Aim: Guidelines for follow-up of melanoma patients are based on limited evidence and differ considerably by country. To guide skin surveillance, we developed a risk prediction model for subsequent primary melanoma based on demographic, environmental, phenotypic, genomic and histopathological risk factors.
Methods: Using Cox regression frailty models, we analyzed data for 2,613 melanomas from 1,266 patients with a single or subsequent primary melanoma recruited to the population-based Genes, Environment and Melanoma (GEM) study in New South Wales, Australia, in 2000-2003 and followed-up via the Cancer Registry for a median of 14 years. Discrimination and calibration of the risk prediction model were assessed, stratified by number of previous melanomas. Nomograms were created for estimating absolute risk of subsequent melanoma.
Results: The median time to diagnosis of a subsequent primary melanoma decreased with each new primary. The final prediction model included age, sex, previous keratinocyte cancer (non-melanoma skin cancer), family history of melanoma, time spent in outdoor leisure activities, skin color, nevus density, ability to tan, anatomical site, histological subtype, polygenic risk score, and CDKN2A mutation. Harrell’s C-statistic was 0.73 (95% confidence interval [CI] 0.69-0.78), 0.65 (95% CI 0.62-0.67) and 0.65 (95% CI 0.61-0.69) for predicting second, third and fourth primary melanomas, respectively. The risk of a subsequent melanoma was 4.72 times higher (95% confidence interval 3.84-5.79) for participants in the highest versus lowest quintile of risk. The mean absolute risk of developing a subsequent primary melanoma within 5 years was 7.6% (standard deviation [SD] 4.0%) after the first melanoma and 47.0% (SD 15.1%) after the second.
Conclusion: This risk prediction model enables estimation of absolute risk of subsequent melanoma based on an individual’s risk factors and could be used to tailor surveillance, communicate risk and inform patient education.