Abstract
OBJECTIVE: To develop a self-assessed melanoma risk score to identify high-risk persons for screening METHODS: We used data from a 1997 melanoma case-control study from Washington State, USA, where 386 cases with invasive cutaneous melanoma and 727 controls were interviewed by telephone. A logistic regression prediction model was developed on 75% of the data and validated in the remaining 25% by calculating the area under the receiver operating characteristic curve (AUC), a measure of predictive accuracy from 0.5-1 (higher scores indicating better prediction). A risk score was calculated for each individual, and sensitivities for various risk cutoffs were calculated. RESULTS: The final model included sex, age, hair color, density of freckles, number of severe sunburns in childhood and adolescence, number of raised moles on the arms, and history of non-melanoma skin cancer. The area under the receiver operating characteristic curve(AUC) was 0.70 (95% CI: 0.64, 0.77). The top 15% risk group included 50% of melanomas (sensitivity 50%). CONCLUSIONS: This self-assessed score could be used as part of a comprehensive melanoma screening and public education program to identify high-risk individuals in the general population. This study suggests it may be possible to capture a large proportion of melanomas by screening a small high-risk group. Further study is needed to determine the costs, feasibility, and risks of this approach.