Chinese herbal medicine for insomnia: A systematic review and network meta-analysis

Abstract

Objective:

Insomnia represents a significant public health issue, with a notable impact on the global burden of disease. Traditional pharmacological interventions, while effective, often entail limitations and adverse effects, necessitating the exploration of alternative therapeutic modalities. Chinese herbal medicines, with their extensive historical use and presumed multifaceted pharmacological actions, emerge as potential candidates for insomnia management.

Methods:

In strict adherence to the PRISMA-NMA guidelines, we systematically reviewed randomized controlled trials (RCTs) that investigated the therapeutic effects of Chinese herbal medicines on insomnia. The primary outcomes assessed were improvements in sleep quality as measured by the Pittsburgh Sleep Quality Index (PSQI), clinical effectiveness rates, and the incidence of adverse reactions. Comprehensive searches were conducted across several databases including MEDLINE, Cochrane Library, EMBASE, Wanfang Data, CNKI, and gray literature. Both direct and indirect evidence was synthesized using Bayesian network meta-analysis techniques to ascertain the relative performance of various herbal interventions.

Results:

The analysis included 186 RCTs involving 13 different herbal interventions. Overall, the included studies exhibited a low-to-moderate risk-of-bias. Key findings from our study suggest that for PSQI scores, the top 5 treatments were guipi decoction, shenqi schisandra tablet, chaihu longgu muli decoction (CLMD), suanzaoren, and wuling capsule. Notably, the highest rankings for effective rate were achieved by longdan xiegan decoction, CLMD, guipi decoction, Huanglian Wendan decoction, and chaihu shugan powder. In terms of safety, jieyu pill, trazodone, and CLMD were the top 3, indicating superior safety profiles among all treatments. Crucially, both the PSQI scores and the effective rate, alongside the safety profile of most Chinese herbal medicines, were generally superior to conventional pharmaceutical treatments.

Conclusion:

The study provides robust evidence that certain herbal medicines may offer effective and safe alternatives for managing insomnia, potentially reducing the reliance on conventional pharmacological interventions.

1. Introduction

Insomnia, a prevalent sleep disorder, markedly affects the global adult population, posing a substantial public health challenge.^[1] Approximately 10% of adults worldwide experience at least one symptom of insomnia, with its prevalence showing a concerning upward trend.^[2,3] The disorder is characterized by difficulties in initiating sleep, maintaining consistent sleep patterns, and premature morning awakenings.

Literature indicates that insomnia can result in several significant health issues, including depression, anxiety disorders, compromised immune function, increased suicidal tendencies, and heightened risk of cardiovascular diseases.^[4] Beyond physical and mental symptoms such as fatigue, memory impairment, and irritability, insomnia significantly undermines daily functioning, daytime productivity, and overall quality of life. These impacts underscore the imperative to address insomnia as a critical public health issue. Additionally, insomnia contributes to elevated medical costs and a general welfare burden.^[5,6]

Cognitive-behavioral therapy for insomnia is the preferred and recommended intervention, recognized for its efficacy and safety.^[7,8] However, its practical application is often constrained by patient compliance challenges and the necessity for skilled psychotherapists. The Food and Drug Administration approves several pharmacotherapeutic agents for use in insomnia, including gamma-aminobutyric acid type A receptor (benzodiazepines, and non-benzodiazepine Z drugs), orexin receptor, or melatonin receptor (ramelteon).^[9] Additionally, many medications are commonly used by clinicians for treating insomnia, including antidepressants, anticonvulsants, mood-stabilizing agents, and antipsychotics. Melatonin is also used in patients with delayed sleep phase syndrome.^[10] However, their prolonged use is frequently associated with significant side effects, such as abuse potential, daytime somnolence, and risks of tolerance and addiction.^[5,11–14] In light of the limitations of pharmacotherapeutic agents, there is an urgent need to identify novel and effective alternative therapies that mitigate adverse effects and enhance sleep quality in managing insomnia.^[15]

