Oral traditional Chinese patent medicines combined with non-steroidal anti-inflammatory drugs for primary dysmenorrhea: A protocol for Bayesian network meta-analysis and systematic review

Abstract

Introduction Primary dysmenorrhea (PD) was the most common gynecological disorder, with an increasingly high prevalence worldwide. PD often accompanied other dysmenorrhea-associated symptoms to trigger exacerbations, and even cause depression and anxiety for patients. As the effective first-line medication, non-steroidal anti-inflammatory drugs (NSAIDs) have become widespread across China and combined with oral traditional Chinese patent medicines (TCPMs) for PD in clinical practice. We hope to provide better efficacy and safety evidence about oral TCPMs combined with NSAIDs (oral TCPMs+NSAIDs) for patients with PD by this network meta-analysis. Methods and analysis We will perform a Bayesian network meta-analysis of all oral TCPMs+NSAIDs for clinical diagnosis as PD. PubMed, Embase, Cochrane Library, Web of Science, China National Knowledge Infrastructure, Wanfang Data Knowledge Service Platform, VIP information resource integration service platform databases, and clinical registers will be searched from the database inception to June 30, 2022 to find randomized controlled trials. Two reviewers will independently screen and check titles and abstracts and read the full text. Data extraction with the same criteria will be conducted by two researchers, including study characteristics, participant characteristics, interventions and comparators, and outcomes. We will perform the network meta-analysis by the Bayesian random method to analyze the direct and indirect comparisons. Meta-regression with multiple covariates will be conducted to find the potential heterogeneity. We will perform the sensitivity analysis to identify the potential effect on the robustness of our results. Evidence certainty of all interventions in outcomes will be identified and assessed by Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) assessment. Funnel plots with Egger test and Begg’s test to detect the potential publication bias. Trial registration PROSPERO registration number: CRD42021265675.