Front. Neurol. Frontiers in Neurology Front. Neurol. 1664-2295 Frontiers Media S.A. 10.3389/fneur.2026.1749660 Systematic Review Efficacy and security of traditional Chinese medicine in the treatment of perimenopausal insomnia in the Chinese population: a systematic review and meta-analysis of randomized controlled trials Yang Denghui 1 Conceptualization Data curation Formal analysis Methodology Software Writing – original draft Chen Dan 2 Data curation Formal analysis Methodology Writing – original draft Peng Jieru 1 Data curation Formal analysis Writing – original draft Peng Yifei 2 Conceptualization Data curation Writing – original draft Yang Chunxia 1 3 Conceptualization Methodology Writing – original draft Writing – review & editing Sun Jungang 2 4 * Conceptualization Funding acquisition Methodology Resources Supervision Writing – original draft Writing – review & editing Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China Acupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China Non-Communicable Diseases Research Center, West China-PUMC C.C. Chen Institute of Health, Sichuan University, Chengdu, Sichuan, China Sub-Health Centre, Sichuan Integrative Medicine Hospital, Chengdu, Sichuan, China Correspondence: Jungang Sun, 32298854@qq.com 19 02 2026 2026 17 1749660 19 11 2025 28 01 2026 04 02 2026 Copyright © 2026 Yang, Chen, Peng, Peng, Yang and Sun. 2026 Yang, Chen, Peng, Peng, Yang and Sun https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Background

Traditional Chinese medicine (TCM) has been widely applied in the management of perimenopausal insomnia (PMI), yet comprehensive evidence on its efficacy and safety remains insufficient. We aimed to systematically evaluate the therapeutic effects and safety of TCM interventions in PMI treatment.

 Methods

Randomized controlled trials (RCTs) that compared TCM interventions with Western medicine for patients with PMI were searched across eight databases from inception to August 1, 2025. Methodological quality, risk of bias, and certainty of evidence were assessed using the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines and Grading of Recommendations Assessment, Development and Evaluation (GRADE) framework. Meta-analysis was performed using RevMan 5.4 and R 4.4.2 software.

 Results

A total of 48 RCTs involving 5,037 patients were included. Meta-analysis showed that TCM was superior to Western medicine in overall efficacy (RR = 1.20, 95% CI [1.17, 1.23]) and had fewer adverse reactions (RR = 0.30, 95% CI [0.24, 0.38]). Besides, TCM interventions significantly improved Pittsburgh Sleep Quality Index (PSQI) score (MD = −2.57, 95% CI [−3.01, −2.14]), reduced luteinizing hormone (LH) (MD = −4.51, 95% CI [−6.15, −2.87]) and follicle-stimulating hormone (FSH) (MD = −8.67, 95% CI [−10.96, −6.38]), increased estradiol (E2) level (MD = 9.64, 95% CI [7.45, 11.82]), and decreased Kupperman Menopausal Index (KMI) score (MD = −6.01, 95% CI [−8.56, −3.47]), Traditional Chinese Medicine Syndrome (TCMS) score (SMD = −2.27, 95% CI [−3.49, −1.05]), Self-Rating Anxiety Scale (SAS) score (MD = −4.77, 95% CI [−5.77, −3.76]), and Self-Rating Depression Scale (SDS) score (MD = −2.96, 95% CI [−5.80, −0.12]).

 Conclusion

TCM interventions demonstrate notable efficacy and safety in managing PMI by improving sleep quality, hormonal balance, and mental health. However, methodological limitations and heterogeneity warrant further validation through large-scale, multicenter, rigorously designed RCTs.

 Systematic review registration

PROSPERO registration number CRD420251127129.

 insomnia meta-analysis perimenopause randomized controlled trial sleep disorder traditional Chinese medicine The author(s) declared that financial support was received for this work and/or its publication. Funding for this research was provided by the Key Research and Development Project of the Sichuan Provincial Department of Science and Technology (grant number: 2024YFFK0087). section-at-acceptance Sleep Disorders Introduction

Perimenopause, the transitional phase from the reproductive period to menopause, is marked by fluctuations in sex hormone levels caused by declining ovarian function and is often accompanied by various physiological and psychological disturbances. Among these disturbances, the prevalence of insomnia is reported to be as high as 40–60% (1, 2). Perimenopausal insomnia (PMI) is mainly characterized by difficulty falling asleep, sleep maintenance disorders, early awakening, and impaired daytime function. Persistent insomnia not only reduces quality of life but may also exacerbate emotional disorders such as anxiety and depression and increase the risk of comorbidities, including cardiovascular disease and metabolic syndrome. Consequently, PMI has emerged as a significant public health issue affecting women’s health (3, 4).

Currently, the treatment of PMI primarily relies on hormone replacement therapy (HRT) and sedative-hypnotic medications, including benzodiazepines and non-benzodiazepines (5, 6). Although these therapies demonstrate clear short-term efficacy, their long-term use may cause adverse effects such as breast tenderness, endometrial hyperplasia, hepatic and renal impairment, and drug dependence. Additionally, some patients show low compliance due to contraindications to hormone use or concerns about drug adverse reactions (7). Therefore, exploring safe, effective, and patient-acceptable alternative therapies has become an important focus of clinical research.

Traditional Chinese Medicine (TCM) has a long history in the treatment of PMI. Clinically, doctors will adopt the principles of syndrome differentiation to select different TCM interventions including classical prescriptions, proprietary formulations, and acupuncture (8, 9). In recent years, several studies have shown that classic TCM prescriptions such as Chaihu Jia Longgu Muli Decoction, Huanglian Ejiao Decoction, and Suanzaoren Decoction have shown positive effects in alleviating insomnia symptoms and regulating sex hormone levels (10–12). However, existing studies vary in sample size, apply inconsistent outcome evaluation criteria, and yield controversial findings. Therefore, this study aims to evaluate the effectiveness and safety of TCM interventions in the treatment of PMI through systematic review and Meta-analysis, so as to provide high-level evidence-based basis for clinical decision-making.

