He Steven Y, McCulloch Charles E, Boscardin W John, Chren Mary-Margaret, Linos Eleni, Arron Sarah T
Department of Dermatology, University of California at San Francisco, San Francisco, California.
Department of Epidemiology and Biostatistics, University of California at San Francisco, San Francisco, California.
J Am Acad Dermatol. 2014 Oct;71(4):731-7. doi: 10.1016/j.jaad.2014.05.023. Epub 2014 Jun 11.
Fitzpatrick skin phototype (FSPT) is the most common method used to assess sunburn risk and is an independent predictor of skin cancer risk. Because of a conventional assumption that FSPT is predictable based on pigmentary phenotypes, physicians frequently estimate FSPT based on patient appearance.
We sought to determine the degree to which self-reported race and pigmentary phenotypes are predictive of FSPT in a large, ethnically diverse population.
A cross-sectional survey collected responses from 3386 individuals regarding self-reported FSPT, pigmentary phenotypes, race, age, and sex. Univariate and multivariate logistic regression analyses were performed to determine variables that significantly predict FSPT.
Race, sex, skin color, eye color, and hair color are significant but weak independent predictors of FSPT (P<.0001). A multivariate model constructed using all independent predictors of FSPT only accurately predicted FSPT to within 1 point on the Fitzpatrick scale with 92% accuracy (weighted kappa statistic 0.53).
Our study enriched for responses from ethnic minorities and does not fully represent the demographics of the US population.
Patient self-reported race and pigmentary phenotypes are inaccurate predictors of sun sensitivity as defined by FSPT. There are limitations to using patient-reported race and appearance in predicting individual sunburn risk.
菲茨帕特里克皮肤光类型(FSPT)是评估晒伤风险最常用的方法,也是皮肤癌风险的独立预测指标。由于传统上认为FSPT可根据色素沉着表型预测,医生常根据患者外观来估计FSPT。
我们试图确定在一个种族多样化的大群体中,自我报告的种族和色素沉着表型对FSPT的预测程度。
一项横断面调查收集了3386名个体关于自我报告的FSPT、色素沉着表型、种族、年龄和性别的回复。进行单变量和多变量逻辑回归分析以确定能显著预测FSPT的变量。
种族、性别、肤色、眼睛颜色和头发颜色是FSPT的显著但较弱的独立预测指标(P<0.0001)。使用FSPT的所有独立预测指标构建的多变量模型仅能以92%的准确率在菲茨帕特里克量表上准确预测FSPT在1分以内(加权kappa统计量为0.53)。
我们的研究增加了少数族裔的回复,但不能完全代表美国人口的人口统计学特征。
患者自我报告的种族和色素沉着表型是FSPT所定义的阳光敏感性的不准确预测指标。在预测个体晒伤风险时,使用患者报告的种族和外观存在局限性。