Development and Validation of a Melanoma Risk Score Based on PooledData from 16 Case – Control Studies

Background: We report the development of a cutaneous melanoma risk algorithm based upon seven factors; hair color, skin type, family history, freckling, nevus count, number of large nevi, and history of sunburn, intended to form the basis of a selfassessment Web tool for the general public. Methods: Predicted odds of melanoma were estimated by analyzing a pooled dataset from 16 case–control studies using logistic random coefficients models. Risk categories were defined based on the distribution of the predicted odds in the controls from these studies. Imputation was used to estimate missing data in the pooled datasets. The 30th, 60th, and 90th centiles were used to distribute individuals into four risk groups for their age, sex, and geographic location. Crossvalidation was used to test the robustness of the thresholds for each group by leaving out each study one by one. Performance of the model was assessed in an independent UK case–control study dataset. Results: Cross-validation confirmed the robustness of the threshold estimates. Cases and controls were well discriminated in the independent dataset [area under the curve, 0.75; 95% confidence interval (CI), 0.73–0.78]. Twenty-nine percent of cases were in the highest risk group compared with 7% of controls, and 43%of controls were in the lowest risk group comparedwith 13% of cases. Conclusion:Wehave identified a composite score representing an estimate of relative risk and successfully validated this score in an independent dataset. Impact: This score may be a useful tool to inform members of the public about their melanoma risk. Cancer Epidemiol Biomarkers Prev; 24(5); 1–8. 2015 AACR. Section of Epidemiology and Biostatistics, Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, United Kingdom. Sax Institute andSydneySchool of PublicHealth,TheUniversityof Sydney, Sydney, Australia. Twin Research and Genetic Epidemiology Unit, St. Thomas' Campus, Kings College London, London, United Kingdom. Dermatology Department,West Herts NHS Trust, Hemel Hempstead General Hospital, Herts, United Kingdom. Department of Dermatology, Leiden University Medical Centre, Leiden, the Netherlands. Department of Internal Medicine, University of New Mexico, Albuquerque, New Mexico. Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California. Department of Epidemiology and Biostatistics, School of Population Health, University of Auckland, Auckland, New Zealand. Department of Medicine, Geisel School of Medicine and the Norris Cotton Cancer Center, Dartmouth University, Lebanon, New Hampshire. Queensland Institute of Medical Research, PO Royal Brisbane Hospital, Brisbane, Australia. Department of Surgery, University Hospital, Lund, Sweden. Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida. Department of Community and Family Medicine, Geisel School of Medicine at Dartmouth, Norris Cotton Cancer Center, Lebanon, NewHampshire. B.C. Cancer Research Centre,Vancouver, British Columbia, Canada. University of Hawaii Cancer Center, Honolulu, Hawaii. Department of Public Health and Health Policy, University of Glasgow, Glasgow, United Kingdom. Department of Oncology, University Hospital, Lund, Sweden. Kobenhaausevej 35, Hillerød, Denmark. Department of Biostatistics and Epidemiology and Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, Pennsylvania. DermatologikumHamburg,Hamburg,Germany. Wolfson Institute of Preventive Medicine, Barts & The London School of Medicine, London, United Kingdom. Division of Genetics and Epidemiology, Institute of Cancer Research, London, United Kingdom. Division of Breast Cancer Research, Institute of Cancer Research, London, United Kingdom. Institute of Medical Biometry and Statistics, University of L€ ubeck, University Hospital Schleswig-Holstein,Campus L€ ubeck,Germany. Center for Clinical Trials, University of L€ ubeck, L€ ubeck, Germany. Note: Supplementary data for this article are available at Cancer Epidemiology, Biomarkers & Prevention Online (http://cebp.aacrjournals.org/). Current address for Marc S. Ernstoff: Taussig Cancer Institute R-35, Cleveland Clinic Foundation, 9500 Euclid Avenue, Cleveland, Ohio. Corresponding Author: John R. Davies, Section of Epidemiology and Biostatistics, Leeds Institute of Cancer and Pathology, Cancer Genetics Building, St James's Hospital, Beckett Street, Leeds LS9 7TF, United Kingdom. Phone: 44113-2066970; Fax: 44-113-2340183; E-mail: J.R. Davies@leeds.ac. uk doi: 10.1158/1055-9965.EPI-14-1062 2015 American Association for Cancer Research. Cancer Epidemiology, Biomarkers & Prevention www.aacrjournals. org OF1 on April 12, 2017. © 2015 American Association for Cancer Research. cebp.aacrjournals. org Downloaded from Published OnlineFirst February 24, 2015; DOI: 10.1158/1055-9965.EPI-14-1062