BACKGROUND: An essential contribution regarding the prevention of thromboembolic events in patients with (non-valvular) atrial fibrillation (AF) is good adherence to direct oral anticoagulants (DOACs). However, it is an open question what "good" adherence means for DOACs or below which threshold non-adherence is clinically relevant for AF patients. Ultimately, such a classification could prevent strokes and associated costs through adjusted treatment regimens or supportive measures. METHODS: We selected 10,092 AF patients from health insurance claims data between 2014 and 2018 who were issued a majority (at least half of the number) of maximum approved strength prescriptions of one of the following DOACs, namely rivaroxaban, apixaban, or dabigatran. Due to the limited sample size, the prescriptions of dabigatran had to be finally excluded for the cut-off analysis. DOAC adherence was calculated as the proportion of days covered (PDC) by dividing the days of theoretical use (days covered) of the drug by the duration in days of the observation interval. PDC cut-off values were derived from stroke risk as a function of continuous PDC values in time-to-event analyses and corresponding dose-response models. The influence of adherence-promoting interventions (targeted and untargeted) on the occurrence of strokes and related costs was then projected, considering intervention costs per patient. RESULTS: The population had a mean age of 74.5 years and 50% were female. The median PDC was 0.79 ± 0.28 with a median follow-up time of 1218 days, in which 2% of all DOAC patients had a stroke. The adherence cut-offs for good adherence were identified at 0.78 for rivaroxaban and 0.8 for apixaban. Targeted interventions appeared to be far more cost-effective than untargeted interventions. CONCLUSION: Clear adherence cut-offs enable healthcare professionals to identify patients with clinically relevant non-adherence. Interventions based on these cut-offs appear to be a promising means to optimize DOAC treatment.
BACKGROUND: An essential contribution regarding the prevention of thromboembolic events in patients with (non-valvular) atrial fibrillation (AF) is good adherence to direct oral anticoagulants (DOACs). However, it is an open question what "good" adherence means for DOACs or below which threshold non-adherence is clinically relevant for AF patients. Ultimately, such a classification could prevent strokes and associated costs through adjusted treatment regimens or supportive measures. METHODS: We selected 10,092 AF patients from health insurance claims data between 2014 and 2018 who were issued a majority (at least half of the number) of maximum approved strength prescriptions of one of the following DOACs, namely rivaroxaban, apixaban, or dabigatran. Due to the limited sample size, the prescriptions of dabigatran had to be finally excluded for the cut-off analysis. DOAC adherence was calculated as the proportion of days covered (PDC) by dividing the days of theoretical use (days covered) of the drug by the duration in days of the observation interval. PDC cut-off values were derived from stroke risk as a function of continuous PDC values in time-to-event analyses and corresponding dose-response models. The influence of adherence-promoting interventions (targeted and untargeted) on the occurrence of strokes and related costs was then projected, considering intervention costs per patient. RESULTS: The population had a mean age of 74.5 years and 50% were female. The median PDC was 0.79 ± 0.28 with a median follow-up time of 1218 days, in which 2% of all DOAC patients had a stroke. The adherence cut-offs for good adherence were identified at 0.78 for rivaroxaban and 0.8 for apixaban. Targeted interventions appeared to be far more cost-effective than untargeted interventions. CONCLUSION: Clear adherence cut-offs enable healthcare professionals to identify patients with clinically relevant non-adherence. Interventions based on these cut-offs appear to be a promising means to optimize DOAC treatment.
Authors: Abdulaali R Almutairi; Lili Zhou; Walid F Gellad; Jeannie K Lee; Marion K Slack; Jennifer R Martin; Wei-Hsuan Lo-Ciganic Journal: Clin Ther Date: 2017-06-28 Impact factor: 3.393
Authors: L Staerk; T A Gerds; G Y H Lip; B Ozenne; A N Bonde; M Lamberts; E L Fosbøl; C Torp-Pedersen; G H Gislason; J B Olesen Journal: J Intern Med Date: 2017-09-21 Impact factor: 8.989
Authors: Maxim Grymonprez; Andreas Capiau; Stephane Steurbaut; Els Mehuys; Koen Boussery; Tine L De Backer; Lies Lahousse Journal: Front Cardiovasc Med Date: 2022-09-29