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开发并内部验证一种预测工具,以帮助临床医生在二甲双胍单药治疗 2 型糖尿病后选择二线治疗。

Development and Internal Validation of A Prediction Tool To Assist Clinicians Selecting Second-Line Therapy Following Metformin Monotherapy For Type 2 Diabetes.

机构信息

Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio; Diasome Pharmaceuticals, Inc, Cleveland, Ohio; Case Western Reserve University, School of Medicine, Cleveland, Ohio.

Department of Endocrinology, Diabetes, and Metabolism, Cleveland Clinic, Cleveland, Ohio.

出版信息

Endocr Pract. 2021 Apr;27(4):334-341. doi: 10.1016/j.eprac.2020.10.015. Epub 2020 Dec 15.

Abstract

OBJECTIVE

Adults with type 2 diabetes (T2D) face increased risk of many long-term adverse outcomes. While managing patients with T2D, clinicians are challenged to stay informed regarding all new therapies and must consider potential risks and benefits resultant to their use. Metformin (MET) is typically prescribed as first-line therapy, but a second line is often needed, given MET can be insufficient for maintaining long-term glycemic control. Our objective was to develop a predictive decision-making tool to help clinicians use an outcome-based approach to select second-line therapies for patients when MET monotherapy is insufficient for glycemic control.

METHODS

Electronic health records of 19 277 adults with T2D on MET monotherapy and ≥3 months of either GLP-1RA, DPP-4i, Insulin, SGLT-2i, SFU, or TZD therapy were reviewed at Cleveland Clinic from patient visits occurring between 2005 and 2019. Separate models were developed to predict likelihood of each main outcome measure (stroke, myocardial infarction, worsening hypertension, renal failure, and death). Discrimination and calibration were assessed with bootstrapping.

RESULTS

The median follow-up time for those without an event was 3.6 years (interquartile range 1.9, 6.3). Model discrimination ability was evaluated by concordance indices (goodness of fit metric with values ranging between 0 and 1: 1 indicates perfect discrimination ability; 0.5 reflects same discrimination ability as chance) demonstrating strong discrimination ability, with concordance index values for outcomes as follows: myocardial infarction (0.786), stroke (0.805), worsening hypertension (0.855), renal failure (0.808), and death (0.827).

CONCLUSION

A decision-making tool has been developed that may afford clinicians a more objective and individualized approach to choosing a second-line therapy to control glycemia for persons with T2D.

摘要

目的

2 型糖尿病(T2D)患者面临许多长期不良结局的风险增加。在治疗 T2D 患者时,临床医生面临着及时了解所有新疗法的挑战,必须考虑使用这些疗法的潜在风险和获益。二甲双胍(MET)通常作为一线治疗药物,但由于 MET 可能不足以维持长期血糖控制,通常需要二线治疗。我们的目的是开发一种预测决策工具,以帮助临床医生在 MET 单药治疗不足以控制血糖时,根据基于结局的方法为患者选择二线治疗药物。

方法

回顾了克利夫兰诊所 2005 年至 2019 年期间就诊的 19277 例接受 MET 单药治疗且至少有 3 个月 GLP-1RA、DPP-4i、胰岛素、SGLT-2i、SFU 或 TZD 治疗的 T2D 成年患者的电子健康记录。分别建立模型以预测每种主要结局指标(中风、心肌梗死、高血压恶化、肾衰竭和死亡)的发生概率。通过 bootstrap 评估判别和校准。

结果

无事件患者的中位随访时间为 3.6 年(四分位间距 1.9,6.3)。通过一致性指数(拟合优度指标,值范围为 0 至 1:1 表示完美的判别能力;0.5 反映与机会相同的判别能力)评估模型判别能力,结果显示具有很强的判别能力,各结局的一致性指数值如下:心肌梗死(0.786)、中风(0.805)、高血压恶化(0.855)、肾衰竭(0.808)和死亡(0.827)。

结论

已经开发出一种决策工具,它可以为临床医生提供一种更客观和个体化的方法,选择二线治疗药物来控制 T2D 患者的血糖。

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