AUTHOR=Rodríguez-Bernal Clara L. , Sánchez-Saez Francisco , Bejarano-Quisoboni Daniel , Hurtado Isabel , García-Sempere Anibal , Peiró Salvador , Sanfélix-Gimeno Gabriel 

TITLE=Assessing Concurrent Adherence to Combined Essential Medication and Clinical Outcomes in Patients With Acute Coronary Syndrome. A Population-Based, Real-World Study Using Group-Based Trajectory Models

JOURNAL=Frontiers in Cardiovascular Medicine

VOLUME=Volume 9 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/cardiovascular-medicine/articles/10.3389/fcvm.2022.863876

DOI=10.3389/fcvm.2022.863876

ISSN=2297-055X

ABSTRACT=Aims: Adherence to multiple medications recommended for secondary prevention of cardiovascular conditions represents a challenge. We aimed to identify patterns of concurrent adherence to combined therapy and assess their impact on clinical outcomes in a cohort of patients with acute coronary syndrome (ACS). 
Methods: Population-based retrospective cohort of all patients discharged after hospitalization for ACS (2009-2011), prescribed ≥3 therapeutic groups within the first month. We assessed monthly concurrent adherence (≥24 days of medication out of 30) to ≥3 medications during the first year, and patterns were identified through group-based trajectory models. A composite clinical outcome during the second year was constructed. The association between adherence patterns -and traditional refill adherence metrics (e.g. Proportion of Days Covered)-  and outcomes was assessed through a multivariable Cox proportional hazards model. 
Results: Among 15,797 patients discharged alive, 12,057 (76.32%) initiated treatment with ≥3therapeutic groups after discharge. We identified seven adherence trajectories to ≥3medications: Adherent (52.94% of patients); Early Gap (6.64%); Middle Gap (5.67%); Late decline (10.93%); Occasional Users (5.45%); Early Decline (8.79%) and Non-Adherent (9.58%). Compared to the Adherent group, patients belonging to Early Gap (HR:1.30, 95%CI 1.07;1.60), Late decline (HR:1.31, 95%CI 1.10;1.56), and Non-Adherent trajectories (HR:1.36, 95%CI 1.14;1.63) had a greater risk of adverse clinical outcomes which also was different to the risk ascertained through concurrent PDC<80 (HR:1.13,95%CI 1.01;1.27). 
Conclusion: Seven adherence trajectories to ≥3 drugs were identified, three distinct adherence patterns being at higher risk of adverse outcomes. The identification of patterns of concurrent adherence, a more comprehensive approach than traditional measurements, may be useful to target interventions to improve adherence to multiple medications.