Comparative adherence trajectories of oral disease-modifying agents in multiple sclerosis.
Comparative adherence trajectories of oral disease-modifying agents in multiple sclerosis.
复制标题
多发性硬化症口腔疾病缓解剂的比较依从轨迹。
DOI：
10.1002/phar.2810
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发表时间：
2023
期刊：
影响因子：
4.1
通讯作者：
Aparasu,RajenderR
中科院分区：
文献类型：
--
作者：
Earla,JagadeswaraRao;Li,Jieni;Hutton,GeorgeJ;Johnson,MichaelL;Aparasu,RajenderR
研究目的本研究比较了芬戈莫德 (FIN)、特立氟胺 (TER) 和富马酸二甲酯 (DMF) 使用者与多发性硬化症 (MS) 的依从轨迹，因为关于不同口腔疾病缓解药物 (DMA) 的比较依从模式的证据有限。设计回顾性队列研究数据源 2015-2019 IBM MarketScan 商业索赔数据库。患者成人（≥ 18 岁） MS（国际疾病分类[ICD]-9/10-临床修改[CM]：340/G35）诊断和≥1个DMA处方。基于DMA指数的干预事件FIN-、TER-或DMF使用，具有1年的清除期。测量一年后使用基于组的轨迹模型（GBTM）检查基于覆盖天数比例（PDC）的DMA依从轨迹治疗开始。基于广义增强模型 (GBM) 的逆概率治疗权重 (IPTW) 被纳入多项 Logistic 回归中，以 FIN 组作为参考类别来评估口腔 DMA 的比较依从轨迹。测量和主要结果研究队列由 1913 名 MS 患者组成，他们开始使用 FIN (24.2%，n= 462)、TER (24.0%，n= 458) 和 DMF (51.9%,n= 993) 2016-2018 年期间。 FIN、TER 和 DMF 用户的依从率 (PDC ≥ 0.8) 分别为 70.8% (n= 327)、59.6% (n= 273) 和 61.0% (n= 606)。 GBTM 将患者分为三种依从性轨迹：完全依从者 — 59.1%、缓慢下降者 — 22.6% 和快速停药者 — 18.3%。涉及基于 GBM 的 IPTW 的多项逻辑回归模型显示，相对于 FIN 用户，DMF（调整后优势比 [aOR]：2.32，95% 置信区间 [CI]：1.57–3.42）和 TER（aOR：2.50，95% CI：1.62–3.88）用户快速停药的几率更高。此外，与 FIN 用户相比，TER 用户更有可能（aOR：1.50，95% CI：1.06-2.13）缓慢下降。结论 与 FIN 相比，特立氟胺和 DMF 与较差的依从性轨迹相关。需要更多的研究来评估这些口服 DMA 依从轨迹的临床意义，以优化 MS 的治疗。
Study ObjectiveThis study compared the adherence trajectories of fingolimod (FIN), teriflunomide (TER), and dimethyl fumarate (DMF) users with multiple sclerosis (MS) as there is limited evidence regarding the comparative adherence patterns of different oral disease‐modifying agents (DMAs).DesignA retrospective cohort studyData Source2015–2019 IBM MarketScan Commercial Claims Database.PatientsAdults (≥18 years) with MS (International Classification of Diseases [ICD]‐9/10‐Clinical Modification [CM]:340/G35) diagnosis and ≥1 DMA prescription.InterventionIncident FIN‐, TER‐, or DMF use based on the index DMA with 1 year of washout period.MeasurementsThe DMA adherence trajectories based on the proportion of days covered (PDC) were examined using the Group‐Based Trajectory Modeling (GBTM) one year after the treatment initiation. Generalized boosting models (GBM)‐based inverse probability treatment weights (IPTW) were incorporated in multinomial logistic regression to assess the comparative adherence trajectories across oral DMAs with FIN group as a reference category.Measurements and Main ResultsThe study cohort consisted of 1913 patients with MS who were initiated with FIN (24.2%,n= 462), TER (24.0%,n= 458), and DMF (51.9%,n= 993) during 2016–2018. The adherence rate (PDC ≥ 0.8) among FIN, TER, and DMF users was found to be 70.8% (n= 327), 59.6% (n= 273), and 61.0% (n= 606), respectively. The GBTM grouped patients into three adherence trajectories: Complete Adherers—59.1%, Slow Decliners—22.6%, and Rapid Discontinuers—18.3%. The multinomial logistic regression model involving GBM‐based IPTW revealed that DMF (adjusted odds ratio [aOR]: 2.32, 95% confidence interval [CI]:1.57–3.42) and TER (aOR: 2.50, 95% CI: 1.62–3.88) users had higher odds to be rapid discontinuers relative to FIN users. In addition, TER users were more likely (aOR: 1.50, 95% CI: 1.06–2.13) to be slow decliners compared with FIN users.ConclusionTeriflunomide and DMF were associated with poorer adherence trajectories than FIN. More research is needed to evaluate the clinical implications of these adherence trajectories of oral DMAs to optimize the management of MS.