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We have previously shown that the functional melanoma risk variant rs12203592 in interferon regulatory factor-4 (IRF4) was associated with increased Breslow thickness, an important prognostic indicator for melanoma. In line with this, a recent study found evidence for an association between the minor T allele of this single nucleotide polymorphism (SNP) and melanoma-specific survival in patients from two European hospitals.

Background People at high risk of developing melanoma are usually identified by pigmentary and naevus phenotypes. Objective We examined whether associations of these phenotypes with melanoma risk differed by ambient sun exposure or participant characteristics in two population‐based, case–control studies with comparable ancestry but different ambient sun exposure. Methods Data were analysed from 616 cases and 496 controls from the Australian Melanoma Family Study and 2012 cases and 504 controls from the Leeds (UK) case–control study. Questionnaire, interview and dermatological skin examination data were collected using the same measurement protocols. Relative risks were estimated as odds ratios using unconditional logistic regression, adjusted for potential confounders. Results Hair and skin colour were the strongest pigmentary phenotype risk factors. All associations of pigmentary phenotype with melanoma risk were similar across countries. The median number of clinically assessed naevi was approximately three times higher in Australia than Leeds, but the relative risks for melanoma associated with each additional common or dysplastic naevus were higher for Leeds than Australia, especially for naevi on the upper and lower limbs. Higher naevus counts on the head and neck were associated with a stronger relative risk for melanoma for women than men. The two countries had similar relative risks for melanoma based on self‐reported naevus density categories, but personal perceptions of naevus number differed by country. There was no consistent evidence of interactions between phenotypes on risk. Conclusions Classifying people at high risk of melanoma based on their number of naevi should ideally take into account their country of residence, type of counts (clinical or self‐reported), body site on which the naevus counts are measured and sex. The presence of naevi may be a stronger indicator of a genetic predisposition in the UK than in Australia based on less opportunity for sun exposure to influence naevus development.

Background: Melanoma aetiology has been proposed to have two pathways, which are determined by naevi and type of sun exposure and related to the anatomical site where melanoma develops. Objectives: We examined associations with melanoma by anatomical site for a comprehensive set of risk factors including pigmentary and naevus phenotypes, ultraviolet radiation exposure and polygenic risk. Methods: We analysed harmonized data from 2617 people with incident first invasive melanoma and 975 healthy controls recruited through two population-based case–control studies in Australia and the UK. Questionnaire data were collected by interview using a single protocol, and pathway-specific polygenic risk scores were derived from DNA samples. We estimated adjusted odds ratios using unconditional logistic regression that compared melanoma cases at each anatomical site with all controls. Results: When cases were compared with control participants, there were stronger associations for many naevi vs. no naevi for melanomas on the trunk, and upper and lower limbs than on the head and neck (P-heterogeneity < 0·001). Very fair skin (vs. olive/brown skin) was more weakly related to melanoma on the trunk than to melanomas at other sites (P-heterogeneity = 0·04). There was no significant difference by anatomical site for polygenic risk. Increased weekday sun exposure was positively associated with melanoma on the head and neck but not on other sites. Conclusions: We found evidence of aetiological heterogeneity for melanoma, supporting the dual pathway hypothesis. These findings enhance understanding of risk factors for melanoma and can guide prevention and skin examination education and practices.