 Methods

This systematic review and Meta-analysis were conducted in strict accordance with the latest PRISMA guidelines. A complete scheme for this study was registered in the Prospective Register of Systematic Reviews (PROSPERO): no. CRD420251127129.

Search strategy and study selection

Systematic searches were conducted in Chinese and English databases to obtain randomized controlled trials related to the treatment of PMI with TCM interventions. Chinese databases included China National Knowledge Infrastructure (CNKI), China Biomedical Literature Database (CBM), CQVIP database, and Wanfang database. English databases included PubMed, Web of Science, Embase, and Cochrane Library. The search time span was limited from the establishment of each database to August 1, 2025. The search terms and keywords included “traditional Chinese medicine”, “perimenopause”, “menopausal”, “insomnia”, “sleep disorder”, “sleeplessness”, “RCTs”, etc. Some of the search strategies are documented in Supplementary Table 1.

After excluding duplicate studies, two researchers excluded studies that were not related to the treatment of PMI with TCM by reading the titles and abstracts. Then, the full text of the selected studies was further read, and the final included studies were determined with reference to the inclusion and exclusion criteria. If the two researchers had inconsistent opinions on study selection, it would be discussed and decided by the third researcher.

 Inclusion and exclusion criteria

Inclusion criteria: (a) included studies were designed as randomized controlled trials (RCTs); (b) the language of studies was restricted to Chinese and English; (c) participants were Chinese individuals diagnosed with PMI, regardless of their ethnicity or disease duration; (d) the experimental group received TCM interventions, which could be administered as a single TCM therapy, a combination of multiple TCMs, TCM combined with Western medicine, or TCM combined with acupuncture; (e) the control group was required to receive conventional Western medicine therapy for PMI; (f) outcome measures included at least one of the primary outcomes and one secondary outcomes. Specifically, primary outcome measures of interests were overall efficiency and adverse reactions, and secondary outcome measures of interests were Pittsburgh Sleep Quality Index (PSQI), Estradiol (E2), Follicle-stimulating hormone (FSH), Luteinizing hormone (LH), Kupperman Menopausal Index (KMI), Traditional Chinese Medicine Syndrome (TCMS) score, Self-Rating Anxiety Scale (SAS), and Self-Rating Depression Scale (SDS).

Studies were excluded if it met the following criteria: (a) studies that do not match the target literature type, such as reviews, animal experiments, trials comparing different dosages of TCM, or non-randomized controlled trials; (b) studies with inconsistent research diseases or medication methods; (c) literature with incomplete data records, insufficient outcome measures, or inaccessible data extraction; (d) duplicate publications; (e) studies where the control group used interventions such as TCM, acupuncture, or other TCM interventions.

 Data extraction and risk of bias assessment

Two independent reviewers used the Cochrane Risk of Bias Tool (Version 2.0) to screen and evaluate the quality of the included studies respectively, and simultaneously collected and verified the relevant outcome measures data. In case of disagreements between the two researchers, a third researcher would participate in the discussion to reach a consensus ultimately. The quality assessment criteria included seven items: random sequence generation (selection bias), allocation concealment (selection bias), blinding of participants and personnel (performance bias), blinding of outcome assessment (detection bias), incomplete outcome data (attrition bias), selective reporting (reporting bias), and other bias, with three evaluation levels: high risk, unclear risk, and low risk. Specifically, the judgment of “low risk” required the included studies to provide explicit and detailed descriptions of the corresponding methodological design without any identified flaws; “unclear risk” was assigned when the study report lacked sufficient information to permit a definitive judgment; and “high risk” was defined when the study design or implementation had obvious defects that could lead to significant bias (13).

 Statistical analysis

Data analysis was performed using RevMan 5.4 software. For continuous variables: The mean difference (MD) was selected as the effect measure for continuous variables with uniform measurement units; The standard mean difference (SMD) was used as the effect measure for continuous variables with non-uniform measurement units, continuous variables measured by different scales, or continuous variables with a numerical difference greater than 10 times between different studies. For dichotomous variables, the Risk Ratio (RR) and its 95% Confidence Interval (CI) were used for evaluation (14, 15).

Heterogeneity testing was conducted for the included studies. If the heterogeneity was low (p > 0.10 and I2 ≤ 50%), a fixed-effects model was adopted for analysis; otherwise, a random-effects model was used for analysis. Subgroup analysis was performed based on differences of interventions. When an outcome measure included more than 10 studies, funnel plots were constructed and Egger’s test and Peter’s test were performed by R 4.4.2 software to assess potential publication bias (16, 17). When necessary, sensitivity analysis and regression analysis were conducted to analyze the sources of heterogeneity. p < 0.05 indicates that the difference is statistically significant.

 Results Study selection

In this study, a total of 1,418 articles were initially retrieved from 8 Chinese and English databases. After excluding duplicate articles, 662 articles remained. Based on the inclusion and exclusion criteria and the completeness of literature information, 48 articles were finally included for Meta-analysis. The literature screening process and results were shown in Figure 1.

Flow diagram of the literature search and study selection process.

Flowchart showing study selection for a meta-analysis: 1,290 Chinese and 128 English articles identified, 662 records after duplicates removed, 510 excluded by abstract, 104 excluded by full-text, resulting in 48 studies included. Characteristics of included studies

This study summarized 48 clinical randomized controlled trials from mainland China, covering 17 provinces or autonomous regions. Among them, Henan Province (12/48), Zhejiang Province (8/48), and Beijing (6/48) were the most common. A total of 5,037 patients participated in these studies, with 2,547 in the experimental group and 2,490 in the control group. The sample size of the included studies ranged from 37 to 820. In addition, considering that 3 articles (18–20) contained multiple experimental groups or control groups, according to the regulations in the Cochrane Handbook for Systematic Reviews of Interventions (21), these studies were split into Study a and Study b.

