A risk prediction model for the development of subsequent primary melanoma in a population-based cohort

Background Guidelines for follow-up of patients with melanoma are based on limited evidence. Objectives To guide skin surveillance, we developed a risk prediction model for subsequent primary melanomas, using demographic, phenotypical, histopathological, sun exposure and genomic risk factors. Methods Using Cox regression frailty models, we analysed data for 2613 primary melanomas from 1266 patients recruited to the population-based Genes, Environment and Melanoma study in New South Wales, Australia, with a median of 14 years' follow-up via the cancer registry. Discrimination and calibration were assessed. Results The median time to diagnosis of a subsequent primary melanoma decreased with each new primary melanoma. The final model included 12 risk factors. Harrell's C-statistic was 0 center dot 73 [95% confidence interval (CI) 0 center dot 68-0 center dot 77], 0 center dot 65 (95% CI 0 center dot 62-0 center dot 68) and 0 center dot 65 (95% CI 0 center dot 61-0 center dot 69) for predicting second, third and fourth primary melanomas, respectively. The risk of a subsequent primary melanoma was 4 center dot 75 times higher (95% CI 3 center dot 87-5 center dot 82) for the highest vs. the lowest quintile of the risk score. The mean absolute risk of a subsequent primary melanoma within 5 years was 8 center dot 0 +/- SD 4.1% after the first primary melanoma, and 46 center dot 8 +/- 15 center dot 0% after the second, but varied substantially by risk score. Conclusions The risk of developing a subsequent primary melanoma varies considerably between individuals and is particularly high for those with two or more primary melanomas. The risk prediction model and its associated nomograms enable estimation of the absolute risk of subsequent primary melanoma, on the basis of on an individual's risk factors, and can be used to tailor surveillance intensity, communicate risk and provide patient education.