TY - JOUR
T1 - Real-World Dispensing Patterns of Inhalation Medication in Young Adult Asthma
T2 - An Inception Cohort Study
AU - Mommers, Irene
AU - van Boven, Job F M
AU - Schuiling-Veninga, Catharina C M
AU - Bos, Jens H J
AU - Koetsier, Marten
AU - Hak, Eelko
AU - Bijlsma, Maarten J
N1 - © 2023 Mommers et al.
PY - 2023/6/22
Y1 - 2023/6/22
N2 - 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.
AB - 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.
KW - ASTHMA
KW - MEDICATION ADHERENCE
KW - BIG DATA
KW - REAL-WORLD
U2 - 10.2147/CLEP.S410036
DO - 10.2147/CLEP.S410036
M3 - Article
C2 - 37337562
SN - 1179-1349
VL - 15
SP - 721
EP - 732
JO - Clinical epidemiology
JF - Clinical epidemiology
ER -