A total of 42 TCM prescriptions or patent medicines for the treatment of PMI were included. Among them, Chaihu Jia Longgu Muli Decoction (4/42) and Huanglian Ejiao Decoction (4/42) were the most frequently used TCM interventions. Based on the different types of treatments, the study set up three subgroups for analysis: (1) The TCM group (TCM), where the experimental group used TCM alone. (2) The TCM-Western medicine group (TCM-WM), where the experimental group used TCM combined with Western medicine. (3) The TCM-Acupuncture group (TCM-A), where the experimental group used TCM combined with acupuncture. Therefore, subsequent subgroup analyses will be conducted according to these three intervention types. In the control groups of the included studies, all patients with PMI received conventional Western medical treatments, such as HRT or benzodiazepine sedative-hypnotics, among which estazolam and zopiclone were the two most commonly used medications. Additionally, the treatment duration of most studies ranged from 4 to 12 weeks. For detailed information on the basic characteristics of the included studies (please refer to Table 1).

Basic characteristics of included literature.

Study ID Region Experimental treatment Control treatment Sample size (E/C) Age (years, E/C) Outcome measures Duration
Chen et al. (12) Zhejiang Jiawei Suanzaoren Decoction Lorazepam 40/38 48.95 ± 2.45/47.82 ± 2.87 ①②③ 4 weeks
Qiao (18) Henan Kuntai Capsule Femara 30/30 47.9 ± 2.3/47.0 ± 2.4 ①②③④⑤⑥⑩ 12 weeks
Liu et al. (52) Beijing Chaihu Guizhi Longgu Muli Decoction combined with Ganmai Dazao Decoction Estazolam 68/68 51 ± 4/50 ± 4 ①②③⑦⑧⑨⑩ 4 weeks
Yao et al. (53) Zhejiang Zishen Jieyu Ningxin Formula Estazolam 60/53 48.5 ± 5.2/49.0 ± 6.0 ①②③④⑤⑥⑧ 8 weeks
Sun et al. (54) Sichuan Suanzaoren Decoction combined with Xiaoyao San Alprazolam 30/30 48.97 ± 2.83/49.07 ± 2.07 ①②③⑥ 4 weeks
Zhang et al. (55) Beijing Liandi Jiaotai Decoction Lorazepam 30/30 51.9 ± 2.4/52.3 ± 2.5 ①②③⑦⑩ 8 weeks
Zhu and Wang (25) Anhui Buxin Xiaoyao Yin Zopiclone 31/31 48.6 ± 4.9/48.3 ± 4.8 ①②③ 4 weeks
Du et al. (19) Tianjin Jiawei Wumei Wan Estazolam 41/41 49.76 ± 3.05/50.45 ± 3.19 ②③⑤⑥⑦ 4 weeks
Wang and Ma (26) Beijing Liuwei Dihuang Tang combined with Xiaoyao San Sex hormones 30/30 48.87 ± 3.85/48.33 ± 3.35 ①③⑤⑥⑦⑧ 3 months
Xiao and Niu (56) Henan Chaihu Jia Longgu Muli Decoction Zopiclone and Paroxetine Hydrochloride Tablets 410/410 52.10 ± 2.01/51.82 ± 2.13 ①②③⑧ 4 weeks
Mao (27) Zhejiang Huanglian Ejiao Decoction Alprazolam 45/45 50.82 ± 3.26/50.30 ± 3.41 ①④⑤⑥ 1 month
Mo et al. (28) Henan Chai Shao Yangxue Jieyu Decoction Estazolam 45/44 49.43 ± 3.02/49.56 ± 3.19 ①④⑤⑥ 12 weeks
Xie (57) Jiangsu Chaihu Guizhi Longgu Muli Decoction Estazolam 30/30 52.1 ± 4.2/51.5 ± 3.3 ①③⑦⑧⑨⑩ 4 weeks
Jia et al. (29) Beijing Gengxin Decoction Zopiclone 20/17 47.65 ± 3.83/49.71 ± 3.84 ①③⑦⑧ 4 weeks
Qian et al. (58) Zhejiang Danzhi Xiaoyao Wan combined with Kuntai Capsule Estazolam 120/80 45.16 ± 3.86/46.07 ± 2.89 ①②③⑦ 30 days
Chen et al. (20) Hubei Huanglian Ejiao Decoction Alprazolam 28/30 46.07 ± 3.50/47.03 ± 3.84 ①④⑤⑥ 30 days
Qi and Kang (30) Zhejiang Zishen Ningshen Decoction Estazolam and oryzanol 48/47 49.4 ± 4.1/49.6 ± 4.3 ①②③④⑤⑥⑦⑧ 8 weeks
Qiao et al. (31) Heilongjiang Tianwang Buxin Dan combined with Jiaotai Wan and conventional Western medicine Estazolam combined with Sex hormones 29/29 51.00 ± 2.79/49.63 ± 3.35 ①②③④⑤⑥ 4 weeks
Qiao (18) Henan Kuntai Capsule combined with Femara Femara 30/30 48.0 ± 2.6/47.0 ± 2.4 ①②③④⑤⑥⑩ 12 weeks
Wu et al. (23) Jiangxi Xiangshao Granules combined with Paroxetine Paroxetine 35/35 46.32 ± 2.74/45.12 ± 2.34 ①④⑤⑥ 8 weeks
Zhou et al. (32) Jiangsu Ziyin Anshen Gao combined with Zopiclone Zopiclone 30/29 49.38 ± 2.19/49.37 ± 2.17 ①③④⑤⑥ 1 month
Zhang et al. (33) Fujian Songyu Yinxu Formula combined with Estazolam Estazolam 58/58 51(48,53)/50(47,53) ②③④⑤⑥⑨⑩ 4 weeks
Zhang et al. (59) Zhejiang Erxian Tang combined with Suanzaoren Decoction and conventional Western medicine Estazolam combined with Femara 75/75 49.5 ± 2.7/50.1 ± 2.7 ①③④⑤⑥ 4 weeks
