糖化血红蛋白的 visit-to-visit 变异性与药物依从性的关联。
Association of visit-to-visit variability of hemoglobin A1c and medication adherence.
机构信息
Boston University School of Medicine, 801 Massachusetts Ave., Crosstown Center, 2nd Fl., Boston, MA 02118.
出版信息
J Manag Care Spec Pharm. 2015 Mar;21(3):229-37. doi: 10.18553/jmcp.2015.21.3.229.
BACKGROUND
Medication nonadherence is widespread, but there are few efficient means of detecting medication nonadherence at the point of care. Visit-to-visit variability in clinical biomarkers has shown inconsistent efficiency to predict medication adherence.
OBJECTIVE
To examine the performance of visit-to-visit variability (VVV) of hemoglobin A1c to predict nonadherence to antidiabetic medications.
METHODS
In this cross-sectional study using a clinical and administrative database, adult members of a managed care plan at a safety-net medical center from 2008 to 2012 were included if they had ≥ 3 noninsulin antidiabetic prescription fills within the same class and ≥ 3 A1c measurements between the first and last prescription fills. The independent variable was VVV of A1c (within-subject standard deviation of A1c), and the dependent variable was medication adherence (defined by medication possession ratio) determined from pharmacy claims. Unadjusted and adjusted multivariate logistic regression models were created to examine the relationship between VVV of A1c and medication nonadherence. Receiver-operating characteristic (ROC) curves assessed the performance of the adjusted model at discriminating adherence from nonadherence.
RESULTS
Among 632 eligible subjects, mean A1c was 7.7% ± 1.3%, and 83% of the sample was nonadherent to antidiabetic medications. Increasing quintiles of VVV of A1c and medication nonadherence were both associated with increased within-subject mean A1c and younger subject age. The logistic regression model (adjusted for age, sex, race/ethnicity, within-subject mean A1c, number of A1c measurements, number of days between the first and last antidiabetic medication prescription fills, and rate of primary care visits during the study period) showed a nonsignificant association of VVV of A1c and medication nonadherence (OR = 1.19, 95% CI = 0.42-3.38 for the highest quintile of VVV). Adding VVV of A1c to a model including age, sex, and race only modestly improved the C-statistic of the ROC curve from 0.6786 to 0.7064.
CONCLUSIONS
VVV of A1c is not a robust predictor of antidiabetic medication nonadherence. Further innovation is needed to develop novel methods of detecting nonadherence.
背景
药物依从性普遍存在，但在护理点检测药物依从性的有效方法却很少。临床生物标志物的随访间变异性已显示出预测药物依从性的效率不一致。
目的
研究血红蛋白 A1c 的随访间变异性（VVV）预测抗糖尿病药物不依从性的表现。
方法
本研究使用临床和行政数据库进行横断面研究，纳入 2008 年至 2012 年期间在一家医疗中心的管理式医疗计划中具有≥3 次同类型非胰岛素抗糖尿病药物处方和≥3 次 A1c 测量（在首次和最后一次处方之间）的成年成员。自变量为 A1c 的随访间变异性（A1c 的个体内标准差），因变量为从药房索赔中确定的药物依从性（定义为药物占有比）。使用未调整和调整后的多元逻辑回归模型来检查 A1c 的 VVV 与药物不依从性之间的关系。接收者操作特征（ROC）曲线评估了调整模型在区分依从性与不依从性方面的性能。
结果
在 632 名合格的研究对象中，平均 A1c 为 7.7%±1.3%，83%的样本对抗糖尿病药物不依从。A1c 随访间变异性和药物不依从性的五分位数增加均与个体内平均 A1c 增加和研究对象年龄减小有关。逻辑回归模型（调整年龄、性别、种族/民族、个体内平均 A1c、A1c 测量次数、首次和最后一次抗糖尿病药物处方之间的天数以及研究期间的初级保健就诊率）显示 A1c 的 VVV 与药物不依从性之间无显著关联（OR=1.19，95%CI=0.42-3.38，VVV 最高五分位数）。将 A1c 的 VVV 添加到仅包含年龄、性别和种族的模型中，ROC 曲线的 C 统计量仅从 0.6786 适度提高到 0.7064。
结论
A1c 的 VVV 不是抗糖尿病药物不依从性的可靠预测指标。需要进一步创新以开发检测不依从性的新方法。
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