Department of Endocrinology and Metabolism, First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China.
Jiangxi Clinical Research Center for Endocrine and Metabolic Disease, Nanchang, Jiangxi, China.
Front Endocrinol (Lausanne). 2022 Nov 15;13:994836. doi: 10.3389/fendo.2022.994836. eCollection 2022.
This study aimed to cluster patients with diabetes and explore the association between duration of diabetes and diabetes treatment choices in each cluster.
A Two-Step cluster analysis was performed on 1332 Chinese patients with diabetes based on six parameters (glutamate decarboxylase antibodies, age at disease onset, body mass index, glycosylated hemoglobin, homeostatic model assessment 2 to estimate β-cell function and insulin resistance). Associations between the duration of diabetes and diabetes treatment choices in each cluster of patients were analyzed using Kaplan-Meier survival curves and logistic regression models.
The following five replicable clusters were identified: severe autoimmune diabetes (SAID), severe insulin-deficient diabetes (SIDD), severe insulin-resistant diabetes (SIRD), mild obesity-related diabetes (MOD), and mild age-related diabetes (MARD). There were significant differences in blood pressure, blood lipids, and diabetes-related complications among the clusters (all < 0.05). Early in the course of disease (≤5 years), compared with the other subgroups, the SIRD, MOD, and MARD populations were more likely to receive non-insulin hypoglycemic agents for glycemic control. Among the non-insulin hypoglycemic drug options, SIRD had higher rates of receiving metformin, alpha-glucosidase inhibitor (AGI), and glucagon-like peptide-1 drug; the MOD and MARD groups both received metformin, AGI and sodium-glucose cotransporter 2 inhibitor (SGLT-2i) drug ratio was higher. While the SAID and SIDD groups were more inclined to receive insulin therapy than the other subgroups, with SAID being more pronounced. With prolonged disease course (>5 years), only the MOD group was able to accept non-insulin hypoglycemic drugs to control the blood sugar levels, and most of them are still treated with metformin, AGI, and SGLT-2i drugs. While the other four groups required insulin therapy, with SIDD being the most pronounced.
Clustering of patients with diabetes with a data-driven approach yields consistent results. Each diabetes cluster has significantly different disease characteristics and risk of diabetes complications. With the development of the disease course, each cluster receives different hypoglycemic treatments.
本研究旨在对糖尿病患者进行聚类，并探讨每个聚类中糖尿病病程与糖尿病治疗选择之间的关系。
对 1332 例中国糖尿病患者的 6 项参数（谷氨酸脱羧酶抗体、发病年龄、体重指数、糖化血红蛋白、稳态模型评估 2 估计β细胞功能和胰岛素抵抗）进行两步聚类分析。采用 Kaplan-Meier 生存曲线和 logistic 回归模型分析每个聚类患者的糖尿病病程与糖尿病治疗选择之间的关系。
共确定了 5 个可重复的聚类：严重自身免疫性糖尿病（SAID）、严重胰岛素缺乏性糖尿病（SIDD）、严重胰岛素抵抗性糖尿病（SIRD）、轻度肥胖相关糖尿病（MOD）和轻度年龄相关性糖尿病（MARD）。各组间血压、血脂和糖尿病相关并发症存在显著差异（均<0.05）。在疾病早期（≤5 年），与其他亚组相比，SIRD、MOD 和 MARD 人群更倾向于使用非胰岛素类降糖药物控制血糖。在非胰岛素类降糖药物的选择中，SIRD 使用二甲双胍、α-葡萄糖苷酶抑制剂（AGI）和胰高血糖素样肽-1 药物的比例较高；MOD 和 MARD 组均使用二甲双胍、AGI 和钠-葡萄糖共转运蛋白 2 抑制剂（SGLT-2i）药物，其比例较高。SAID 和 SIDD 组比其他亚组更倾向于接受胰岛素治疗，而 SAID 更为明显。随着病程的延长（>5 年），只有 MOD 组能够接受非胰岛素类降糖药物来控制血糖水平，且大部分仍使用二甲双胍、AGI 和 SGLT-2i 药物。而其他 4 组则需要胰岛素治疗，其中 SIDD 最为明显。
采用数据驱动的方法对糖尿病患者进行聚类可获得一致的结果。每个糖尿病聚类具有显著不同的疾病特征和糖尿病并发症风险。随着疾病病程的发展，每个聚类接受不同的降糖治疗。
