Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, 250012, Shandong, China; Healthcare Big Data Research Institute, Cheeloo College of Medicine, Shandong University, Jinan, 250012, Shandong, China.
Qingdao Huangdao District Center for Disease Control and Prevention, Qingdao, 266400, Shandong, China.
Atherosclerosis. 2021 Mar;320:24-30. doi: 10.1016/j.atherosclerosis.2021.01.005. Epub 2021 Jan 12.
Few studies estimated the impact of antihypertensive adherence on cardiovascular diseases (CVD) in a longitudinal cohort with presence of time-dependent confounders. This study aims to assess the association between antihypertensive adherence and CVD using marginal structural Cox model (MSM-Cox) and to characterize blood pressure (BP) trajectories of patients with different adherence.
This longitudinal study included 16,896 hypertensive patients receiving antihypertensive medication. The median follow-up time was 3.5 years (25th to 75th, 1.75-4.75 years). BP and medication adherence were measured four times every year. We used MSM-Cox and Cox model to assess association between antihypertensive adherence and CVD events. The linear mixed-effects model was used to characterize BP trajectories of patients with different adherence, and the area under curves (AUC) was calculated as BP burden.
We documented 4735 CVD events, crude incidence of CVD was 80.8 (95% CI, 78.1-83.4) and 112.6 (95% CI, 107.2-118.0) per 1000 person-years for baseline high-adherence and low-adherence, respectively. Compared with high adherence, the adjusted hazard ratio (HR) for association between low adherence with CVD was 1.75 (95%CI, 1.62-1.89) and 1.34 (95%CI, 1.26-1.42) based on the MSM-Cox and the Cox model, respectively. The BP burden and fluctuation range of BP trajectory in low-adherence patients were larger than those of high-adherence patients. Patients with high adherence got 28% greater reduction of BP burden than low-adherence patients.
Antihypertensive adherence was more strongly associated with the risk of CVD than conventional regression analyses based on a single adherence measurement.
很少有研究在存在时间依赖性混杂因素的纵向队列中，估计降压药物依从性对心血管疾病 (CVD) 的影响。本研究旨在使用边缘结构 Cox 模型 (MSM-Cox) 评估降压药物依从性与 CVD 之间的关联，并描述不同依从性患者的血压 (BP) 轨迹特征。
本纵向研究纳入了 16896 名接受降压药物治疗的高血压患者。中位随访时间为 3.5 年（25 至 75 分位，1.75 至 4.75 年）。每年测量 4 次 BP 和药物依从性。我们使用 MSM-Cox 和 Cox 模型评估降压药物依从性与 CVD 事件之间的关联。使用线性混合效应模型描述不同依从性患者的 BP 轨迹特征，并计算曲线下面积 (AUC) 作为 BP 负担。
我们记录了 4735 例 CVD 事件，基线高依从性和低依从性患者的 CVD 粗发生率分别为 80.8（95%CI，78.1-83.4）和 112.6（95%CI，107.2-118.0）/1000 人年。与高依从性相比，低依从性与 CVD 相关的调整后危险比 (HR) 分别为 1.75（95%CI，1.62-1.89）和 1.34（95%CI，1.26-1.42），基于 MSM-Cox 和 Cox 模型。低依从性患者的 BP 负担和 BP 轨迹波动范围大于高依从性患者。高依从性患者的 BP 负担降低幅度比低依从性患者大 28%。
与基于单次依从性测量的传统回归分析相比，降压药物依从性与 CVD 风险的相关性更强。
