Luo Yingying, Wu Hong, Liao Xiyang, Zhao Tingting, Cui Nan, Li Aihua, Sun Xingzhi, Zhang Puhong, Huang Yahua, Zhang Xia, Yin Huiqiu, Ji Linong
Department of Endocrinology and Metabolism, Peking University People's Hospital, Beijing, China.
Peking University Diabetes Center, Beijing, China.
Diabetes Ther. 2021 Jul;12(7):1887-1899. doi: 10.1007/s13300-021-01075-1. Epub 2021 May 29.
China has the world's largest diabetes epidemic and has been facing a serious shortage of primary care providers for chronic diseases including diabetes. To help primary care physicians follow guidelines and mitigate the workload in primary care communities in China, we developed a guideline-based decision tree. This study aimed to validate it at 3 months with real-world data.
The decision tree was developed based on the 2017 Chinese Type 2 Diabetes (T2DM) guideline and 2018 guideline for primary care. It was validated with the data from two registry studies: the NEW2D and ORBIT studies. Patients' data were divided into two groups: the compliance and non-compliance group, depending on whether the physician's prescription was consistent with the decision tree or not. The primary outcome was the difference of change in HbA1c from baseline to 3 months between the two groups. The secondary outcomes included the difference in the proportion of patients achieving HbA1c < 7% at 3 months between the two groups, the incidence of self-reported hypoglycemia at 3 months, and the proportion of patients (baseline HbA1c ≥ 7%) with a HbA1c reduction ≥ 0.3%. The statistical analysis was performed using linear or logistic regression with inverse probability of treatment weighting with adjustments of confounding factors.
There was a 0.9% reduction of HbA1c in the compliance group and a 0.8% reduction in the non-compliance group (P < 0.001); 61.1% of the participants in the compliance group and 44.3% of the participants in the non-compliance group achieved a HbA1c level < 7% at 3 months (P < 0.001). The hypoglycemic events occurred in 7.1% of patients in the compliance group vs. 9.4% in the non-compliance group (P < 0.001).
The decision tree can help physicians to treat their patients so that they achieve their glycemic targets with fewer hypoglycemic risks. ( http://www.clinicaltrials.gov NCT01525693 & NCT01859598).
中国是全球糖尿病患者最多的国家，且一直面临包括糖尿病在内的慢性病基层医疗服务提供者严重短缺的问题。为帮助基层医疗医生遵循指南并减轻中国基层医疗社区的工作量，我们开发了一种基于指南的决策树。本研究旨在利用真实世界数据在3个月时对其进行验证。
该决策树是基于2017年中国2型糖尿病（T2DM）指南和2018年基层医疗指南开发的。它通过两项注册研究的数据进行验证：NEW2D研究和ORBIT研究。根据医生的处方是否与决策树一致，将患者数据分为两组：依从组和不依从组。主要结局是两组从基线到3个月时糖化血红蛋白（HbA1c）变化的差异。次要结局包括两组在3个月时糖化血红蛋白水平＜7%的患者比例差异、3个月时自我报告的低血糖发生率，以及糖化血红蛋白降低≥0.3%的患者（基线糖化血红蛋白≥7%）比例。采用线性或逻辑回归进行统计分析，并使用治疗权重的逆概率对混杂因素进行调整。
依从组糖化血红蛋白降低了0.9%，不依从组降低了0.8%（P＜0.001）；3个月时，依从组61.1%的参与者和不依从组44.3%的参与者糖化血红蛋白水平＜7%（P＜0.001）。依从组7.1%的患者发生低血糖事件，不依从组为9.4%（P＜0.001）。
该决策树可帮助医生治疗患者，使其在低血糖风险较低的情况下实现血糖目标。（http://www.clinicaltrials.gov NCT01525693 & NCT01859598）