Concurrently, a variety of botanical drugs and complex formulas are gaining popularity among individuals with insomnia.^[16–18] Herbal medicine is becoming a promising alternative medicine form with a good benefit–risk ratio in countries like China, Korea, America, Europe, and Australia.^[19] Nonetheless, existing literature often focuses on individual botanical drugs, lacking concurrent assessment of various traditional decoctions and capsules, such as suanzaoren, wuling capsule, zaoren anshen capsule (ZRAS), bailemian, shenqi schisandra tablet (SST), chaihu longgu muli decoction (CLMD), chaihu shugan powder (CSP), guipi decoction, and Huanglian Wendan decoction (HLWDD).^[20–28] Therefore, comparing the efficacy and safety of different botanical drugs for insomnia treatment remains a complex challenge, often confounding clinicians in clinical settings.

Network meta-analysis (NMA) is an advanced statistical technique used to compare and analyze the effectiveness of multiple interventions simultaneously, unlike traditional meta-analysis, which typically compares 2 treatments at a time. NMA integrates both direct evidence (comparisons within the same studies) and indirect evidence (comparisons across different studies sharing a common comparator). This approach increases the statistical power and can provide more comprehensive insights into the relative effectiveness of various treatments. It is valuable for evidence-based medicine, helping to make informed decisions about the best available treatments in the medical field.^[29]

Currently, Chinese herbal medicines are widely adopted and have achieved the desired efficacy. The purpose of this Bayesian NMA is to comprehensively evaluate the available data regarding the efficacy and safety of various herbal medicines in treating insomnia, then investigate the optimal strategy of adults with insomnia treatment and to strengthen additional insights for clinical practice in the future.

2. Methods

A network systematic review and meta-analysis focusing on interventions for insomnia was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) extension statement for network meta-analyses guidelines. The protocol for this review was prospectively registered with PROSPERO (ID: CRD42023492050). The researchable question was structured using the PICOS (Population, Intervention, Comparison, Outcome, Study design) format. Population: patients diagnosed with insomnia were included. Intervention: patients with insomnia received a single Chinese medicine formulation without combining it with conventional therapies for insomnia. Comparison: participants were assigned to medicinal herb, placebo, conventional medicine, or no-treatment for the treatment of insomnia. Outcome: the main outcomes included Pittsburgh Sleep Quality Index (PSQI) score, clinical effectiveness rate, and the incidence of adverse reactions. Study design: randomized controlled trials (RCTs).

2.1. Data searches

Exhaustive searches were conducted across multiple databases from their inception until May 2024. These databases included MEDLINE, the Cochrane Library, EMBASE, Wanfang Data, and CNKI, with the aim of identifying studies that evaluate the effectiveness of botanical drugs for treating insomnia. Grey literature was also searched.

2.2. Inclusion and exclusion criteria

The inclusion criteria were as follows: Adult patients (≥18 years) diagnosed with insomnia were based on established diagnostic criteria, such as the International Classification of Sleep Disorders, Third Edition (ICSD-3), the Chinese Classification of Mental Disorders, Second Revised Edition (CCMD-2-R) and the updated version 3 Chinese Classification of Mental Disorders (CCMD-3),^[30,31] the Diagnostic and Statistical Manual of Mental Disorders,^[32] and the International Statistical Classification of Diseases and Related Health Problems, Tenth Edition, International Statistical Classification of Diseases and Related Health Problems tenth edition (ICD-10)^[2,33] Comparison: participants were assigned to medicinal herb, placebo, conventional medicine, or no-treatment for the treatment of insomnia.^[3] Publications reporting the following efficacy/safety outcomes: PSQI score, clinical effectiveness rate, and the incidence of adverse reactions. The PSQI is crucial for assessing sleep quality and provides a comprehensive and standardized measure of sleep patterns, disturbances, and overall sleep health. The clinical effectiveness rate is recommended in the Criteria of Diagnosis and Therapeutic Effect of Diseases and Syndromes in Traditional Chinese Medicine.^[34] The clinical effective rate = (cured + improved) cases/total cases × 100%. The incidence of adverse reactions, which measures the ratio of patients encountering at least one adverse event to the total patient count within either the intervention or control group, represents a universally recognized parameter for assessing safety^[4,35–37] Only RCTs.

