Journal
FAMILIAL CANCER
Volume 20, Issue 3, Pages 231-239Publisher
SPRINGER
DOI: 10.1007/s10689-020-00209-x
Keywords
CDKN2A; Familial melanoma; Germline mutation; Genetic testing; Nomogram; GenoMEL
Categories
Funding
- National Health and Medical Research Council of Australia (NHMRC) [402761, APP1093017]
- US National Institutes of Health (NIH RO1 Grant) [CA83115]
- NHMRC Career Development Fellowship [1147843]
- Highland Island Enterprise [HMS9353763]
- NHMRC Senior Principal Research Fellowship
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A risk prediction model named FRAMe was developed and validated to estimate the likelihood of carrying a heritable CDKN2A mutation in Australian families with increased melanoma risk. Family variables such as age of melanoma diagnosis, number of primary melanomas, and cancer history were independently associated with mutation status. The model had good predictive performance, especially in areas with high melanoma incidence.
Germline mutations inCDKN2Agreatly increase risk of developing cutaneous melanoma. We have constructed a risk prediction model, Familial Risk Assessment of Melanoma (FRAMe), for estimating the likelihood of carrying a heritableCDKN2Amutation among Australian families, where the prevalence of these mutations is low. Using logistic regression, we analysed characteristics of 299 Australian families recruited through the Sydney site of GenoMEL (international melanoma genetics consortium) with at least three cases of cutaneous melanoma (in situ and invasive) among first-degree blood relatives, for predictors of the presence of a pathogenicCDKN2Amutation. The final multivariable prediction model was externally validated in an independent cohort of 61 melanoma kindreds recruited through GenoMEL Queensland. Family variables independently associated with the presence of aCDKN2Amutation in a multivariable model were number of individuals diagnosed with melanoma under 40 years of age, number of individuals diagnosed with more than one primary melanoma, and number of individuals blood related to a melanoma case in the first degree diagnosed with any cancer excluding melanoma and non-melanoma skin cancer. The number of individuals diagnosed with pancreatic cancer was not independently associated with mutation status. The risk prediction model had an area under the receiver operating characteristic curve (AUC) of 0.851 (95% CI 0.793, 0.909) in the training dataset, and 0.745 (95%CI 0.612, 0.877) in the validation dataset. This model is the first to be developed and validated using only Australian data, which is important given the higher rate of melanoma in the population. This model will help to effectively identify families suitable for genetic counselling and testing in areas of high ambient ultraviolet radiation. A user-friendly electronic nomogram is available at www.melanomarisk.org.au.
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