Abstract 2244: The M-SKIP Project: an international pooled-analysis on melanocortin-1 receptor (MC1 R) variants and skin carcinogenesis
Bibliographic record
Abstract
Abstract Background: MC1R is one of the major genes involved in the determinism of skin pigmentation. The role of MC1R variants in skin carcinogenesis was previously investigated by a meta-analysis of 18 published studies. Although the results were informative, published data were not enough to deeply investigate the specific contribution of each MC1R variant on skin cancer development. Aim: The M-SKIP Project aims to perform an international collaborative pooled-analysis on the role of MC1R variants in skin carcinogenesis, using individual patient data. The main endpoint is skin cancer. Secondary endpoints are phenotypic characteristics involved in skin carcinogenesis, e.g. freckling. Methods and Patients: An Advisory Committee of investigators with great expertise in melanoma and genetic research was established. The authors of appropriate papers were invited to provide their original published and unpublished data. Preliminary results: Up to February 2010, 27 out of 35 contacted investigators (77%) agreed to join the M-SKIP Project. Thanks to the positive response obtained up to now, we estimate to receive data on around 6,500 melanoma cases, 1,500 non-melanoma skin cancer cases and 13,000 controls. So far, we have already received data on 2,683 melanoma cases, 1,364 non-melanoma skin cancer cases and 4,340 controls from 15 investigators internationally. After quality controls, data are inserted in a central database, and pooled-analysis will be performed in order to evaluate: (1) the association between MC1R variants and skin cancer overall, and by skin cancer type; (2) the association between MC1R variants and phenotypic characteristics under study; (3) MC1R-phenotype interaction in skin cancer risk. In addition, stratified analysis will be performed to understand the independent and dependent role of MC1R variants in skin cancer development by phenotypic characteristics. Conclusion: The pooled analysis approach applied in such a setting is particularly useful because it will help reaching firm conclusions even in sub-group and interaction analyses, controlling for important confounders. This data-bank will represent a reference and guide for all investigators working in this research field. Collaboration within investigators would significantly improve the knowledge and accelerate our understanding of the role of MC1R variants in skin carcinogenesis. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 2244. doi:10.1158/1538-7445.AM2011-2244
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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 | 0.048 | 0.071 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.015 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".