Li et al. (34) Hubei Banxia Xiexin Decoction combined with Zopiclone Zopiclone 73/72 50.42 ± 2.34/50.03 ± 2.01 ①②③⑤ 4 weeks
Li (60) Henan Zixin Yangshen Decoction combined with Estazolam Estazolam 49/49 48.77 ± 4.21/49.28 ± 4.57 ①②③⑦ 30 days
Du et al. (35) Shaanxi Roukou Wuwei Wan combined with Trazodone Hydrochloride Paroxetine 60/60 46.70 ± 3.74/46.48 ± 3.70 ①③⑤⑥ 8 weeks
Lin et al. (36) Fujian Zishen Shugan Anshen Decoction combined with Estazolam Estazolam 32/32 49.16 ± 2.07/49.06 ± 2.26 ①②③⑧ 4 weeks
Liang (37) Shanghai Wuling Capsule combined with Zopiclone Zopiclone 40/40 50.94 ± 5.22/50.82 ± 4.62 ①②③ 4 weeks
Liang and Zheng (61) Henan Baihe Dihuang Decoction combined with Zopiclone Zopiclone 41/41 52.54 ± 2.43/52.63 ± 2.52 ①④⑤⑥ 4 weeks
Wang and Wang (10) Beijing Chaihu Jia Longgu Muli Decoction combined with Estazolam Estazolam 30/30 49.6 ± 2.1/49.8 ± 2.2 ①②③④⑤⑥⑦⑧ 8 weeks
Wang et al. (38) Anhui Yiganxue combined with Suanzaoren Decoction and Estazolam Estazolam 69/69 49.12 ± 2.20/48.98 ± 2.45 ①②③④⑤⑥ 4 weeks
Dou et al. (24) Henan Yishen Anshen Decoction combined with conventional Western medicine Zopiclone combined with Sex hormones 36/36 50.33 ± 3.27/50.56 ± 1.52 ①②④⑤⑥ 4 weeks
Shao et al. (39) Hebei Chaiqi Ningshen Anmian Decoction combined with Estazolam Estazolam 30/30 51.62 ± 5.47/50.88 ± 5.78 ①③⑧ 4 weeks
Zheng (40) Jilin Guizhi Jia Longgu Muli Decoction combined with Alprazolam Alprazolam 30/30 43.21 ± 7.67/41.97 ± 11.25 ①③ 4 weeks
Chen (41) Zhejiang Guipi Tang combined with Estazolam Estazolam 30/30 48.23 ± 3.16/48.15 ± 3.26 ①②③④⑤⑥ 8 weeks
Chen et al. (42) Guangdong Guanlong Compound combined with Eszopiclone Zopiclone 26/26 49.04 ± 2.91/48.31 ± 2.45 ②③④⑤⑥ 2 months
Chen et al. (43) Fujian Kuntai Capsule combined with Estrogen and Progesterone Sex hormones 41/41 50.15 ± 3.1/50.23 ± 3.2 ①③④⑤⑥⑦ 3 months
Ran and Wang (44) Henan Modified Suanzaoren Decoction combined with Acupuncture Estazolam 43/43 50.63 ± 7.59/50.51 ± 7.57 ②③④⑤⑥ 4 weeks
Wu et al. (22) Sichuan Acupuncture combined with Zhumin Decoction Sex hormones 48/48 49.67 ± 2.76/49.80 ± 2.79 ①③④⑤⑥ 3 weeks
Sun et al. (45) Henan Acupuncture combined with Qingre Anshen Decoction Estazolam 53/53 51.62 ± 3.11/51.66 ± 3.12 ①③④⑤⑥ 2 months
Zuo and Jin (62) Shanghai Acupuncture combined with Xiaoyao Decoction Estazolam 38/38 52.15 ± 2.40/52.20 ± 2.54 ①②③ 4 weeks
Kang (46) Henan Acupuncture combined with Xiangfu Decoction Estazolam 43/43 50.45 ± 3.92/49.30 ± 3.15 ①③④⑤⑥ 1 month
Zhang and Fan (63) Henan Acupuncture combined with Huanglian Ejiao Decoction Estazolam combined with oryzanol 23/23 52.24 ± 1.86/50.06 ± 1.78 ①③ 1 month
Zhang and Zhou (47) Beijing Acupuncture combined with Baihe Dihuang Decoction Estazolam 39/39 52.76 ± 2.81/52.14 ± 2.63 ①②③④⑤⑥ 4 weeks
Xu and Zhao (48) Zhejiang Acupuncture combined with Wen’an Shenyangxue Decoction Estazolam 53/53 51.01 ± 5.22/51.24 ± 5.33 ①②③④⑤⑥⑦ 3 months
Du2017b (19) Liaoning Acupuncture combined with Jiawei Wumei Wan Estazolam 42/41 50.61 ± 2.62/50.45 ± 3.19 ②③⑤⑥⑦ 4 weeks
Yang and Liu (49) Shandong Acupuncture combined with Huanglian Wendan Decoction Alprazolam 30/30 49.06 ± 2.56/49.02 ± 2.31 ①④⑤⑥⑦⑧ 4 weeks
Yan et al. (50) Henan Acupuncture combined with Xiangfu Decoction Estazolam 59/57 50.8 ± 7.6/49.6 ± 7.2 ①②③④⑤⑥⑧ 16 weeks
Chen et al. (20) Hubei Acupuncture combined with Jiawei Huanglian Ejiao Tang Alprazolam 30/30 47.87 ± 4.12/47.03 ± 3.84 ①④⑤⑥ 30 days
Lu et al. (64) Henan Acupuncture combined with Baizi Yangxin Tang Estazolam 46/46 40–52/40–52 ①②③⑤⑥ 4 weeks
Huang et al. (51) Fujian Acupuncture combined with Sun’s Anshen Formula Estazolam combined with Tibolone 50/50 50.42 ± 5.90/50.38 ± 5.20 ①②③⑨⑩ 3 months

E: Experimental Group; C: Control Group; ①Overall Efficiency; ②Adverse Reactions; ③Pittsburgh Sleep Quality Index; ④Luteinizing Hormone; ⑤Follicle-Stimulating Hormone; ⑥Estradiol; ⑦Kupperman Menopausal Index; ⑧Traditional Chinese Medicine Syndrome; ⑨Self-Rating Anxiety Scale; ⑩Self-Rating Depression Scale.

