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

GenoMEL Study Group

Research output: Contribution to journalArticle

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 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.

Original languageEnglish
Pages (from-to)386-394
Number of pages9
JournalJournal of the American Academy of Dermatology
Volume81
Issue number2
DOIs
Publication statusPublished - Aug 1 2019

Fingerprint

Melanoma
Area Under Curve
Mutation
Pancreatic Neoplasms
Confidence Intervals
Germ-Line Mutation
Genetic Testing
Counseling
Cutaneous Malignant Melanoma
Population
Neoplasms

Keywords

  • CDKN2A
  • familial melanoma
  • GenoMEL
  • GenoMELPREDICT
  • mutation prediction

ASJC Scopus subject areas

  • Dermatology

Cite this

Estimating CDKN2A mutation carrier probability among global familial melanoma cases using GenoMELPREDICT. / GenoMEL Study Group.

In: Journal of the American Academy of Dermatology, Vol. 81, No. 2, 01.08.2019, p. 386-394.

Research output: Contribution to journalArticle

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title = "Estimating CDKN2A mutation carrier probability among global familial melanoma cases using GenoMELPREDICT",
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 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.",
keywords = "CDKN2A, familial melanoma, GenoMEL, GenoMELPREDICT, mutation prediction",
author = "{GenoMEL Study Group} and Taylor, {Nicholas J.} and Nandita Mitra and Lu Qian and Avril, {Marie Fran{\cc}oise} and Bishop, {D. Timothy} and {Bressac-de Paillerets}, Brigitte and William Bruno and Donato Calista and Francisco Cuellar and Cust, {Anne E.} and Florence Demenais and Elder, {David E.} and Gerdes, {Anne Marie} and P. Ghiorzo and Goldstein, {Alisa M.} and Grazziotin, {Thais C.} and Gruis, {Nelleke A.} and J. Hansson and Mark Harland and Hayward, {Nicholas K.} and M. Hocevar and Veronica H{\"o}iom and Holland, {Elizabeth A.} and Christian Ingvar and Landi, {Maria Teresa} and Gilles Landman and Alejandra Larre-Borges and Mann, {Graham J.} and Eduardo Nagore and H{\aa}kan Olsson and Palmer, {Jane M.} and Barbara Perić and Dace Pjanova and Pritchard, {Antonia L.} and Susana Puig and H. Schmid and {van der Stoep}, Nienke and Tucker, {Margaret A.} and Wadt, {Karin A.W.} and Yang, {Xiaohong R.} and Newton-Bishop, {Julia A.} and Kanetsky, {Peter A.}",
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T1 - Estimating CDKN2A mutation carrier probability among global familial melanoma cases using GenoMELPREDICT

AU - GenoMEL Study Group

AU - Taylor, Nicholas J.

AU - Mitra, Nandita

AU - Qian, Lu

AU - Avril, Marie Françoise

AU - Bishop, D. Timothy

AU - Bressac-de Paillerets, Brigitte

AU - Bruno, William

AU - Calista, Donato

AU - Cuellar, Francisco

AU - Cust, Anne E.

AU - Demenais, Florence

AU - Elder, David E.

AU - Gerdes, Anne Marie

AU - Ghiorzo, P.

AU - Goldstein, Alisa M.

AU - Grazziotin, Thais C.

AU - Gruis, Nelleke A.

AU - Hansson, J.

AU - Harland, Mark

AU - Hayward, Nicholas K.

AU - Hocevar, M.

AU - Höiom, Veronica

AU - Holland, Elizabeth A.

AU - Ingvar, Christian

AU - Landi, Maria Teresa

AU - Landman, Gilles

AU - Larre-Borges, Alejandra

AU - Mann, Graham J.

AU - Nagore, Eduardo

AU - Olsson, Håkan

AU - Palmer, Jane M.

AU - Perić, Barbara

AU - Pjanova, Dace

AU - Pritchard, Antonia L.

AU - Puig, Susana

AU - Schmid, H.

AU - van der Stoep, Nienke

AU - Tucker, Margaret A.

AU - Wadt, Karin A.W.

AU - Yang, Xiaohong R.

AU - Newton-Bishop, Julia A.

AU - Kanetsky, Peter A.

PY - 2019/8/1

Y1 - 2019/8/1

N2 - 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.

AB - 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.

KW - CDKN2A

KW - familial melanoma

KW - GenoMEL

KW - GenoMELPREDICT

KW - mutation prediction

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U2 - 10.1016/j.jaad.2019.01.079

DO - 10.1016/j.jaad.2019.01.079

M3 - Article

VL - 81

SP - 386

EP - 394

JO - Journal of the American Academy of Dermatology

JF - Journal of the American Academy of Dermatology

SN - 0190-9622

IS - 2

ER -