Abstract
Endometriosis is now considered to be a systemic disease rather than a disease that primarily affects the pelvis. Dienogest (DNG) has unique advantages in the treatment of endometriosis, but it also has side effects. Alternatively, Traditional Chinese Medicine (TCM) has been used for over 2000 years in the treatment and prevention of disease and growing numbers of Chinese scholars are experimenting with the combined use of Dienogest and TCM for endometriosis treatment. This review evaluated the efficacy and safety of TCM in combination with Dienogest in the treatment of endometriosis through meta-analysis. MEDLINE, Embase, the Cochrane Library, PubMed, Web of Science, China National Knowledge Infrastructure, Journal Integration Platform, and Wanfang were used in literature searches, with a deadline of May 31, 2022. Literature quality was assessed using the Cochrane Collaboration "risk of bias" (ROB2) tool, and the "meta" package of R software v.4.1 was used for meta-analysis. Dichotomous variables and continuous variables were assessed using the relative risk (RR) and 95% confidence intervals (95% CI); standard mean differences (MD) and 95% CI, respectively. Twelve human randomized controlled trials (RCTs) and one retrospective study, all 13 written in the Chinese language, were included in the meta-analysis (720 experiments and 719 controls). The result indicated that TCM plus Dienogest was superior to Dienogest/TCM alone in increasing the cure rates (RR = 1.3780; 95% CI, 1.1058, 1.7172; P = 0.0043), remarkable effect rate (RR = 1.3389; 95% CI, 1.1829, 1.5154; P < 0.0001), invalid rate (RR = 0.2299; 95% CI, 0.1591, 0.3322; P < 0.0001), and rate of adverse effects (RR = 0.6177; 95% CI, 0.4288, 0.8899; P = 0.0097). The same conclusion was drawn from the subgroup analysis. Results suggest that TCM combined with Dienogest is superior to Dienogest or TCM alone and can be used as a complementary treatment for endometriosis. TCMs have potential to improve clinical efficacy and reduce the side effects of Dienogest. This study was financially supported by Annual Science and Technology Steering Plan Project of Zhuzhou. PROSPERO has registered our meta-analysis as CRD42022339518 (https://www.crd.york.ac.uk/prospero/record_email.php).
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