Regarding diagnostic criteria, seven studies lacked specific criteria for perimenopause. The remaining studies provided clear diagnostic criteria for both perimenopause and insomnia. Among them, four studies adopted Western medical diagnostic criteria, six applied Traditional Chinese Medicine criteria, and the remaining 31 studies used both TCM and Western medical diagnostic criteria. Specifically, most studies diagnosed perimenopause based on Obstetrics and Gynecology, while the diagnosis of insomnia was primarily guided by the Chinese Classification of Mental Disorders, Third Edition (CCMD-3), as details in the Supplementary Table 2.

 Risk of bias assessment

Among the 48 included studies, a total of 34 studies were judged as low risk, among which 2 studies (12, 22) used computer-generated random numbers, 1 study (23) adopted simple random grouping, 1 study (24) conducted random grouping by the draw-ball method, and the remaining 30 studies (10, 18, 19, 25–51) used random number tables to generate random sequences. In addition, 14 studies (20, 52–64) stated random grouping in the text but did not specify the randomization method, so their risk was judged as unclear risk. However, only 2 studies (22, 31) adopted the envelope method for allocation concealment, so they were rated as low risk; the other studies did not implement allocation concealment and were rated as high risk. Almost all included clinical randomized controlled trials did not mention blinding in the text, except for 1 study (12) that applied blinding to outcome assessors and data analysts. All randomized controlled trials had no missing data, or the missing data did not affect the result analysis, so they were assessed as low bias risk in this dimension. All randomized controlled trials reported all outcomes described in the study design or methodology, so they were assessed as low risk of selective reporting bias. Further details are provided in Figure 2, and the bias risk of each included study is shown in Supplementary Figure 1.

Risk of bias summary for included studies.

Bar chart assessing risk of bias in seven study domains using green for low, yellow for unclear, and red for high risk. Allocation concealment shows the highest high risk, while incomplete outcome data and selective reporting are predominantly low risk. Primary outcomes Overall efficiency

A total of 4,609 patients in 46 studies reported the overall efficiency in treating PMI. Since the heterogeneity was low (p = 0.80 > 0.10, I2 < 50%), a fixed-effects model was used for analysis. The extracted data revealed that TCM interventions were more effective than conventional Western medicine in treating PMI (RR = 1.20, 95% CI [1.17, 1.23], p < 0.00001). Subgroup analysis indicated that TCM combined with Western medicine may achieve higher efficacy (RR = 1.22, 95% CI [1.17, 1.28], p < 0.00001). However, no statistical significance was observed in the overall efficiency among the subgroups (p = 0.37). The results are shown in Figure 3.

Forest plot of overall efficacy rate.

Forest plot from a meta-analysis displaying risk ratios and confidence intervals for three subgroups: TCM versus WM, TCM plus WM versus WM, and TCM plus acupuncture versus WM. Summary diamonds indicate all interventions favor the experimental groups with pooled risk ratios between 1.17 and 1.22 and no observed heterogeneity. Adverse reactions

A total of 2,486 patients in 29 studies reported the incidence of adverse events in treating PMI. Since the heterogeneity was low (p > 0.10, I2 < 50%), so a fixed-effects model was used for analysis. The extracted data indicated that patients treated with TCM interventions had a lower incidence of adverse reactions (RR = 0.30, 95% CI [0.24, 0.38], p < 0.00001). Subgroup analysis revealed that patients treated with TCM alone were associated with the lower incidence of adverse reactions (RR = 0.20, 95% CI [0.13, 0.31], p < 0.00001), and there was statistical significance in the incidence of adverse reactions among the subgroups (p = 0.001). The results are shown in Figure 4.

Forest plot of adverse reaction incidence.

Forest plot comparing risk ratios of adverse events between TCM interventions and Western medicine across three subgroups, displaying individual study results, confidence intervals, weights, and pooled estimates for each subgroup and overall, suggesting lower adverse event risk with TCM interventions. Secondary outcomes PSQI score

A total of 4,456 patients in 43 studies reported the PSQI score in treating PMI. The extracted data showed high heterogeneity across all subgroups (p < 0.10, I2 > 50%), so a random-effects model was used for analysis. The results indicated that patients with PMI who received TCM interventions had a lower PSQI score after treatment than those who received Western medicine treatment (MD = −2.57, 95% CI [−3.01, −2.14], p < 0.00001). Subgroup analysis revealed that the PSQI score of the experimental group was lower than that of the control group in all subgroups (all p < 0.05). However, there was no statistical significance among the subgroups (p = 0.25). The results are shown in Figure 5. Sensitivity analysis, as shown in the Supplementary Figure 2, suggested that the results were generally robust. Systematically removing studies one at a time fails to make heterogeneity reduce significantly.

Forest plot of PSQI score.

Forest plot comparing mean differences and confidence intervals for studies assessing TCM interventions versus Western medicine across three subgroups, showing pooled effect sizes, weights, heterogeneity statistics, and favored direction of effect for each group. LH level

A total of 2,358 patients in 36 studies reported the LH level in treating PMI. The heterogeneity test results showed high heterogeneity across all subgroups (p < 0.10, I2 > 50%), so a random-effects model was used for analysis. The extracted results indicated that patients with PMI who received TCM interventions had a lower LH level than those who received Western medicine (MD = −4.51, 95% CI [−6.15, −2.87], p < 0.00001). Subgroup analysis results showed that the LH level of the experimental group was lower than that of the control group in all subgroups (all p < 0.05). However, no statistical difference was observed in the LH level among the subgroups (p = 0.29). The results are shown in Figure 6. Sensitivity analysis, as shown in the Supplementary Figure 3, suggested that the results were generally robust. Systematically removing studies one at a time fails to make heterogeneity reduce significantly.

Forest plot of LH level.

