Estimating Adverse Events Associated With Herbal Medicines Using Pharmacovigilance Databases: Systematic Review and Meta-Analysis (Preprint)

Abstract

Herbal medicines (HMs) are extensively used by consumers/patients worldwide. However, their safety profiles are often poorly reported and characterized. Previous studies have documented adverse events (AEs) associated with HMs, such as hepatotoxicity, renal failure, and allergic reactions. However, the prevalence rate of AEs related to HMs has been reported to be low. To date, no systematic review and meta-analysis has comprehensively analyzed the AEs of HMs using published data acquired from pharmacovigilance (PV) databases.

This study aimed to (1) estimate the reporting rate of the AEs of HMs using PV databases and (2) assess the detailed data provided in AE reports.

In this systematic review and meta-analysis, MEDLINE/PubMed, SCOPUS, EMBASE, and CINAHL were systematically searched for relevant studies (until December 2023). The DerSimonian-Laird random effects model was used for pooling the data, and subgroup analyses, the meta-regression model, and sensitivity analysis were used to explore the source of heterogeneity. Crombie’s checklist was used to evaluate the risk of bias (ROB) of the included studies.

In total, 26 studies met the eligibility criteria. The reporting rate of the AEs of HMs ranged considerably, from 0.03% to 29.84%, with a median overall pooled estimate of 1.42% (IQR 1.12%-1.72%). Subgroup analyses combined with the meta-regression model revealed that the reporting rate of the AEs of HMs was associated with the source of the reporter (<i>P</i>=.01). None of the included studies provided full details of suspected herbal products, only the main ingredients were disclosed, and other potentially harmful components were not listed.

This systematic review and meta-analysis highlighted risks related to HMs, with a wide range of reporting rates, depending on the source of the reporter. Continuous efforts are necessary to standardize consumer reporting systems in terms of the reporting form, education, and follow-up strategy to improve data quality assurance, aiming to enhance the reliability and utility of PV data for monitoring the safety of HMs. Achieving effective monitoring and reporting of these AEs necessitates collaborative efforts from diverse stakeholders, including patients/consumers, manufacturers, physicians, complementary practitioners, sellers/distributors, and health authorities.

PROSPERO (Prospective International Register of Systematic Reviews) CRD42021276492