Background Guidelines for follow-up of patients with melanoma are based on limited evidence. Objectives To guide skin surveillance, we developed a risk prediction model for subsequent primary melanomas, using demographic, phenotypical, histopathological, sun exposure and genomic risk factors. Methods Using Cox regression frailty models, we analysed data for 2613 primary melanomas from 1266 patients recruited to the population-based Genes, Environment and Melanoma study in New South Wales, Australia, with a median of 14 years' follow-up via the cancer registry. Discrimination and calibration were assessed. Results The median time to diagnosis of a subsequent primary melanoma decreased with each new primary melanoma. The final model included 12 risk factors. Harrell's C-statistic was 0·73 [95% confidence interval (CI) 0·68-0·77], 0·65 (95% CI 0·62-0·68) and 0·65 (95% CI 0·61-0·69) for predicting second, third and fourth primary melanomas, respectively. The risk of a subsequent primary melanoma was 4·75 times higher (95% CI 3·87-5·82) for the highest vs. the lowest quintile of the risk score. The mean absolute risk of a subsequent primary melanoma within 5 years was 8·0 ± SD 4.1% after the first primary melanoma, and 46·8 ± 15·0% after the second, but varied substantially by risk score. Conclusions The risk of developing a subsequent primary melanoma varies considerably between individuals and is particularly high for those with two or more primary melanomas. The risk prediction model and its associated nomograms enable estimation of the absolute risk of subsequent primary melanoma, on the basis of on an individual's risk factors, and can be used to tailor surveillance intensity, communicate risk and provide patient education. What's already known about this topic? Current guidelines for the frequency and length of follow-up to detect new primary melanomas in patients with one or more previous primary melanomas are based on limited evidence. People with one or more primary melanomas have, on average, a higher risk of developing another primary invasive melanoma, compared with the general population, but an accurate way of estimating individual risk is needed. What does this study add? We provide a comprehensive risk prediction model for subsequent primary melanomas, using data from 1266 participants with melanoma (2613 primary melanomas), over a median 14 years' follow-up. The model includes 12 risk factors comprising demographic, phenotypical, histopathological and genomic factors, and sun exposure. It enables estimation of the absolute risk of subsequent primary melanomas, and can be used to tailor surveillance intensity, communicate individual risk and provide patient education.

Breslow thickness is considered to be the most important prognostic tumor feature in melanoma patients and is associated with age, sex, and phenotypic risk factors for melanoma such as number of nevi. However, its association with inherited genetic variants in recently identified melanoma risk loci is largely unknown. In a Western Australian Melanoma Health Study (WAMHS) study, published in the British Journal of Dermatology, IRF4 rs12203592, OCA2 rs1800401 and TP53 rs1042522 were significantly associated (P < 0.05) with Breslow thickness; however, these associations did not pass false discovery. This article is protected by copyright. All rights reserved.

The purpose of this study was to quantify the risk of cancers other than melanoma among family members of CDKN2A mutation carriers using data from the Genes, Environment and Melanoma study. Relative risks (RRs) of all non-melanoma cancers among first-degree relatives (FDRs) of melanoma patients with CDKN2A mutations (n = 65) and FDRs of melanoma patients without mutations (n = 3537) were calculated as the ratio of estimated event rates (number of cancers/total person-years) in FDRs of carriers vs noncarriers with exact Clopper–Pearson-type tests and 95% confidence intervals (CIs). All statistical tests were two-sided. There were 56 (13.1%) non-melanoma cancers reported among 429 FDRs of mutation carriers and 2199 (9.4%) non-melanoma cancers in 23 452 FDRs of noncarriers. The FDRs of carriers had an increased risk of any cancer other than melanoma (56 cancers among 429 FDRs of carrier probands vs 2199 cancers among 23 452 FDRs of noncarrier probands; RR = 1.5, 95% CI = 1.2 to 2.0, P = .005), gastrointestinal cancer (20 cancers among 429 FDRs of carrier probands vs 506 cancers among 23 452 FDRs of noncarrier probands; RR = 2.4, 95% CI = 1.4 to 3.7, P = .001), and pancreatic cancer (five cancers among 429 FDRs of carrier probands vs 41 cancers among 23 452 FDRs of noncarrier probands; RR = 7.4, 95% CI = 2.3 to 18.7, P = .002). Wilms tumor was reported in two FDRs of carrier probands and three FDRs of noncarrier probands (RR = 40.4, 95% CI = 3.4 to 352.7, P = .005). The lifetime risk of any cancer other than melanoma among CDKN2A mutation carriers was estimated as 59.0% by age 85 years (95% CI = 39.0% to 75.4%) by the kin-cohort method, under the standard assumptions of Mendelian genetics on the genotype distribution of FDRs conditional on proband genotype.