Forest plot displaying a meta-analysis comparing the effects of three interventions—TCM vs WM, TCM+WM vs WM, and TCM+Acupuncture vs WM—across multiple studies, with mean differences and confidence intervals shown for each study and subgroup, and overall effect sizes summarized by diamonds on the right. FSH level

A total of 34 studies reported the post-treatment FSH level of 2,940 patients. The heterogeneity test results showed high heterogeneity across all subgroups (p < 0.10, I2 > 50%), so a random-effects model was used for analysis. The extracted data showed that patients treated with TCM interventions had a lower FSH level than those treated with Western medicine (MD = −8.67, 95% CI [−10.96, −6.38], p < 0.00001). Subgroup analysis indicated that the FSH level of the experimental group was lower than that of the control group in all subgroups (all p < 0.05). In addition, a statistical difference was observed in the FSH level among the subgroups (p = 0.02). Specifically, patients treated with TCM combined with acupuncture had the lower FSH level after treatment (MD = −14.09, 95% CI [−19.28, −8.90], p < 0.00001). The results are shown in Figure 7. Sensitivity analysis, as shown in the Supplementary Figure 4, suggested that the results were generally robust. Systematically removing studies one at a time fails to make heterogeneity reduce significantly.

Forest plot of FSH level.

Forest plot summarizing a meta-analysis comparing TCM interventions and Western medicine with data on mean differences, confidence intervals, and study weights. Three subgroups are analyzed: TCM vs WM, TCM plus WM vs WM, and TCM plus acupuncture vs WM. Each subgroup’s pooled mean difference is represented by a diamond, with negative values favoring experimental interventions. Statistical heterogeneity (I²) and overall effect tests are presented, showing significant differences for all subgroups. E2 level

A total of 2,801 patients in 33 studies reported the E2 level in treating PMI. The heterogeneity test results showed high heterogeneity across all subgroups (p < 0.10, I2 > 50%), so a random-effects model was used for analysis. The extracted results showed that patients with PMI who received TCM interventions had a higher E2 level after treatment than those who received Western medicine treatment (MD = 9.64, 95% CI [7.45, 11.82], p < 0.00001). Subgroup analysis revealed that the E2 level of the experimental group was higher than that of the control group in all subgroups (all p < 0.05). In addition, a statistical difference was observed in the E2 level among the subgroups (p = 0.04). Specifically, patients treated with TCM combined with acupuncture had the higher E2 level after treatment (MD = 13.27, 95% CI [8.52, 18.01], p < 0.00001). The results are shown in Figure 8. Sensitivity analysis, as shown in the Supplementary Figure 5, suggested that the results were generally robust. Systematically removing studies one at a time fails to make heterogeneity reduce significantly.

Forest plot of E2 level.

Forest plot illustrating meta-analysis results comparing traditional Chinese medicine (TCM), TCM plus Western medicine (WM), and TCM plus acupuncture versus WM alone in three subgroups. Mean differences and confidence intervals are represented by horizontal lines for each study, with pooled effects shown as diamonds for each subgroup and overall. All subgroups and the total show significant improvement in the experimental groups favoring TCM interventions. KMI score

A total of 1,219 patients in 14 studies reported the KMI score in treating PMI. The heterogeneity test results showed high heterogeneity across all subgroups (p < 0.10, I2 > 50%), so a random-effects model was used for analysis. The extracted data showed that patients with PMI who received TCM interventions had a lower KMI score than those who received Western medicine (MD = −6.01, 95% CI [−8.56, −3.47], p < 0.00001). Subgroup analysis revealed that the KMI score of the experimental group was lower than that of the control group in all subgroups (all p < 0.05). However, no statistical difference was observed in the post-treatment KMI score among the subgroups (p = 0.57). The results are shown in Figure 9. Sensitivity analysis, as shown in the Supplementary Figure 6, suggested that the results were generally robust. Systematically removing studies one at a time fails to make heterogeneity reduce significantly.

Forest plot of KMI score.

Forest plot showing three subgroups comparing TCM interventions to Western medicine controls, with studies listed on the left, mean differences and confidence intervals on the right, and pooled effect sizes represented by black diamonds, indicating overall favour towards TCM interventions. TCMS score

A total of 1,621 patients in 11 studies reported the TCMS score in treating PMI. Considering that some studies adopted different TCM symptoms as evaluation criteria, the SMD was used as the effect size. The heterogeneity test results showed high heterogeneity (p < 0.10, I2 > 50%), so a random-effects model was used for analysis. The extracted data indicated that patients with PMI who received TCM interventions had a lower TCMS score after treatment than those who received Western medicine treatment (SMD = −2.27, 95% CI [−3.49, −1.05], p < 0.00001). Subgroup analysis results showed that: In the TCM group and TCM-WM group, the TCMS score of patients in the experimental group was lower (all p < 0.05). However, no statistical difference was observed in the TCMS score in the TCM-A group (p = 0.23). This result may be related to the small number of included studies (n = 2) in this subgroup, which may lead to insufficient statistical power to detect potential differences. In addition, there was no statistical significance among the subgroups (p = 0.30). The results are shown in Figure 10. Sensitivity analysis, as shown in the Supplementary Figure 7, suggested that the results were generally robust. Systematically removing studies one at a time fails to make heterogeneity reduce significantly.

Forest plot of TCMS score.

Forest plot comparing standard mean differences between TCM interventions and Western medicine for three subgroups, showing data for individual studies, confidence intervals, weights, and pooled results. Overall effect favors experimental groups with a summary estimate of −2.27 and confidence interval from −3.49 to −1.05. SAS score

A total of 412 patients in 4 studies reported the SAS score in treating PMI. The heterogeneity test results showed low heterogeneity (p > 0.10, I2 < 50%), so a fixed-effects model was used for analysis. The extracted data showed that patients with PMI who received TCM interventions had a lower SAS score after treatment than those treated with Western medicine (MD = −4.77, 95% CI [−5.77, −3.76], p < 0.00001). Subgroup analysis indicated that patients treated with TCM alone may have lower SAS score after treatment (MD = −5.59, 95% CI [−7.16, −4.02], p < 0.00001), but this advantage did not reach a significant difference due to small sample sizes. The results are shown in Figure 11.

Forest plot of SAS score.

