Real-World Dispensing Patterns of Inhalation Medication in Young Adult Asthma: An Inception Cohort Study.

IF 3.4 2区医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH Clinical Epidemiology Pub Date : 2023-01-01 DOI:10.2147/CLEP.S410036

Irene Mommers, Job F M van Boven, Catharina C M Schuiling-Veninga, Jens H J Bos, Marten Koetsier, Eelko Hak, Maarten J Bijlsma

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Abstract

Purpose: The Global Initiative for Asthma (GINA) suggests a step-wise approach for pharmacological treatment of asthma. Valid study of real-world treatment patterns using dispensing databases includes proper measurement of medication adherence. We aim to explore such patterns by applying a time-varying proportion of days covered (tPDC)-based algorithm.

Patients and methods: We designed a retrospective inception cohort study using the University of Groningen IADB.nl community pharmacy dispensing database. Included were 19,184 young adults who initiated asthma medication anywhere between 1994 and 2021, in the Netherlands. Main treatment steps were defined as: 1 - SABA/ICS-formoterol as needed, 2 - low dose ICS, 3 - low dose ICS + LABA or tiotropium, or intermediate dose ICS, 4 - intermediate to high dose ICS + LABA or tiotropium, triple therapy, or high dose ICS, 5 - treatment prescribed by a specialist. Changes in treatment steps were determined using a time-varying proportion of days covered (tPDC)-based algorithm. Individual drug treatment trajectories were visualized over time using a lasagna plot.

Results: At initiation, of the 19,184 included individuals, 52%, 7%, 15%, 16%, and 10% started treatment in steps 1 to 5, respectively. The median (IQR) follow-up time was 3 (1-7) years. Median (IQR) number of switches was 1 (0-3). Comparing starting step to last observed step, 37% never switched between treatment steps, 20% of individuals stepped down and 22% stepped up.

Conclusion: The low proportion of treatment switches between steps indicates that tailoring of treatment to patients' needs might be suboptimal. The tPDC-based algorithm functions well in translating dispensing data into continuous drug-utilization data, enabling a more granular assessment of treatment patterns among asthma patients.

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青少年哮喘患者吸入药物的实际分配模式:一项初始队列研究。

目的:全球哮喘倡议(GINA)提出了一种循序渐进的哮喘药物治疗方法。使用配药数据库对真实世界的治疗模式进行有效的研究，包括对药物依从性的适当测量。我们的目标是通过应用基于时间变化的覆盖天数比例(tPDC)的算法来探索这种模式。患者和方法:我们使用格罗宁根大学IADB设计了一项回顾性初始队列研究。社区药房调剂数据库。其中包括荷兰在1994年至2021年间开始服用哮喘药物的19184名年轻人。主要治疗步骤定义为:1 - SABA/ICS-福莫特罗根据需要，2 -低剂量ICS, 3 -低剂量ICS + LABA或噻托溴铵，或中剂量ICS, 4 -中高剂量ICS + LABA或噻托溴铵，三联治疗，或高剂量ICS, 5 -专家规定的治疗。使用基于时变天数比例(tPDC)的算法确定治疗步骤的变化。个体药物治疗轨迹随着时间的推移使用千层面图可视化。结果:在开始时，19184名纳入的个体中，分别有52%，7%，15%，16%和10%在步骤1至5中开始治疗。中位(IQR)随访时间为3(1-7)年。开关中位数(IQR)为1(0-3)。将开始步骤与最后观察步骤进行比较，37%的人从未在治疗步骤之间切换，20%的人降级，22%的人升级。结论:低比例的治疗切换之间的步骤表明，量身定制的治疗，以病人的需要可能是不理想的。基于tpdc的算法可以很好地将调剂数据转换为连续的药物利用数据，从而对哮喘患者的治疗模式进行更细致的评估。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Clinical Epidemiology Medicine-Epidemiology

CiteScore

6.30

自引率

5.10%

发文量

169

审稿时长

16 weeks

期刊介绍： Clinical Epidemiology is an international, peer reviewed, open access journal. Clinical Epidemiology focuses on the application of epidemiological principles and questions relating to patients and clinical care in terms of prevention, diagnosis, prognosis, and treatment. Clinical Epidemiology welcomes papers covering these topics in form of original research and systematic reviews. Clinical Epidemiology has a special interest in international electronic medical patient records and other routine health care data, especially as applied to safety of medical interventions, clinical utility of diagnostic procedures, understanding short- and long-term clinical course of diseases, clinical epidemiological and biostatistical methods, and systematic reviews. When considering submission of a paper utilizing publicly-available data, authors should ensure that such studies add significantly to the body of knowledge and that they use appropriate validated methods for identifying health outcomes. The journal has launched special series describing existing data sources for clinical epidemiology, international health care systems and validation studies of algorithms based on databases and registries.