Publication date: Available online 5 February 2019
Source: Journal of the American Academy of Dermatology
Author(s): Nicholas J. Taylor, Nandita Mitra, Lu Qian, Marie-Françoise Avril, D. Timothy Bishop, Brigitte Bressac-de Paillerets, William Bruno, Donato Calista, Francisco Cuellar, Anne E. Cust, Florence Demenais, David E. Elder, Anne-Marie Gerdes, Paola Ghiorzo, Alisa M. Goldstein, Thais C. Grazziotin, Nelleke A. Gruis, Johan Hansson, Mark Harland, Nicholas K. Hayward
Abstract
Background
Although rare in the general population, highly penetrant germline mutations in CDKN2A are responsible for 5-40% of melanoma cases reported in melanoma-prone families. We sought to determine whether MELPREDICT was generalizable to a global series of melanoma families and whether performance improvements can be achieved.
Methods
2,116 familial melanoma cases were ascertained by the international GenoMEL Consortium. We recapitulated the MELPREDICT model within our data (GenoMELPREDICT) to assess performance improvements by adding phenotypic risk factors and history of pancreatic cancer. We report areas under the curve (AUC) with 95% confidence intervals (CI) along with net reclassification indices (NRI) as performance metrics.
Results
MELPREDICT performed well (AUC=0.752; 95%CI: 0.730, 0.775), and GenoMELPREDICT performance was similar (AUC=0.748; 95% CI: 0.726, 0.771). Adding a reported history of pancreatic cancer yielded discriminatory improvement (p<0.0001) in GenoMELPREDICT (AUC=0.772; 95%CI: 0.750, 0.793; NRI=0.40). Including phenotypic risk factors did not improve performance.
Conclusion
The MELPREDICT model functioned well in a global dataset of familial melanoma cases. Adding pancreatic cancer history improved model prediction. GenoMELPREDICT is a simple tool for predicting CDKN2A mutational status among melanoma patients from melanoma-prone families and can aid in counselling these patients towards genetic testing or cancer risk counselling.
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