ArticleBMC cancer2013
MC1R genotype as a predictor of early-onset melanoma, compared with self-reported and physician-measured traditional risk factors: an Australian case-control-family study.
Article in BMC cancer, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 2 of them syntheses that pooled it.
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Who cites it
17 citing papers in PubMed, 2 syntheses or guidelines pooled it, 34 citations in OpenAlex.
- Risk Prediction Models for Melanoma: A Systematic Review on the Heterogeneity in Model Development and Validation.International journal of environmental research and public health · 2020Pooled it
- Updated field synopsis and systematic meta-analyses of genetic association studies in cutaneous melanoma: the MelGene database.The Journal of investigative dermatology · 2015Pooled it
- Unique Features of Melanoma Risk and Diagnosis in Red-Haired Populations.International journal of molecular sciences · 2026Review
- The Level of Agreement between Self-Assessments and Examiner Assessments of Melanocytic Nevus Counts: Findings from an Evaluation of 4548 Double Assessments.Current oncology (Toronto, Ont.) · 2024Article
- Inter-Rater Agreement in Assessing Risk of Bias in Melanoma Prediction Studies Using the Prediction Model Risk of Bias Assessment Tool (PROBAST): Results from a Controlled Experiment on the Effect of Specific Rater Training.Journal of clinical medicine · 2023Article
- Using the Prediction Model Risk of Bias Assessment Tool (PROBAST) to Evaluate Melanoma Prediction Studies.Cancers · 2022Article
- Reporting Quality of Studies Developing and Validating Melanoma Prediction Models: An Assessment Based on the TRIPOD Statement.Healthcare (Basel, Switzerland) · 2022Article
- Development and external validation study of a melanoma risk prediction model incorporating clinically assessed naevi and solar lentigines.The British journal of dermatology · 2020Article
- Assessing the Incremental Contribution of Common Genomic Variants to Melanoma Risk Prediction in Two Population-Based Studies.The Journal of investigative dermatology · 2018Article
- Sunscreen Use and Melanoma Risk Among Young Australian Adults.JAMA dermatology · 2018Article
- Article
- Emerging concepts and recent advances in basal cell carcinoma.F1000Research · 2017Review
- No prognostic value added by vitamin D pathway SNPs to current prognostic system for melanoma survival.PloS one · 2017Article
- Public preferences for communicating personal genomic risk information: a focus group study.Health expectations : an international journal of public participation in health care and health policy · 2016Article
- Indoor tanning and the MC1R genotype: risk prediction for basal cell carcinoma risk in young people.American journal of epidemiology · 2015Article
- Clinical applications of melanoma genetics.Current treatment options in oncology · 2014Review
- Article
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Authors and funding
17 authors at 7 institutions in 2 countries.
Funding
Abstract
backgroundMelanocortin-1 receptor (MC1R) gene variants are very common and are associated with melanoma risk, but their contribution to melanoma risk prediction compared with traditional risk factors is unknown. We aimed to 1) evaluate the separate and incremental contribution of MC1R genotype to prediction of early-onset melanoma, and compare this with the contributions of physician-measured and self-reported traditional risk factors, and 2) develop risk prediction models that include MC1R, and externally validate these models using an independent dataset from a genetically similar melanoma population.
methodsUsing data from an Australian population-based, case-control-family study, we included 413 case and 263 control participants with sequenced MC1R genotype, clinical skin examination and detailed questionnaire. We used unconditional logistic regression to estimate predicted probabilities of melanoma. Results were externally validated using data from a similar study in England.
resultsWhen added to a base multivariate model containing only demographic factors, MC1R genotype improved the area under the receiver operating characteristic curve (AUC) by 6% (from 0.67 to 0.73; P < 0.001) and improved the quartile classification by a net 26% of participants. In a more extensive multivariate model, the factors that contributed significantly to the AUC were MC1R genotype, number of nevi and previous non-melanoma skin cancer; the AUC was 0.78 (95% CI 0.75-0.82) for the model with self-reported nevi and 0.83 (95% CI 0.80-0.86) for the model with physician-counted nevi. Factors that did not further contribute were sun and sunbed exposure and pigmentation characteristics. Adding MC1R to a model containing pigmentation characteristics and other self-reported risk factors increased the AUC by 2.1% (P = 0.01) and improved the quartile classification by a net 10% (95% CI 1-18%, P = 0.03).
conclusionsAlthough MC1R genotype is strongly associated with skin and hair phenotype, it was a better predictor of early-onset melanoma than was pigmentation characteristics. Physician-measured nevi and previous non-melanoma skin cancer were also strong predictors. There might be modest benefit to measuring MC1R genotype for risk prediction even if information about traditional self-reported or clinically measured pigmentation characteristics and nevi is already available.
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