melanoma are limited. In the current study, the authors assessed melanoma risk according to family history of melanoma and other melanoma-associated malignancies and evaluated the familial heterogeneity of melanomas, pancreatic malignancies, and gastrointestinal malignancies. METHODS: The authors obtained patient histories of malignancy in first-degree relatives as part of a clinic-based case-control study. The case group included 737 newly diagnosed patients with invasive melanoma, and the control group included 1021 outpatients from clinics at the same medical centers. To assess heterogeneity of risk among families affected by melanoma, a nonparametric method was used to detect extrabinomial variation. In addition, selected patients with melanoma (n=133) were tested for germline mutations in CDKN2A. RESULTS: The adjusted odds ratio associated with a family history of melanoma was 1.7 (95% confidence interval, 1.1-2.7). Family histories of pancreatic, gastrointestinal, brain, breast, or lymphoproliferative disease did not increase the risk of melanoma significantly. Among case families, significant evidence of familial heterogeneity was found for melanomas, but not for pancreatic or gastrointestinal malignancies. Two mutations in CDKN2A previously associated with melanoma risk were identified among the 133 patients tested in the case group; mutation detection did not differ between families with low and high heterogeneity scores. CONCLUSIONS: Familial heterogeneity testing in the study population did not improve the selection of high-risk families for genetic study. Even in a large case-control study, few families that had multiple members with melanoma were identified, and family members with pancreatic malignancies were rare.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".