Models predict the relationship between nonmelanoma skin cancer and ambient UV radiation

1. Squamous Cell Carcinoma (SCC) and Basal Cell Carcinoma (BCC) displayed differing environmental and demographic etiologies, but development of both cancers were correlated with higher ambient ultraviolet radiation (UVR) levels. 

2. Statistical models may accurately predict the incidence of SCCs and BCCs based on age group, sex, and ambient UVR. 

Evidence Rating Level: 2 (Good) 

Study Rundown: A broad classification that most commonly refers to SCCs and BCCs, nonmelanoma skin cancer (NMSC), has long been known to be primarily caused by exposure to UVR.  However, there is significant variability in NMSC incidence among geographical locations that cannot be entirely explained by individual behavior (such as a person who sunbathes each day).  In this study, the authors analyzed 40 previously published studies to identify relationships between ambient UVR levels and NMSC incidence at the population level. In this data collection, 88% of SCCs and 85% of BCCs could be predicted by age group, sex, study year, and ambient UVR. These high percentages suggest that the analytical models used in this study can be applied to the prediction of NMSC incidence both in areas in which cancer data is unavailable and in locations in which demographic and/or environmental conditions are changing. A strength of this study was the authors’ comprehensive utilization of statistical models. A weakness was the study’s inherent dependence on the accuracy of articles published by other individuals.

Click to read the study in JAMA Dermatology

Relevant reading: A meta-analysis of pigmentary characteristics, sun sensitivity, freckling and melanocytic nevi and risk of basal cell carcinoma of the skin

In-Depth [retrospective cohort]: Forty articles met inclusion criteria. Based on data gathered from two international geographic databases (the International Research Institute web-based data library and the National Aeronautics and Space Administration Ozone Monitoring Instrument), mean daily ambient UVR levels were estimated for each study’s location and year.  Incidence data were standardized using DISMOD II software and were analyzed with Poisson distribution regression models.  Other models, including negative binomial and ordinary least squares regression with log transformation, were examined, but the Poisson regression model proved to be superior. Study year, age group, and sex were responsible for 3%, 37%, and 3%, respectively, of the variability in BCCs. For SCC, the corresponding results were 6%, 34%, and 3%. Together, a Poisson Regression Model combining these factors, along with ambient UVR values, explained 82% of the variability in BCC incidence and 85% of SCC incidence. However, when the data were restricted to studies that reported age-specific data, the percentages increased to 85% and 88% for BCC and SCC, respectively.

Image: PD 

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