Development and Validation of a Simple Model to Predict the Risk of Nonmelanoma Skin Cancer on Screening Total Body Skin Examination.

IF 1.5 Q3 DERMATOLOGY Dermatology Research and Practice Pub Date : 2022-08-16 eCollection Date: 2022-01-01 DOI:10.1155/2022/2313896
Rebecca I Hartman, Yun Xue, Ryan Karmouta, Elizabeth Tkachenko, Sara J Li, David G Li, Cara Joyce, Arash Mostaghimi
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Abstract

Objective: There is insufficient evidence to generate skin cancer screening guidelines at the population level, resulting in arbitrary variation in patient selection for screening skin examinations. This study was aimed at developing an easy-to-use predictive model of nonmelanoma skin cancer (NMSC) risk on screening total body skin examination (TBSE).

Methods: This epidemiologic assessment utilized data from a prospective, multicenter international study from primarily academic outpatient dermatology clinics. Potential predictors of NMSC on screening TBSE were identified and used to generate a multivariable model that was converted into a point-based scoring system. The performance characteristics of the model were validated in a second data set from two healthcare institutions in the United States.

Results: 8,501 patients were included. Statistically significant predictors of NMSC on screening TBSE included age, skin phototype, and history of NMSC. A multivariable model and point-based scoring system using these predictors exhibited high discrimination (AUC = 0.82).

Conclusion: A simple three-variable model, abbreviated as CAP (cancer history, age, phototype) can accurately predict the risk of NMSC on screening TBSE by dermatology. This tool may be used in clinical decision making to enhance the yield of screening TBSE.

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建立和验证一个简单的模型来预测非黑色素瘤皮肤癌的风险筛选全身皮肤检查。
目的:在人群水平上制定皮肤癌筛查指南的证据不足,导致筛查皮肤检查患者选择的随意性变化。本研究旨在开发一种易于使用的非黑色素瘤皮肤癌(NMSC)风险预测模型,用于筛查全身皮肤检查(TBSE)。方法:这项流行病学评估利用了一项前瞻性、多中心的国际研究数据,主要来自学术门诊皮肤科诊所。确定了NMSC筛查TBSE的潜在预测因子,并用于生成多变量模型,该模型转化为基于积分的评分系统。该模型的性能特征在来自美国两家医疗机构的第二个数据集中得到验证。结果:共纳入8501例患者。有统计学意义的NMSC筛查TBSE的预测因子包括年龄、皮肤光型和NMSC病史。使用这些预测因子的多变量模型和基于点数的评分系统显示出高判别性(AUC = 0.82)。结论:一个简单的三变量模型,缩写为CAP(癌史、年龄、光型)可以准确预测皮肤病学筛查TBSE时NMSC的风险。该工具可用于临床决策,以提高筛查TBSE的产量。
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来源期刊
CiteScore
3.80
自引率
0.00%
发文量
16
审稿时长
11 weeks
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