Terman Samuel W, Kerr Wesley T, Aubert Carole E, Hill Chloe E, Marcum Zachary A, Burke James F
From the Department of Neurology (S.W.T., W.T.K., C.E.H., J.F.B.), and Institute for Healthcare Policy and Innovation (S.W.T., C.E.H., J.F.B.), University of Michigan, Ann Arbor; Department of Neurology (W.T.K.), David Geffen School of Medicine at UCLA, Los Angeles, CA; Department of General Internal Medicine (C.E.A.), Bern University Hospital, and Institute of Primary Health Care (BIHAM) (C.E.A.), University of Bern, Switzerland; and Department of Pharmacy (Z.A.M.), School of Pharmacy, University of Washington, Seattle.
Neurology. 2022 Jan 24;98(4):e427-e436. doi: 10.1212/WNL.0000000000013119.
The objectives of this study were to compare adherence to antiseizure medications (ASMs) vs non-ASMs among individuals with epilepsy, to assess the degree to which variation in adherence is due to differences between individuals vs between medication classes among individuals with epilepsy, and to compare adherence in individuals with vs without epilepsy.
This was a retrospective cohort study using Medicare. We included beneficiaries with epilepsy (≥1 ASM, plus ICD-9-CM diagnostic codes) and a 20% random sample without epilepsy. Adherence for each medication class was measured by the proportion of days covered (PDC) in 2013 to 2015. We used Spearman correlation coefficients, Cohen κ statistics, and multilevel logistic regressions.
There were 83,819 beneficiaries with epilepsy. Spearman correlation coefficients between ASM PDCs and each of the 5 non-ASM PDCs ranged from 0.44 to 0.50; Cohen κ ranged from 0.33 to 0.38; and within-person differences between the PDC of each ASM minus the PDC of each non-ASM were all statistically significant ( < 0.01), although median differences were all very close to 0. Fifty-four percent of variation in adherence across medications was due to differences between individuals. Adjusted predicted probabilities of adherence were as follows: ASMs 74% (95% confidence interval [CI] 73%-74%), proton pump inhibitors 74% (95% CI 74%-74%), antihypertensives 77% (95% CI 77%-78%), selective serotonin reuptake inhibitors 77% (95% CI 77%-78%), statins 78% (95% CI 78%-79%), and levothyroxine 82% (95% CI 81%-82%). Adjusted predicted probabilities of adherenc to non-ASMs were 80% (95% CI 80%-81%) for beneficiaries with epilepsy vs 77% (95% CI 77%-77%) for beneficiaries without epilepsy.
Among individuals with epilepsy, ASM adherence and non-ASM adherence were moderately correlated, half of the variation in adherence was due to between-person rather than between-medication differences, adjusted adherence was slightly lower for ASMs than several non-ASMs, and epilepsy was associated with a quite small increase in adherence to non-ASMs. Nonadherence to ASMs may provide an important cue to the clinician to inquire about adherence to other potentially life-prolonging medications as well. Although efforts should focus on improving ASM adherence, patient-level rather than purely medication-specific behaviors are also critical to consider when developing interventions to optimize adherence.
本研究的目的是比较癫痫患者中抗癫痫药物(ASM)与非抗癫痫药物的依从性,评估癫痫患者依从性差异在个体间差异与药物类别间差异中所占的比例,并比较癫痫患者与非癫痫患者的依从性。
这是一项使用医疗保险数据的回顾性队列研究。我们纳入了患有癫痫的受益人(使用≥1种ASM,加上ICD - 9 - CM诊断代码)以及20%无癫痫的随机样本。每种药物类别的依从性通过2013年至2015年的覆盖天数比例(PDC)来衡量。我们使用了斯皮尔曼相关系数、科恩κ统计量和多水平逻辑回归。
有83,819名患有癫痫的受益人。ASM的PDC与5种非ASM的PDC之间的斯皮尔曼相关系数范围为0.44至0.50;科恩κ范围为0.33至0.38;每种ASM的PDC减去每种非ASM的PDC的个体内差异均具有统计学意义(<0.01),尽管中位数差异都非常接近0。药物依从性的54%的变异是由于个体间差异。调整后的预测依从概率如下:ASM为74%(95%置信区间[CI]73% - 74%),质子泵抑制剂为74%(95%CI 74% - 74%),抗高血压药物为77%(95%CI 77% - 78%),选择性5 - 羟色胺再摄取抑制剂为77%(95%CI 77% - 78%),他汀类药物为78%(95%CI 78% - 79%),左甲状腺素为82%(95%CI 81% - 82%)。癫痫患者中对非ASM的调整后预测依从概率为80%(95%CI 80% - 81%),而非癫痫患者为77%(95%CI 77% - 77%)。
在癫痫患者中,ASM依从性与非ASM依从性呈中度相关,依从性变异的一半是由于个体间差异而非药物间差异,ASM的调整后依从性略低于几种非ASM,癫痫与非ASM依从性的小幅增加相关。不依从ASM可能为临床医生提供一个重要提示,促使其询问患者对其他可能延长生命的药物的依从情况。尽管应努力提高ASM依从性,但在制定优化依从性的干预措施时,患者层面而非单纯药物特异性行为也至关重要。