Forest plot comparing TCM interventions with western medicine for three subgroups, showing mean differences, confidence intervals, study weights, and heterogeneity statistics. All results favor experimental interventions, with pooled mean differences around -4.77. SDS score

A total of 592 patients in 7 studies reported the SDS score in treating PMI. The heterogeneity test results showed high heterogeneity (p < 0.10, I2 > 50%), so a random-effects model was used for analysis. The extracted data showed that patients with PMI who received TCM interventions had a lower SDS score than those who received Western medicine (MD = −2.96, 95% CI [−5.80, −0.12], p = 0.04). Subgroup analysis results indicated that: In the TCM group and TCM-WM group, no statistical difference was observed in the SDS score between the experimental group and the control group (both p > 0.05). In the TCM-A group, although the SDS score of the experimental group was lower, this subgroup only included one study, so the result needs to be interpreted with caution. In addition, no statistical difference was observed in the post-treatment SDS score among the subgroups (p = 0.26), as detailed in Figure 12. Sensitivity analysis, as shown in the Supplementary Figure 8, suggested that the overall results were generally robust, with consistent effect directions across leave-one-out analyses. However, the statistical significance of the pooled estimate was influenced by several studies (18, 51, 52, 57), suggesting some dependency on these trials. Although excluding certain studies could reduce heterogeneity, the heterogeneity after reduction remained substantial (I2 > 50%).

Forest plot of SDS score.

Forest plot comparing traditional Chinese medicine (TCM) interventions to Western medicine (WM) across three subgroups, showing mean differences with confidence intervals for each study and overall estimates; overall effect favors TCM interventions with a mean difference of minus two point nine six and confidence interval spanning minus five point eight zero to minus zero point one two. Subgroup analysis, sensitivity analysis and regression analysis

There subgroups were created based on the different interventions: TCM, TCM combined with WM and TCM combined with acupuncture. For outcome measures with significant heterogeneity remaining after subgroup analysis, sensitivity analysis was conducted to assess robustness, and studies were excluded one by one to identify the source of heterogeneity. The detailed results can be found in the Supplementary Figures 2–8. For the seven outcome indicators (PSQI, LH, FSH, E2, KMI, TCMS, and SDS) that still displayed high heterogeneity after subgroup analysis, we performed regression analysis to explore potential sources of heterogeneity. The results demonstrated that for the TCMS, both sample size and follow-up duration were identified as significant moderators of heterogeneity (both p < 0.05); in contrast, none of sample size, age, or follow-up duration exerted a significant moderating effect on the heterogeneity of the remaining six indicators (all p > 0.05). The detailed regression results can be found in Supplementary Table 3.

 Publication bias

Publication bias analysis was conducted for outcome measures with more than 10 included studies. Results of the funnel plot and bias test revealed that for overall efficiency, adverse reactions, LH level, KMI score, TCMS score, SAS score, and SDS score, the possibility of publication bias was low. In contrast, for PSQI score, FSH level, and E2 level, the possibility of publication bias was high. The results are shown in Figure 13.

Funnel plot of the outcomes. (A) OE; (B) AE; (C) PSQI; (D) LH; (E) FSH; (F) E2; (G) KMI; (H) TCMS.

Eight funnel plots display standard error versus effect size (risk ratio, mean difference, or standardized mean difference) with P-values shown. Each plot contains scattered data points, shaded confidence regions, and dashed guide lines, illustrating potential publication bias in meta-analyses. Quality of evidence

The quality of the evidence was evaluated using the GRADE profiler, the assessment results showed that the quality of evidence is relatively moderate. Further details are provided in the Supplementary Table 4.

 Discussion

Nearly 50% of women in China experience insomnia during the perimenopausal period, which markedly interfere with daily functioning and overall well-being. As a result, PMI has emerged as a significant public health concern warranting increased clinical attention and research (65). The etiology of perimenopausal insomnia is highly complex. Modern clinical studies indicate that it is associated with multiple factors, including aging, psychological stress, neuroendocrine changes, and hormonal fluctuations (66–68). To date, there is no consensus on the precise pathophysiological mechanisms. According to Western medical theory, the primary mechanism involves ovarian function decline, which disrupts the hypothalamic–pituitary-ovarian (HPO) axis, leading to hormonal fluctuations, particularly in estrogen and progesterone, which play critical roles in maintaining neurotransmitter balance, regulating circadian rhythms, modulating sleep architecture, and indirectly influencing mood (69). Hormonal imbalances during the perimenopausal period can therefore perturb sleep–wake cycles and emotional regulation, contributing to the development of insomnia, mood disturbances, irritability, and other associated symptoms (70, 71). The treatment of PMI can be nonpharmacologic, pharmacologic, or both. Non-pharmacological interventions include aromatherapy, hypnosis, psychotherapy, cognitive behavioral therapy (CBT), and music therapy (72). In China, however, pharmacological treatment with Western medicine remains the primary approach for managing PMI. Conventional pharmacological treatments, such as benzodiazepine hypnotics, non–benzodiazepine receptor agonists and HRT, have shown efficacy in alleviating insomnia but remain limited by adverse events and drug dependence (6, 73). Consequently, there has been increasing interest in complementary and integrative approaches, with TCM emerging as a potential therapeutic option for PMI. According to TCM theory, PMI is associated with multiple factors, including liver and kidney deficiency, yin-yang imbalance, dual deficiency of the heart and spleen, as well as disharmony of qi and blood. Such deficiencies and imbalances are believed to disrupt the smooth flow and transformation of qi and blood, impair the nourishment of the shen (spirit), and compromise the body’s ability to regulate emotions and maintain physiological homeostasis, leading to heat rash, night sweats, emotional instability, and sleep disturbances (74). Various TCM interventions, including herbal medicine, acupuncture, and combined use of Chinese and Western medicine, have demonstrated the therapeutic advantages of TCM in the management of PMI. Herbal formulations such as Chaihu Jia Longgu Muli decoction and Kuntai capsule can regulate the hormonal levels in patients with PMI to alleviate insomnia symptoms (75, 76). Acupuncture is another widely utilized TCM therapy for treating PMI, with advantages including broad indications, significant efficacy, high cost-effectiveness, and few adverse reactions. Accumulating evidence from previous clinical and experimental studies indicates that acupuncture exerts its therapeutic effects on insomnia through multiple neurobiological pathway, including vagal stimulation, enhancement of 5-HT neurotransmission, and modulation of HPO axis (77–79). In addition, combination therapy has emerged as an increasingly prevalent strategy in the treatment of PMI. Integrating traditional Chinese and Western medicines, or combining acupuncture with TCM, not only facilitate the rapid alleviation of diverse symptoms in patients with PMI, but also may mitigate the adverse effects often associated with long-term use of synthetic hormones or sedative-hypnotic drugs (80, 81). Moreover, TCM can alleviate patients’ depression and anxiety by enhancing monoamine neurotransmitter levels, suppressing hyperactivity of the hypothalamic–pituitary–adrenal (HPA) axis, modulating hippocampal neurons and neurotrophic factors, regulating immune cytokines, counteracting excitatory amino acid toxicity, and modulating the microbiota–gut–brain axis (82–84).

