Estimating CDKN2A mutation carrier probability among global familial melanoma cases using GenoMELPREDICT

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

  • 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
  • Gerdes, Anne-Marie Axø
  • P. Ghiorzo
  • Alisa M. Goldstein
  • Thais C. Grazziotin
  • Nelleke A. Gruis
  • J. Hansson
  • Mark Harland
  • Nicholas K. Hayward
  • M. Hocevar
  • Veronica Höiom
  • Elizabeth A. Holland
  • Christian Ingvar
  • Maria Teresa Landi
  • Gilles Landman
  • Alejandra Larre-Borges
  • Graham J. Mann
  • Eduardo Nagore
  • Håkan Olsson
  • Jane M. Palmer
  • Barbara Perić
  • Dace Pjanova
  • Antonia L. Pritchard
  • Susana Puig
  • H. Schmid
  • Nienke van der Stoep
  • Margaret A. Tucker
  • Wadt, Karin Anna Wallentin
  • Xiaohong R. Yang
  • Julia A. Newton-Bishop
  • Peter A. Kanetsky
  • GenoMEL Study Group

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.

OriginalsprogEngelsk
TidsskriftJournal of the American Academy of Dermatology
Vol/bind81
Udgave nummer2
Sider (fra-til)386-394
ISSN0190-9622
DOI
StatusUdgivet - aug. 2019

ID: 240197061