Efficacy and safety of Chinese patent medicines for allergic rhinitis based on 2020 Chinese Pharmacopoeia: a protocol for systematic review and meta-analysis of randomized controlled trials.

Abstract

Background: Allergic Rhinitis (AR) is a prevalent chronic respiratory condition with limited long-term relief from Western medications. Interest in Traditional Chinese Patent Medicines (TCPMs) as a complementary approach is growing, but research on their efficacy and safety is lacking. We aim to evaluate the efficacy and safety of TCPMs listed in the 2020 Chinese Pharmacopoeia (ChP 2020) that are indicated for treating AR.

Methods: We will search PubMed, Embase, Web of Science, Cochrane Library, and four Chinese databases to retrieve randomized controlled trials investigating specific TCPMs (Biyankang tablets, Tongqiao Biyan Granules, Tongqiao Biyan Tablets, Tongqiao Biyan Capsules, Xinqin Granules, Xinqin Tablets, Xinyi Biyan Pills) for AR. Primary outcomes are Total Nasal Symptom Scores (TNSS) and Total Ocular Symptom Scores (TOSS). Secondary outcomes include quality of life, relapse rates, nasal function, biomarkers, and adverse events. No languages and publication data limitations. Meta-analysis will be performed using RevMan 5.4 with random effects model. Publication bias are set to be assessed using funnel plots and Egger's test, and adjusted with the trim and fill method. Meta-regression will investigate factors influencing outcomes for AR. Study quality will be assessed using the Cochrane Risk of Bias 2.0 tool, and the Grading of Recommendations Assessment, Development, and Evaluation approach will be used to evaluate the quality of evidence.

Discussion: Despite the limitations of conventional AR medications, TCPMs show potential benefits in immune modulation and symptom relief. This review will focus on TCPMs listed in ChP 2020 to comprehensively evaluate their safety and efficacy for AR. Unlike existing reviews, this study emphasizes rigorous standards of TCPMs, aiming to provide a more reliable evidence base. Although a network meta-analysis would be ideal, a traditional meta-analysis will be conducted due to limited data. Future research should focus on direct comparative studies and utilize AI techniques for understanding mechanisms and enhancing personalized treatments. This review aims to bridge gaps in the current literature and potentially improve clinical guidelines and patient outcomes in AR management.

Systematic review registration: INPLASY202450121.