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J Am Acad Dermatol. 2019 Aug;81(2):386-394. doi: 10.1016/j.jaad.2019.01.079. Epub 2019 Feb 5.

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

Author information

1
Department of Epidemiology and Biostatistics, Texas A&M University, College Station, Texas.
2
Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, Pennsylvania.
3
Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida.
4
Assistance Publique-Hôpitaux de Paris, Hôpital Cochin et Université Paris Descartes, Paris, France.
5
Section of Epidemiology and Biostatistics, Leeds Institute of Medical Research at St. James's, University of Leeds, Leeds, United Kingdom.
6
Gustave Roussy, Université Paris-Saclay, Département de Biopathologie and Institut National de la Santé et de la Recherche Médicale U1186, Villejuif, France.
7
Department of Internal Medicine and Medical Specialties, University of Genoa and Istituto de Ricovero e Cura a Carattere Scientifico AOU San Martino-IST, Genoa, Italy.
8
Dermatology Unit, Maurizio Bufalini Hospital, Cesena, Italy.
9
Melanoma Unit, Dermatology Department, Hospital Clinic Barcelona, Institut de Investigacions Biomediques August Pi Sunyer, Universitat de Barcelona, Barcelona, Spain.
10
Sydney School of Public Health, The University of Sydney, Sydney, Australia; Melanoma Institute Australia, The University of Sydney, Sydney, Australia.
11
Institut National de la Santé et de la Recherche Médicale UMR-946, Genetic Variation and Human Disease Unit, Université Paris Diderot, Paris, France.
12
Department of Pathology and Laboratory Medicine, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania.
13
Department of Clinical Genetics, University Hospital of Copenhagen, Copenhagen, Denmark.
14
Human Genetics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland.
15
Pontifícia Universidade Católica do Rio Grande do Sul, Porto Alegre, Brazil.
16
Department of Dermatology, Leiden University Medical Centre, Leiden, the Netherlands.
17
Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden.
18
QIMR Berghofer Medical Research Institute, Herston, Australia.
19
Institute of Oncology Ljubljana, Zaloska, Ljubljana, Slovenia.
20
Melanoma Institute Australia, The University of Sydney, Sydney, Australia; Westmead Institute for Medical Research, University of Sydney, Sydney, Australia.
21
Department of Clinical Sciences, Lund University Hospital Lund, Sweden; Department of Surgery, Lund University Hospital, Lund, Sweden.
22
Department of Pathology, Escola Paulista de Medicina, Universidade Federal de São Paulo, São Paulo, Brazil.
23
Unidad de Lesiones Pigmentadas, Cátedra de Dermatología, Hospital de Clínicas, Universidad de la República, Montevideo, Uruguay.
24
Department of Dermatology, Instituto Valenciano de Oncologia, Valencia, Spain.
25
Latvian Biomedical Research and Study Centre, Riga, Latvia.
26
Melanoma Unit, Dermatology Department, Hospital Clinic Barcelona, Institut de Investigacions Biomediques August Pi Sunyer, Universitat de Barcelona, Barcelona, Spain; Centro de Investigacion Biomedica en Red de Enfermedades Raras, Instituto de Salud Carlos III, Barcelona, Spain.
27
Department of Clinical Genetics, Leiden University Medical Center Leiden, the Netherlands.
28
Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida. Electronic address: peter.kanetsky@moffitt.org.

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; GenoMEL; GenoMELPREDICT; familial melanoma; mutation prediction

PMID:
30731170
PMCID:
PMC6634996
[Available on 2020-08-01]
DOI:
10.1016/j.jaad.2019.01.079

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