Large-scale epidemiological analysis of common skin diseases to identify shared and unique comorbidities and demographic factors

The utilization of large-scale claims databases has greatly improved the management, accessibility, and integration of extensive medical data. However, its potential for systematically identifying comorbidities in the context of skin diseases remains unexplored. This study aims to assess the capability of a comprehensive claims database in identifying comorbidities linked to 14 specific skin and skin-related conditions and examining temporal changes in their association patterns. This study employed a retrospective case-control cohort design utilizing 13 million skin/skin-related patients and 2 million randomly sampled controls from Optum's de-identified Clinformatics Data Mart Database spanning the period from 2001 to 2018. A broad spectrum of comorbidities encompassing cancer, diabetes, respiratory, mental, immunity, gastrointestinal, and cardiovascular conditions were examined for each of the 14 skin and skin-related disorders in the study. Using the established type-2 diabetes (T2D) and psoriasis comorbidity as example, we demonstrated the association is significant (P-values