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Accuracy of Self-reported Nevus and Pigmentation Phenotype Compared with Clinical Assessment in a Population-based Study of Young Australian Adults

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Date 2015 Jan 29
PMID 25628333
Citations 6
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Abstract

Background: Awareness of individual risk may encourage improved prevention and early detection of melanoma.

Methods: We evaluated the accuracy of self-reported pigmentation and nevus phenotype compared with clinical assessment, and examined agreement between nevus counts from selected anatomical regions. The sample included 456 cases with invasive cutaneous melanoma diagnosed between ages 18 to 39 years and 538 controls from the population-based Australian Melanoma Family Study. Participants completed a questionnaire about their pigmentation and nevus phenotype, and attended a dermatologic skin examination.

Results: There was strong agreement between self-reported and clinical assessment of eye color [κ, = 0.78; 95% confidence interval (CI), 0.74-0.81]; and moderate agreement for hair color (κ = 0.46; 95% CI, 0.42-0.50). Agreement between self-reported skin color and spectrophotometer-derived measurements was poor (κ = 0.12; 95% CI, 0.08-0.16) to moderate (Spearman correlation rs = -0.37; 95% CI, -0.32 to -0.42). Participants tended to underestimate their nevus counts and pigmentation; men were more likely to underreport their skin color. The rs was 0.43 (95% CI, 0.38-0.49) comparing clinical total body nevus counts with self-reported nevus categories. There was good agreement between total body nevus counts and site-specific nevus counts, particularly on both arms.

Conclusions: Young adults have suboptimal accuracy when assessing important risk characteristics including nevus numbers and pigmentation. Measuring nevus count on the arms is a good predictor of full body nevus count.

Impact: These results have implications for the likely success of targeted public health programs that rely on self-assessment of these factors.

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References
1.
English J, Swerdlow A, Mackie R, ODoherty C, Hunter J, Clark J . Site-specific melanocytic naevus counts as predictors of whole body naevi. Br J Dermatol. 1988; 118(5):641-4. DOI: 10.1111/j.1365-2133.1988.tb02564.x. View

2.
Gallus S, Naldi L, Carli P, La Vecchia C . Nevus count on specific anatomic sites as a predictor of total body count: a survey of 3,406 children from Italy. Am J Epidemiol. 2007; 166(4):472-8. DOI: 10.1093/aje/kwm114. View

3.
Dodd A, Morelli J, Mokrohisky S, Asdigian N, Byers T, Crane L . Melanocytic nevi and sun exposure in a cohort of colorado children: anatomic distribution and site-specific sunburn. Cancer Epidemiol Biomarkers Prev. 2007; 16(10):2136-43. PMC: 2997330. DOI: 10.1158/1055-9965.EPI-07-0453. View

4.
Pershing L, Tirumala V, Nelson J, Corlett J, Lin A, Meyer L . Reflectance spectrophotometer: the dermatologists' sphygmomanometer for skin phototyping?. J Invest Dermatol. 2008; 128(7):1633-40. DOI: 10.1038/sj.jid.5701238. View

5.
Richtig E, Santigli E, Fink-Puches R, Weger W, Hofmann-Wellenhof R . Assessing melanoma risk factors: how closely do patients and doctors agree?. Public Health. 2008; 122(12):1433-9. DOI: 10.1016/j.puhe.2008.04.012. View