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 families with melanoma and whether performance improvements can be achieved. METHODS In total, 2116 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 (CIs) along with net reclassification indices (NRIs) 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 < .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 data set 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 directing these patients to receive genetic testing or cancer risk counseling.

中文翻译：

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使用GenoMELPREDICT估算全球家族性黑色素瘤病例中CDKN2A突变携带者的可能性。

背景技术尽管在普通人群中很少见，但CDKN2A中的高渗透性生殖系突变占易发黑色素瘤家族中报告的黑色素瘤病例的5％-40％。我们试图确定MELPREDICT是否可以推广到全球范围内的一系列黑色素瘤家庭，以及是否可以提高性能。方法国际GenoMEL联合会确定了2116例家族性黑色素瘤病例。我们在数据（GenoMELPREDICT）中总结了MELPREDICT模型，以通过添加表型风险因素和胰腺癌病史来评估性能改善。我们以95％的置信区间（CI）报告曲线下的区域（AUC）以及净重分类指数（NRI）作为绩效指标。结果MELPREDICT表现良好（AUC 0.752，95％CI 0.730-0.775），和GenoMELPREDICT性能相似（AUC 0.748，95％CI 0.726-0.771）。添加已报道的胰腺癌病史在GenoMELPREDICT（AUC 0.772，95％CI 0.750-0.793，NRI 0.40）中产生了歧视性改善（P <.0001）。包括表型危险因素并没有改善表现。结论MELPREDICT模型在家族性黑色素瘤病例的全球数据集中运行良好。添加胰腺癌病史改善了模型预测。GenoMELPREDICT是一种用于在易发黑素瘤家族的黑素瘤患者中预测CDKN2A突变状态的简单工具，可帮助指导这些患者接受基因检测或癌症风险咨询。750-0.793，NRI 0.40）。包括表型危险因素并没有改善表现。结论MELPREDICT模型在家族性黑色素瘤病例的全球数据集中运行良好。添加胰腺癌病史改善了模型预测。GenoMELPREDICT是一种用于在易发黑素瘤家族的黑素瘤患者中预测CDKN2A突变状态的简单工具，可帮助指导这些患者接受基因检测或癌症风险咨询。750-0.793，NRI 0.40）。包括表型危险因素并没有改善表现。结论MELPREDICT模型在家族性黑色素瘤病例的全球数据集中运行良好。添加胰腺癌病史改善了模型预测。GenoMELPREDICT是一种用于在易发黑素瘤家族的黑素瘤患者中预测CDKN2A突变状态的简单工具，可帮助指导这些患者接受基因检测或癌症风险咨询。