Institute of Clinical Pharmacy and Pharmaceutical Sciences, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Cardiovasc Diabetol. 2024 Jul 10;23(1):244. doi: 10.1186/s12933-024-02320-0.
To adapt risk prediction equations for myocardial infarction (MI), stroke, and heart failure (HF) among patients with type 2 diabetes in real-world settings using cross-institutional electronic health records (EHRs) in Taiwan.
The EHRs from two medical centers, National Cheng Kung University Hospital (NCKUH; 11,740 patients) and National Taiwan University Hospital (NTUH; 20,313 patients), were analyzed using the common data model approach. Risk equations for MI, stroke, and HF from UKPDS-OM2, RECODe, and CHIME models were adapted for external validation and recalibration. External validation was assessed by (1) discrimination, evaluated by the area under the receiver operating characteristic curve (AUROC) and (2) calibration, evaluated by calibration slopes and intercepts and the Greenwood-Nam-D'Agostino (GND) test. Recalibration was conducted for unsatisfactory calibration (p-value of GND test < 0.05) by adjusting the baseline hazards of original equations to address variations in patients' cardiovascular risks across institutions.
The CHIME risk equations had acceptable discrimination (AUROC: 0.71-0.79) and better calibration than that for UKPDS-OM2 and RECODe, although the calibration remained unsatisfactory. After recalibration, the calibration slopes/intercepts of the CHIME-MI, CHIME-stroke, and CHIME-HF risk equations were 0.9848/- 0.0008, 1.1003/- 0.0046, and 0.9436/0.0063 in the NCKUH population and 1.1060/- 0.0011, 0.8714/0.0030, and 1.0476/- 0.0016 in the NTUH population, respectively. All the recalibrated risk equations showed satisfactory calibration (p-values of GND tests ≥ 0.05).
We provide valid risk prediction equations for MI, stroke, and HF outcomes in Taiwanese type 2 diabetes populations. A framework for adapting risk equations across institutions is also proposed.
利用台湾两家医疗机构的跨机构电子健康记录(EHR),通过共同数据模型方法,对 2 型糖尿病患者的心肌梗死(MI)、中风和心力衰竭(HF)风险预测方程进行适应性调整。
分析来自国立成功大学医院(NCKUH;11740 例患者)和台湾大学医院(NTUH;20313 例患者)的 EHR。使用 UKPDS-OM2、RECODe 和 CHIME 模型的 MI、中风和 HF 风险方程进行外部验证和重新校准。外部验证通过(1)接受者操作特征曲线下的面积(AUROC)评估的区分度和(2)通过校准斜率和截距以及 Greenwood-Nam-D'Agostino(GND)检验评估的校准来评估。对校准不理想(GND 检验的 p 值<0.05)的情况进行重新校准,通过调整原始方程的基线风险来解决机构间患者心血管风险的差异。
CHIME 风险方程具有可接受的区分度(AUROC:0.71-0.79)和优于 UKPDS-OM2 和 RECODe 的校准,尽管校准仍然不理想。在重新校准后,CHIME-MI、CHIME-中风和 CHIME-HF 风险方程的校准斜率/截距分别为 NCKUH 人群中的 0.9848/-0.0008、1.1003/-0.0046 和 0.9436/0.0063,以及 NTUH 人群中的 1.1060/-0.0011、0.8714/0.0030 和 1.0476/-0.0016。所有重新校准的风险方程均显示出令人满意的校准(GND 检验的 p 值≥0.05)。
我们为台湾 2 型糖尿病人群提供了 MI、中风和 HF 结局的有效风险预测方程。还提出了一种跨机构适应风险方程的框架。