• 1. Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing 100091, P. R. China;
  • 2. Beijing University of Chinese Medicine, Beijing 100029, P. R. China;
  • 3. Beijing Tongrentang Research Institute, Beijing Tongrentang Medical Care Investment Co., Ltd., Beijing 100062, P. R. China;
LU Yan, Email: 13661311325@139.com
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Objective To conduct pharmacovigilance signal mining and safety analysis of losartan potassium based on the FDA adverse event reporting system (FAERS) database, providing references for rational clinical drug use. Methods The study collected adverse event reports from the FAERS database from the first quarter of 2004 to the first quarter of 2024. After data cleaning and de-duplication, reports with losartan potassium as the main suspected drug were selected. Adverse events were coded and classified using the preferred term (PT) and system organ class (SOC) in the medical dictionary for regulatory activities (MedDRA). Two non-Bayesian methods, reporting odds ratio (ROR) and proportional reporting ratio (PRR), were used for signal detection, and the generated effective signals needed to meet specific statistical thresholds. Additionally, subgroup analyses based on age and weight were conducted, and descriptive statistics and Weibull distribution tests were performed on the time-to-onset (TTO) to analyze the risk pattern over time. Results A total of 11 175 adverse event reports with losartan potassium as the main suspected drug were identified. Female reporters were more than male (55.8% vs. 35.6%), and the majority of patients were aged 65-85 years (32.3%). A total of 369 effective adverse event signals were generated, involving 27 SOC. The most frequent system organ categories for adverse events included nervous system disorders, various examinations, and gastrointestinal disorders. In terms of signal strength, vascular diseases and metabolic and nutritional disorders showed the strongest association signals. At the preferred term level, dizziness, elevated blood pressure, and hypertension had the highest reporting frequencies, among which heart failure was a significant signal not mentioned in the drug instructions. Subgroup analysis showed that the signal strength of hyponatremia was higher in elderly patients (>80 years old). The median time to onset of adverse events was 106 days, with most events concentrated within one month and one year after medication. The Weibull distribution test (shape parameter β=0.62, 95%CI 0.61 to 0.64) indicated that the overall risk decreased over time (early failure type). Conclusion This study confirmed the known adverse reactions of losartan potassium (such as dizziness and hyperkalemia) through large-scale real-world data and revealed potential risk signals (such as heart failure and hyponatremia in specific populations). The analysis of medication time provided a basis for monitoring key time points in clinical practice. It is recommended that clinicians pay particular attention to high-risk patients such as the elderly and those on combination therapy when using losartan potassium, and strengthen the monitoring of blood potassium, blood sodium, and renal function, as well as be vigilant about the risk of adverse events in the early and long-term use.

Citation: JIAO Kaiyu, LU Yueyang, LU Yan. Mining and analysis of adverse reaction signals of losartan potassium: based on the FAERS database. Chinese Journal of Evidence-Based Medicine, 2026, 26(5): 524-532. doi: 10.7507/1672-2531.202510097 Copy

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