Generic substitution of amlodipine is not associated with increased risk of mortality or adverse cardiovascular events: An observational cohort study.
Boya ZhaoJing WuChengzhi LuXing Lin FengPublished in: Clinical and translational science (2024)
This study aims to assess clinical outcomes following switching from originator to generic amlodipine. This population-based, matched, cohort study included users of originator amlodipine using claims data during 2018-2020 from a health system in Tianjin, China, in which usage of generic amlodipine was promoted by a drug procurement policy, the national volume-based procurement. Non-switchers refer to those remained on originator after the policy, while pure-switchers were those who switched to and continued using generic amlodipine, and back-switchers were those switched to generic amlodipine but then back to the originator. Propensity score matching generates comparable non-switchers and pure-switchers pairs, and non-switchers and back-switchers pairs. The primary outcome was major adverse cardiovascular events (MACEs), defined as all-cause mortality, stroke, and myocardial infarction during follow-up (April 1, 2019 to December 30, 2020). Secondary outcomes included heart failure, atrial fibrillation, and adherence to amlodipine. The hazard ratio (HR) for each clinical outcome was assessed through Cox proportional hazard regression. In total, 5943 non-switchers, 2949 pure-switchers, and 3061 back-switchers were included (mean age: 62.9 years; 55.5% men). For the matched pairs, pure-switchers (N = 2180) presented no additional risks of clinical outcomes compared to non-switchers (N = 4360) (e.g., MACEs: 2.86 vs. 2.95 events per 100 person-years; HR = 0.97 [95%CI: 0.70-1.33]). Back-switchers (N = 1998) also presented no additional risk compared to non-switchers (N = 3996) for most outcomes except for stroke (HR = 1.55 [95%CI: 1.03-2.34]). Pure-switchers and back-switchers all had better amlodipine adherence than non-switchers. Generic substitution of amlodipine is not associated with increased risk of cardiovascular events or all-cause mortality, but improves medicine adherence.
Keyphrases
- cardiovascular events
- atrial fibrillation
- coronary artery disease
- heart failure
- hypertensive patients
- cardiovascular disease
- healthcare
- public health
- type diabetes
- left ventricular
- emergency department
- risk assessment
- machine learning
- acute coronary syndrome
- left atrial
- metabolic syndrome
- insulin resistance
- adipose tissue
- deep learning
- venous thromboembolism
- mitral valve
- human health
- glycemic control
- direct oral anticoagulants
- drug induced