切换到第二品牌阿托伐他汀:一个6个月的回顾性队列,现实世界研究。

IF 1.9 Q3 PHARMACOLOGY & PHARMACY
Panisa Manasirisuk, Somsak Tiamkao, Chaiyasith Wongvipaporn, Nanthaphan Chainirun, Kittisak Sawanyawisuth
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引用次数: 0

摘要

高水平的低密度脂蛋白-胆固醇(LDL)是心血管疾病的主要危险因素。虽然用阿托伐他汀治疗是有益的,但对一些患者来说,最初的阿托伐他汀可能成本过高。目前,市场上有第二个品牌的阿托伐他汀。本研究旨在评价阿托伐他汀第二个仿制品牌的有效性。方法:这是一项在泰国孔敬大学医院进行的回顾性队列研究。纳入标准是接受Xarator®(原始阿托伐他汀;辉瑞制药公司(波多黎各)或阿托伐他汀山德士®(Lek制药公司,斯洛文尼亚)至少3个月,然后切换到第二个品牌:Lipostat®(暹罗制药公司,泰国)。研究期间为2022年4月1日至2023年6月30日。该研究的主要结局是在从原始(Xarator®)或仿制阿托伐他汀(阿托伐他汀山德士®)转换治疗后6个月LDL的变化。结果:683例患者从原始阿托伐他汀(Xarator®)切换治疗,1044例患者从仿制阿托伐他汀(阿托伐他汀山德士®)切换治疗,总计1727例患者。关于LDL水平,从最初的阿托伐他汀(Xarator®)转换治疗导致LDL在6个月时略有降低但不显著降低(- 0.96 mg/dL;95% CI为- 3.20,1.28),而从通用阿托伐他汀(阿托伐他汀山德士®)转换治疗导致LDL显著降低至- 3.30 mg/dL (95% CI为- 5.25,- 1.36)。原始(Xarator®)和仿制阿托伐他汀(阿托伐他汀山德士®)组也导致肾小球滤过率的估计显著降低,分别为- 0.90和- 1.21 mL/min/1.73 m2。结论:第二种阿托伐他汀(Lipostat®)与最初的阿托伐他汀(Xarator®)相比,LDL的结果相当,但在转换治疗后6个月,LDL水平明显低于另一种阿托伐他汀(阿托伐他汀山德士®)。然而,肾功能应密切监测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Switching Therapy to the Second Brand of Generic Atorvastatin: A 6-Month Retrospective Cohort, Real-World Study.

Introduction: High levels of low-density lipoprotein-cholesterol (LDL) is a major risk factor for cardiovascular diseases. While treatment with atorvastatin is beneficial, the original atorvastatin may be cost prohibitive to some patients. Currently, a second brand of generic atorvastatin is available on the market. This study aimed to evaluate the effectiveness of the second generic brand of atorvastatin.

Methods: This was a retrospective cohort study conducted at Khon Kaen University Hospital, Thailand. The inclusion criteria were adult patients who received either Xarator® (original atorvastatin; Pfizer Pharmaceuticals, Puerto Rico) or Atorvastatin Sandoz® (Lek Pharmaceuticals, Slovenia) for at least 3 months prior to switching therapy to the second brand: Lipostat® (Siam Pharmaceutical, Thailand). The study period was between 1 April 2022 and 30 June 2023. The primary outcome of this study was a change in LDL 6 months after switching therapy from either the original (Xarator®) or generic atorvastatin (Atorvastatin Sandoz®).

Results: There were 683 patients who switched therapy from the original atorvastatin (Xarator®), and 1044 patients who switched therapy from generic atorvastatin (Atorvastatin Sandoz®), for a total of 1727 patients. Regarding LDL levels, switching therapy from original atorvastatin (Xarator®) resulted in a slightly lower but not significant decrease in LDL at 6 months (- 0.96 mg/dL; 95% CI of - 3.20, 1.28), while switching therapy from generic atorvastatin (Atorvastatin Sandoz®) led to significantly lower LDL at - 3.30 mg/dL (95% CI of - 5.25, - 1.36). The original (Xarator®) and generic atorvastatin (Atorvastatin Sandoz®) group also resulted in a significantly lower estimated glomerular filtration rate at - 0.90 and - 1.21 mL/min/1.73 m2, respectively, from baseline.

Conclusions: The second generic atorvastatin (Lipostat®) resulted in comparable outcomes on LDL compared with the original (Xarator®), but significantly lower LDL levels than another generic atorvastatin (Atorvastatin Sandoz®) 6 months after switching therapy. However, renal function should be closely monitored.

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来源期刊
Drugs - Real World Outcomes
Drugs - Real World Outcomes PHARMACOLOGY & PHARMACY-
CiteScore
3.60
自引率
5.00%
发文量
49
审稿时长
8 weeks
期刊介绍: Drugs - Real World Outcomes targets original research and definitive reviews regarding the use of real-world data to evaluate health outcomes and inform healthcare decision-making on drugs, devices and other interventions in clinical practice. The journal includes, but is not limited to, the following research areas: Using registries/databases/health records and other non-selected observational datasets to investigate: drug use and treatment outcomes prescription patterns drug safety signals adherence to treatment guidelines benefit : risk profiles comparative effectiveness economic analyses including cost-of-illness Data-driven research methodologies, including the capture, curation, search, sharing, analysis and interpretation of ‘big data’ Techniques and approaches to optimise real-world modelling.
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