Our systematic review and meta-analysis comprehensively synthesized available evidence from 48 RCTs encompassing a total of 5,037 participants, thereby providing robust and quantitatively rigorous insights into the therapeutic efficacy and safety profile of TCM in the management of PMI. The results demonstrated that TCM interventions, whether administered as monotherapy or integrated with conventional pharmacological or acupuncture, exhibited statistically significant superiority over Western medicines in enhancing multiple clinically relevant outcomes. Specifically, TCM was associated with a greater improvement in overall treatment efficiency along with significant amelioration in sleep quality indicated by reductions in PSQI scores, favorable modulation of key endocrine markers such as E2, FSH, and LH, and notable alleviation of menopausal symptoms reflected by decreased KMI scores. Additionally, psychological parameters including anxiety and depression levels, as assessed by the SAS score and SDS score, showed more pronounced improvement in the TCM groups. While enhancements in TCMS scores and SDS scores were also observed following TCM treatment, these effects were accompanied by considerable heterogeneity, and subsequent subgroup analyses revealed inconsistent findings, suggesting the need for cautious interpretation and further investigation. Of particular clinical significance was the safety profile of TCM interventions, which were consistently associated with a markedly lower incidence of adverse reactions compared to control groups, indicating a favorable risk–benefit ratio.

Notably, although subgroup analysis was conducted by therapeutic type, several outcome measures in this meta-analysis still exhibited substantial heterogeneity (I2 > 50%). To further identify potential sources of heterogeneity, we performed regression analysis targeting these indicators, with sample size, age of participants, and follow-up duration as the explanatory variables. The regression analysis results revealed that sample size and follow-up duration were statistically significant factors explaining the high heterogeneity of TCMS (both p < 0.05), while none of the three factors exerted a significant explanatory effect on the heterogeneity of the remaining six indicators (all p > 0.05). The result suggested that this substantial residual heterogeneity may be attributed to other unexamined factors, including differences in TCM syndrome differentiation, different diagnostic criteria for PMI across studies, diverse symptom presentations of PMI patients, or inconsistencies in outcome assessment tools. Moreover, the subgroup analysis results indicated that no statistically significant differences were observed among subgroups in most outcome measures. This suggests that the choice of TCM intervention may have less impact on outcomes. Sensitivity analyses conducted for each outcome measure confirmed the stability and reliability of our results. However, further studies with larger sample sizes are needed to confirm these findings.

Compared to previous meta-analyses (80, 81, 85), this study has the following advantages: (1) it included a larger number of clinical randomized controlled trials (48 in total) and patients (5,037 cases). (2) It included more comprehensive outcome measures. (3) We conducted detailed subgroup analyses to assess the efficacy and safety of three common TCM therapies for PMI. (4) We rated the certainty of evidence using the latest GRADE approach.

This study has the following limitations: (1) although most trials reported improvements favoring TCM, methodological quality was generally moderate. Notably, all included studies were single-center investigations, with a distinct paucity of multi-center RCTs in the current literature. Additionally, many studies failed to provide detailed descriptions of randomization procedures, allocation concealment, or blinding methods. (2) The control groups were limited to conventional Western medicine, which may limit the generalizability of the results. (3) Some outcome measures could not be extracted, which may lead to bias in some results. (4) The heterogeneity of some outcome indicators was high, which may affect the accuracy of the results. (5) All included studies were conducted in mainland China, where participants share specific genetic backgrounds, lifestyle patterns, and local TCM clinical practice norms. This regional restriction potentially limits the generalizability of our findings to broader populations, especially those from other countries or regions with distinct ethnic compositions and medical care systems. In conclusion, this meta-analysis provides compelling evidence that TCM interventions represent a safe, well-tolerated, and effective therapeutic option for patients suffering from PMI, with the potential to improve both physiological and psychological dimensions of the disorder, thus warranting consideration in integrative clinical management strategies and further validation through large-scale, high-quality randomized trials.

 Conclusion

This systematic review and meta-analysis provide compelling evidence that TCM appears to be a promising and relatively safe option for patients with PMI. Clinically, these findings offer robust evidence-based support for integrating TCM into the standardized management of PMI patients, to alleviate symptoms and improve quality of life without severe adverse reactions. However, future research should prioritize rigorous methodological designs, larger sample sizes, longer follow-up, objective sleep measures and international collaborations to further substantiate these findings and guide evidence-based integration of TCM into clinical practice.

 Data availability statement

The original contributions presented in the study are included in the article/Supplementary material, further inquiries can be directed to the corresponding author.

 Author contributions

DY: Conceptualization, Data curation, Formal analysis, Methodology, Software, Writing – original draft. DC: Data curation, Formal analysis, Methodology, Writing – original draft. JP: Data curation, Formal analysis, Writing – original draft. YP: Conceptualization, Data curation, Writing – original draft. CY: Conceptualization, Methodology, Writing – original draft, Writing – review & editing. JS: Conceptualization, Funding acquisition, Methodology, Resources, Supervision, Writing – original draft, Writing – review & editing.

 Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

 Generative AI statement

The author(s) declared that Generative AI was not used in the creation of this manuscript.

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 Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

 Supplementary material

The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fneur.2026.1749660/full#supplementary-material

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Edited by: Iván Pérez-Neri, National Institute of Rehabilitation Luis Guillermo Ibarra Ibarra, Mexico

Reviewed by: Paulo Sargento, Lusofona University, Portugal

Jieying Zhang, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, China