Department of Neurology, The First Affiliated Hospital, Jinan University, Guangzhou, Guangdong 510632, China.
Guangdong Geriatrics Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong 510080, China.
Chin Med J (Engl). 2019 May 5;132(9):1053-1062. doi: 10.1097/CM9.0000000000000210.
High on-treatment platelet reactivity (HTPR) has been suggested as a risk factor for patients with ischemic vascular disease. We explored a predictive model of platelet reactivity to clopidogrel and the relationship with clinical outcomes.
A total of 441 patients were included. Platelet reactivity was measured by light transmittance aggregometry after receiving dual antiplatelet therapy. HTPR was defined by the consensus cutoff of maximal platelet aggregation >46% by light transmittance aggregometry. CYP2C19 loss-of-function polymorphisms were identified by DNA microarray analysis. The data were compared by binary logistic regression to find the risk factors. The primary endpoint was major adverse clinical events (MACEs), and patients were followed for a median time of 29 months. Survival curves were constructed with Kaplan-Meier estimates and compared by log-rank tests between the patients with HTPR and non-HTPR.
The rate of HTPR was 17.2%. Logistic regression identified the following predictors of HTPR: age, therapy regimen, body mass index, diabetes history, CYP2C192, or CYP2C193 variant. The area under the curve of receiver operating characteristic for the HTPR predictive model was 0.793 (95% confidence interval: 0.738-0.848). Kaplan-Meier analysis showed that patients with HTPR had a higher incidence of MACE than those with non-HTPR (21.1% vs. 9.9%; χ = 7.572, P = 0.010).
Our results suggest that advanced age, higher body mass index, treatment with regular dual antiplatelet therapy, diabetes, and CYP2C192 or CYP2C193 carriers are significantly associated with HTPR to clopidogrel. The predictive model of HTPR has useful discrimination and good calibration and may predict long-term MACE.
高血小板反应性（HTPR）已被认为是缺血性血管疾病患者的一个危险因素。我们探讨了一种预测氯吡格雷血小板反应性的模型及其与临床结局的关系。
共纳入 441 例患者。在接受双联抗血小板治疗后，通过光透射聚集法测量血小板反应性。高血小板反应性定义为光透射聚集最大血小板聚集率>46%的共识截止值。通过 DNA 微阵列分析确定 CYP2C19 失活功能多态性。通过二元逻辑回归比较数据，以找到危险因素。主要终点为主要不良临床事件（MACEs），并对患者进行了中位数为 29 个月的随访。Kaplan-Meier 估计构建生存曲线，并通过对数秩检验比较 HTPR 患者与非 HTPR 患者之间的生存曲线。
HTPR 发生率为 17.2%。逻辑回归确定了 HTPR 的以下预测因素：年龄、治疗方案、体重指数、糖尿病史、CYP2C192 或 CYP2C193 变异。HTPR 预测模型的曲线下面积为 0.793（95%置信区间：0.738-0.848）。Kaplan-Meier 分析显示，HTPR 患者的 MACE 发生率高于非 HTPR 患者（21.1%比 9.9%；χ=7.572，P=0.010）。
我们的研究结果表明，年龄较大、体重指数较高、常规双联抗血小板治疗、糖尿病以及 CYP2C192 或 CYP2C193 携带者与氯吡格雷的 HTPR 显著相关。HTPR 的预测模型具有良好的区分度和校准度，可预测长期 MACE。
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