台湾 2 型糖尿病患者糖尿病肾脏疾病预测风险方程的外部验证和校准。

External validation and calibration of risk equations for prediction of diabetic kidney diseases among patients with type 2 diabetes in Taiwan.

机构信息

Institute of Clinical Pharmacy and Pharmaceutical Sciences, College of Medicine, National Cheng Kung University, 1 University Road, Tainan, 701, Taiwan.

Institute of Clinical Medicine, College of Medicine, National Cheng Kung University, Tainan, Taiwan.

出版信息

Cardiovasc Diabetol. 2024 Oct 9;23(1):357. doi: 10.1186/s12933-024-02443-4.

DOI:10.1186/s12933-024-02443-4

PMID:39385193

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11465834/

Abstract

BACKGROUND

Most existing risk equations for predicting/stratifying individual diabetic kidney disease (DKD) risks were developed using relatively dated data from selective and homogeneous trial populations comprising predominately Caucasian type 2 diabetes (T2D) patients. We seek to adapt risk equations for prediction of DKD progression (microalbuminuria, macroalbuminuria, and renal failure) using empiric data from a real-world population with T2D in Taiwan.

METHODS

Risk equations from three well-known simulation models: UKPDS-OM2, RECODe, and CHIME models, were adapted. Discrimination and calibration were determined using the area under the receiver operating characteristic curve (AUROC), a calibration plot (slope and intercept), and the Greenwood-Nam-D'Agostino (GND) test. Recalibration was performed for unsatisfactory calibration (p-value of GND test < 0.05) by adjusting the baseline hazards of risk equations to address risk variations among patients.

RESULTS

The RECODe equations for microalbuminuria and macroalbuminuria showed moderate discrimination (AUROC: 0.62 and 0.76) but underestimated the event risks (calibration slope > 1). The CHIME equation had the best discrimination for renal failure (AUROCs from CHIME, UKPDS-OM2 and RECODe: 0.77, 0.60 and 0.64, respectively). All three equations overestimated renal failure risk (calibration slope < 1). After rigorous updating, the calibration slope/intercept of the recalibrated RECODe for predicting microalbuminuria (0.87/0.0459) and macroalbuminuria (1.10/0.0004) risks as well as the recalibrated CHIME equation for predicting renal failure risk (0.95/-0.0014) were improved.

CONCLUSIONS

Risk equations for prediction of DKD progression in real-world Taiwanese T2D patients were established, which can be incorporated into a multi-state simulation model to project and differentiate individual DKD risks for supporting timely interventions and health economic research.

摘要

背景

大多数用于预测/分层个体糖尿病肾病（DKD）风险的现有风险方程是使用来自选择性和同质性试验人群的相对陈旧数据开发的，这些试验人群主要由白种人 2 型糖尿病（T2D）患者组成。我们试图使用来自台湾 T2D 真实世界人群的经验数据来调整用于预测 DKD 进展（微量白蛋白尿、大量白蛋白尿和肾衰竭）的风险方程。

方法

适应了三个著名的模拟模型的风险方程：UKPDS-OM2、RECODe 和 CHIME 模型。使用接受者操作特征曲线（AUROC）下的面积、校准图（斜率和截距）和 Greenwood-Nam-D'Agostino（GND）检验来确定区分度和校准。对于校准不理想的情况（GND 检验的 p 值<0.05），通过调整风险方程的基线风险来调整风险变化，从而进行重新校准。

结果

RECODe 方程对于微量白蛋白尿和大量白蛋白尿具有中等的区分度（AUROC：0.62 和 0.76），但低估了事件风险（校准斜率>1）。CHIME 方程对肾衰竭的区分度最好（CHIME、UKPDS-OM2 和 RECODe 方程的 AUROC 分别为 0.77、0.60 和 0.64）。所有三个方程都高估了肾衰竭风险（校准斜率<1）。经过严格的更新，校准斜率/截距重新校准的用于预测微量白蛋白尿（0.87/0.0459）和大量白蛋白尿（1.10/0.0004）风险的 RECODe 方程以及重新校准的 CHIME 方程用于预测肾衰竭风险（0.95/-0.0014）都得到了改善。