Department of Biostatistics, University of Michigan, Ann Arbor, MI, United States.
Department of Dermatology, University of Michigan, Ann Arbor, MI, United States.
Front Immunol. 2024 Jan 8;14:1309549. doi: 10.3389/fimmu.2023.1309549. eCollection 2023.
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<1x10) and stable across years (OR=1.15-1.31). Analysis of the 2014-2018 data reveals that celiac disease, Crohn's disease, and ulcerative colitis exhibit the strongest associations with the 14 skin/skin-related conditions. Systemic lupus erythematosus (SLE), leprosy, and hidradenitis suppurativa show the strongest associations with 30 different comorbidities. Particularly notable associations include Crohn's disease with leprosy (odds ratio [OR]=6.60, 95% confidence interval [CI]: 3.09-14.08), primary biliary cirrhosis with SLE (OR=6.07, 95% CI: 4.93-7.46), and celiac disease with SLE (OR=6.06, 95% CI: 5.49-6.69). In addition, changes in associations were observed over time. For instance, the association between atopic dermatitis and lung cancer demonstrates a marked decrease over the past decade, with the odds ratio decreasing from 1.75 (95% CI: 1.47-2.07) to 1.02 (95% CI: 0.97-1.07). The identification of skin-associated comorbidities contributes to individualized healthcare and improved clinical management, while also enhancing our understanding of shared pathophysiology. Moreover, tracking these associations over time aids in evaluating the progression of clinical diagnosis and treatment.
The findings highlight the potential of utilizing comprehensive claims databases in advancing research and improving patient care in dermatology.
利用大规模的索赔数据库极大地提高了广泛的医疗数据的管理、可及性和整合。然而，其在皮肤病背景下系统识别合并症的潜力尚未得到探索。
本研究旨在评估综合索赔数据库识别 14 种特定皮肤和皮肤相关疾病相关合并症的能力，并研究其关联模式的时间变化。本研究采用回顾性病例对照队列设计，利用 Optum 的去识别 Clinformatics Data Mart 数据库中的 1300 万例皮肤/皮肤相关患者和 200 万例随机抽样对照，时间范围为 2001 年至 2018 年。本研究对 14 种皮肤和皮肤相关疾病中的每一种疾病进行了广泛的合并症检查，包括癌症、糖尿病、呼吸、精神、免疫、胃肠道和心血管疾病。
以已建立的 2 型糖尿病（T2D）和银屑病合并症为例，我们证明了这种关联是显著的（P 值<1x10）且多年来保持稳定（OR=1.15-1.31）。对 2014-2018 年数据的分析表明，乳糜泻、克罗恩病和溃疡性结肠炎与 14 种皮肤/皮肤相关疾病的关联最强。系统性红斑狼疮（SLE）、麻风病和化脓性汗腺炎与 30 种不同的合并症关联最强。特别显著的关联包括克罗恩病与麻风病（比值比 [OR]=6.60，95%置信区间 [CI]：3.09-14.08）、原发性胆汁性肝硬化与 SLE（OR=6.07，95% CI：4.93-7.46）和乳糜泻与 SLE（OR=6.06，95% CI：5.49-6.69）。此外，还观察到关联随时间的变化。例如，特应性皮炎与肺癌之间的关联在过去十年中显著下降，比值比从 1.75（95%CI：1.47-2.07）降至 1.02（95%CI：0.97-1.07）。识别与皮肤相关的合并症有助于个性化医疗保健和改善临床管理，同时增强我们对共同病理生理学的理解。此外，随着时间的推移跟踪这些关联有助于评估临床诊断和治疗的进展。
这些发现突出了利用综合索赔数据库在推进皮肤科研究和改善患者护理方面的潜力。
