Huang Yanqun, Chen Siyuan, Wang Yongfeng, Ou Xiaohong, Yan Huanhuan, Gan Xin, Wei Zhixiao
Department of Medical Equipment, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
Department of Nuclear Medicine, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
Interact J Med Res. 2024 Oct 3;13:e54891. doi: 10.2196/54891.
Thyroid disease (TD) is a prominent endocrine disorder that raises global health concerns; however, its comorbidity patterns remain unclear.
This study aims to apply a network-based method to comprehensively analyze the comorbidity patterns of TD using large-scale real-world health data.
In this retrospective observational study, we extracted the comorbidities of adult patients with TD from both private and public data sets. All comorbidities were identified using ICD-10 (International Classification of Diseases, 10th Revision) codes at the 3-digit level, and those with a prevalence greater than 2% were analyzed. Patients were categorized into several subgroups based on sex, age, and disease type. A phenotypic comorbidity network (PCN) was constructed, where comorbidities served as nodes and their significant correlations were represented as edges, encompassing all patients with TD and various subgroups. The associations and differences in comorbidities within the PCN of each subgroup were analyzed and compared. The PageRank algorithm was used to identify key comorbidities.
The final cohorts included 18,311 and 50,242 patients with TD in the private and public data sets, respectively. Patients with TD demonstrated complex comorbidity patterns, with coexistence relationships differing by sex, age, and type of TD. The number of comorbidities increased with age. The most prevalent TDs were nontoxic goiter, hypothyroidism, hyperthyroidism, and thyroid cancer, while hypertension, diabetes, and lipoprotein metabolism disorders had the highest prevalence and PageRank values among comorbidities. Males and patients with benign TD exhibited a greater number of comorbidities, increased disease diversity, and stronger comorbidity associations compared with females and patients with thyroid cancer.
Patients with TD exhibited complex comorbidity patterns, particularly with cardiocerebrovascular diseases and diabetes. The associations among comorbidities varied across different TD subgroups. This study aims to enhance the understanding of comorbidity patterns in patients with TD and improve the integrated management of these individuals.
甲状腺疾病（TD）是一种引起全球健康关注的突出内分泌疾病；然而，其共病模式仍不明确。
本研究旨在应用基于网络的方法，使用大规模真实世界健康数据全面分析TD的共病模式。
在这项回顾性观察研究中，我们从私人和公共数据集中提取成年TD患者的共病情况。所有共病均使用国际疾病分类第10版（ICD-10）三位编码识别，并对患病率大于2%的共病进行分析。患者根据性别、年龄和疾病类型分为几个亚组。构建了一个表型共病网络（PCN），其中共病作为节点，它们之间的显著相关性表示为边，涵盖所有TD患者和各个亚组。分析并比较了每个亚组PCN中共病之间的关联和差异。使用PageRank算法识别关键共病。
最终队列分别包括私人数据集和公共数据集中的18311例和50242例TD患者。TD患者表现出复杂的共病模式，共存关系因性别、年龄和TD类型而异。共病数量随年龄增加。最常见的TD是非毒性甲状腺肿、甲状腺功能减退、甲状腺功能亢进和甲状腺癌，而高血压、糖尿病和脂蛋白代谢紊乱在共病中患病率和PageRank值最高。与女性和甲状腺癌患者相比，男性和良性TD患者的共病数量更多、疾病多样性增加且共病关联更强。
TD患者表现出复杂的共病模式，尤其是与心脑血管疾病和糖尿病。不同TD亚组中共病之间的关联各不相同。本研究旨在增进对TD患者共病模式的理解，并改善这些患者的综合管理。
