Journal of evaluation in clinical practice · 2026
Long-Term Adherence and Drug Utilisation Patterns Among New Users of Anti-Hyperlipidemic Monotherapy: Development of a Risk Prediction Model.
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Li Xuechun, Hak Eelko, Bos Jens H J, Schuiling-Veninga Catharina C M, Mubarik Sumaira
Аннотация
RATIONALE: Real-world long-term adherence and drug patterns are essential in hyperlipidemia management. However, the evidence was unclear.
AIMS AND OBJECTIVES: This study aimed to assess long-term adherence, drug usage patterns of anti-hyperlipidemic monotherapy, associated risk factors, and develop risk prediction models.
METHODS: We performed a retrospective inception cohort study utilising data from the University of Groningen's IADB.nl dispensing database. The study included new users of anti-hyperlipidemic monotherapies-simvastatin, pravastatin, fluvastatin, atorvastatin, rosuvastatin, and fibrates, with approximately a follow-up to 10 years. Using logistic regression, we developed risk prediction models for adherence and drug utilisation patterns, including discontinuation, continuation, switching, and add-on therapies.
RESULTS: Simvastatin users demonstrated high prevalence of high adherence throughout the study (83.6%-90.2%) and had the highest continuation rate (39.2%) with minimal switching or add-on therapy use. Individuals aged 40 and older exhibited better adherence and higher continuation rates. Male patients had lower adherence but higher continuation rates. High adherence was associated with both high continuation and increased switching or add-on therapy use. Patients using diabetes medications had better adherence, higher continuation, and lower switching and add-on rates, whereas those on antiparkinson drugs had lower continuation rates. Recent initiators showed better continuation and lower switching or add-on rates.
CONCLUSIONS: Simvastatin users demonstrated higher adherence and continuation rates compared to other anti-hyperlipidemic monotherapy users. Factors including older age, female sex, and diabetes medications use were associated with improved adherence. Sensitivity analyses using equivalent dosing regimens yielded consistent findings. These insights into adherence and drug patterns are critical for informing personalised strategies to optimise cardiovascular disease prevention.
AIMS AND OBJECTIVES: This study aimed to assess long-term adherence, drug usage patterns of anti-hyperlipidemic monotherapy, associated risk factors, and develop risk prediction models.
METHODS: We performed a retrospective inception cohort study utilising data from the University of Groningen's IADB.nl dispensing database. The study included new users of anti-hyperlipidemic monotherapies-simvastatin, pravastatin, fluvastatin, atorvastatin, rosuvastatin, and fibrates, with approximately a follow-up to 10 years. Using logistic regression, we developed risk prediction models for adherence and drug utilisation patterns, including discontinuation, continuation, switching, and add-on therapies.
RESULTS: Simvastatin users demonstrated high prevalence of high adherence throughout the study (83.6%-90.2%) and had the highest continuation rate (39.2%) with minimal switching or add-on therapy use. Individuals aged 40 and older exhibited better adherence and higher continuation rates. Male patients had lower adherence but higher continuation rates. High adherence was associated with both high continuation and increased switching or add-on therapy use. Patients using diabetes medications had better adherence, higher continuation, and lower switching and add-on rates, whereas those on antiparkinson drugs had lower continuation rates. Recent initiators showed better continuation and lower switching or add-on rates.
CONCLUSIONS: Simvastatin users demonstrated higher adherence and continuation rates compared to other anti-hyperlipidemic monotherapy users. Factors including older age, female sex, and diabetes medications use were associated with improved adherence. Sensitivity analyses using equivalent dosing regimens yielded consistent findings. These insights into adherence and drug patterns are critical for informing personalised strategies to optimise cardiovascular disease prevention.