PURPOSE: Incidence and mortality of cutaneous melanoma is rising rapidly in the United States; therefore, identifying risk factors for melanoma and integrating them into a clinical and population risk estimation tool may help guide prevention efforts and identify participants for preventive interventions. METHODS: We examined risk factors for melanoma in three large prospective studies of women and men. We observed 152,949 women and 25,206 men free of cancer at baseline for up to 14 years. RESULTS: A total of 535 incident cases of invasive melanoma (444 women and 91 men) were included in the analysis. We combined the three studies to examine risk factors and to build a risk model to calculate melanoma risk score. Older age, male sex, family history of melanoma, higher number of nevi, history of severe sunburn, and light hair color were each associated with significantly elevated risk of melanoma and were included in the final risk prediction. Participants at the highest decile of risk had a more than three-fold increase in risk of melanoma compared with those in the lowest decile (observed relative risk, 3.61; expected relative risk, 4.20). The measure of discriminatory accuracy as summarized by an age-and sex-adjusted concordance statistic of 0.62 (95% CI, 0.58 to 0.65) indicated that the model had reasonable ability to differentiate those who will develop melanoma and those who will remain free from the disease. CONCLUSION: We identified several risk factors for melanoma and developed statistical models with adequate performance and discriminatory accuracy.
PURPOSE: Incidence and mortality of cutaneous melanoma is rising rapidly in the United States; therefore, identifying risk factors for melanoma and integrating them into a clinical and population risk estimation tool may help guide prevention efforts and identify participants for preventive interventions. METHODS: We examined risk factors for melanoma in three large prospective studies of women and men. We observed 152,949 women and 25,206 men free of cancer at baseline for up to 14 years. RESULTS: A total of 535 incident cases of invasive melanoma (444 women and 91 men) were included in the analysis. We combined the three studies to examine risk factors and to build a risk model to calculate melanoma risk score. Older age, male sex, family history of melanoma, higher number of nevi, history of severe sunburn, and light hair color were each associated with significantly elevated risk of melanoma and were included in the final risk prediction. Participants at the highest decile of risk had a more than three-fold increase in risk of melanoma compared with those in the lowest decile (observed relative risk, 3.61; expected relative risk, 4.20). The measure of discriminatory accuracy as summarized by an age-and sex-adjusted concordance statistic of 0.62 (95% CI, 0.58 to 0.65) indicated that the model had reasonable ability to differentiate those who will develop melanoma and those who will remain free from the disease. CONCLUSION: We identified several risk factors for melanoma and developed statistical models with adequate performance and discriminatory accuracy.
Authors: Peter A Kanetsky; Saarene Panossian; David E Elder; DuPont Guerry; Michael E Ming; Lynn Schuchter; Timothy R Rebbeck Journal: Cancer Date: 2010-05-15 Impact factor: 6.860
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Authors: Sang Min Park; Tricia Li; Shaowei Wu; Wen-Qing Li; Martin Weinstock; Abrar A Qureshi; Eunyoung Cho Journal: Int J Cancer Date: 2017-02-14 Impact factor: 7.396
Authors: Rajesh Talluri; Anna V Wilkinson; Margaret R Spitz; Sanjay Shete Journal: Cancer Epidemiol Biomarkers Prev Date: 2014-07-25 Impact factor: 4.254