Phenotypic heterogeneity among patients with type 2 diabetes mellitus (T2DM) and atherosclerotic cardiovascular disease (ASCVD) is ill defined. We used cluster analysis machine-learning algorithms to identify phenotypes among trial participants with T2DM and ASCVD.

We used data from the Trial Evaluating Cardiovascular Outcomes with Sitagliptin (TECOS) study (n = 14,671), a cardiovascular outcome safety trial comparing sitagliptin with placebo in patients with T2DM and ASCVD (median follow-up 3.0 years). Cluster analysis using 40 baseline variables was conducted, with associations between clusters and the primary composite outcome (cardiovascular death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for unstable angina) assessed by Cox proportional hazards models. We replicated the results using the Exenatide Study of Cardiovascular Event Lowering (EXSCEL) trial.

Four distinct phenotypes were identified: cluster I included Caucasian men with a high prevalence of coronary artery disease; cluster II included Asian patients with a low BMI; cluster III included women with noncoronary ASCVD disease; and cluster IV included patients with heart failure and kidney dysfunction. The primary outcome occurred, respectively, in 11.6%, 8.6%, 10.3%, and 16.8% of patients in clusters I to IV. The crude difference in cardiovascular risk for the highest versus lowest risk cluster (cluster IV vs. II) was statistically significant (hazard ratio 2.74 [95% CI 2.29–3.29]). Similar phenotypes and outcomes were identified in EXSCEL.

In patients with T2DM and ASCVD, cluster analysis identified four clinically distinct groups. Further cardiovascular phenotyping is warranted to inform patient care and optimize clinical trial designs.

2 型糖尿病 (T2DM) 和动脉粥样硬化性心血管疾病 (ASCVD) 患者的表型异质性尚不明确。我们使用聚类分析机器学习算法来识别患有 T2DM 和 ASCVD 的试验参与者的表型。

我们使用了西格列汀心血管结果评估试验 (TECOS) 研究 ( n = 14,671) 的数据，该研究是一项在 T2DM 和 ASCVD 患者中比较西他列汀与安慰剂的心血管结果安全性试验（中位随访 3.0 年）。使用 40 个基线变量进行聚类分析，通过 Cox 比例风险模型评估聚类与主要复合结局（心血管死亡、非致命性心肌梗塞、非致命性中风或不稳定心绞痛住院）之间的关联。我们使用艾塞那肽降低心血管事件研究 (EXSCEL) 试验重复了结果。

确定了四种不同的表型：I 组包括冠状动脉疾病患病率较高的白人男性；第二组包括体重指数较低的亚洲患者；第三组包括患有非冠状动脉 ASCVD 疾病的女性；第四组包括患有心力衰竭和肾功能障碍的患者。主要结局发生在 I 至 IV 组的患者中，分别为 11.6%、8.6%、10.3% 和 16.8%。最高风险组与最低风险组（IV 组与 II 组）心血管风险的粗略差异具有统计学意义（风险比 2.74 [95% CI 2.29–3.29]）。 EXSCEL 中发现了类似的表型和结果。

在 T2DM 和 ASCVD 患者中，聚类分析确定了四个临床上不同的组。需要进一步的心血管表型分析来为患者护理提供信息并优化临床试验设计。