The exclusion criteria were as follows: patients receiving combinations of pharmaceutical treatments (biomedicine, herbal medicine), cognitive-behavioral therapy for insomnia in the intervention or control group.^[2] Insomnia defined as a symptom or a complaint only, not primary insomnia.^[3] Animal studies, case reports, incomplete raw data, and reviews.

2.3. Data extraction and quality assessment

Data extraction from the studies encompassed participant demographics, including gender, age, and group-specific sample sizes. The specifics of the interventions and control conditions were also detailed, encompassing dosages of medication, duration of treatment, method of administration, therapeutic course, and diagnostic criteria. Outcome measures, including PSQI score, clinical effectiveness rate, and the incidence of adverse events, were meticulously recorded. The quality of the included studies was appraised using the Cochrane Collaboration’s Risk of Bias assessment tool (RoB 2.0 Tool).^[38] Bias risk was categorized into 3 levels: “low risk of bias,” “some concerns,” and “high risk of bias.” Data extraction and quality assessment were independently performed by 2 reviewers, CD and YL, utilizing a standardized form. In instances of disagreement, a consensus was achieved through discussion with a third reviewer, WL.

2.4. Statistical analysis

The Bayesian NMA compares various interventions and incorporates a substantial number of indirect comparisons, and the Markov chain Monte Carlo method has been used.^[39] This approach uses random-effects generalized linear model for Bayesian NMA. The nma.fit() function is proficient in conducting model fitting and identifying potential outliers. The lever diagram elucidates the comparison between leverage_ik (leverage for test i in arm k) and Bayesian deviation residuals across all I tests in each of the K arms, proving invaluable in highlighting potential outliers in model fitting. Specifically, a data point outside the purple arc may indicate suboptimal model fitting. Odds ratios (ORs) or their logarithms were utilized as the effect index for counting data, with their 95% confidence intervals (CI) serving as boundaries.^[40] The mean difference was used as the statistical effect size for continuous variables, and the OR for binary variables, contingent on the type of outcome data. A difference was deemed statistically significant when the OR value did not encompass 1 within the 95% CI. Statistical heterogeneity was assessed using the I² statistic.^[41] The extent of publication bias was gauged by analyzing the symmetry of individual study points within a funnel plot. Symmetrical distribution intimates a diminished likelihood of publication bias. Model convergence was ascertained using the Gelman-Rubin method, complemented by a density plot and trajectory plot. Network meta-analyses were executed for each collated outcome of the studies, with the extant evidence summarized through the construction of 3 network graphs. The efficacy and safety of various drugs in treating insomnia were ranked according to the surface under the cumulative ranking (SUCRA) curve.^[42] Pairwise meta-analyses are conducted using Stata, version 17, whilst network meta-analyses within a Bayesian framework will be undertaken using R software, version 4.3.1 (R Foundation for Statistical Computing, Shanghai, Asia), employing the “gemtc 0.8-2” and “JAGS” (version 3.5.3) packages.^[43–45] A P-value of <.05 was considered indicative of statistical significance.

3. Results

3.1. Study selection

After the initial search of the literature via databases (MEDLINE, EMBASE, the Cochrane Library, CNKI, and Wanfang Data) and gray literature, a total of 9112 citations were preliminarily identified. After removing 1959 duplicates and 2134 irrelevant papers, 5019 articles were retrieved from titles and abstracts. A total of 3459 eligible records were identified for full-text review in this NMA. Subsequently, 2607 citations that fulfilled the exclusion criteria for this study were removed.

Ultimately, 186 publications were included, as depicted in Figure 1.^[46–231]

Figure 1.

PRISMA flow diagram. PRISMA = Preferred Reporting Items for Systematic Reviews and Meta-Analyses.

3.2. Study and participant characteristics

In this meta-analysis, 186 RCTs evaluated the therapeutic efficacy and safety of 13 distinct botanical drugs compared to placebos or standard treatments, involving 9808 patients with insomnia randomized to various interventions and 9146 to control groups. The herbal treatment arms in these studies varied considerably in size, with participant numbers ranging from 8 to 340.

Specifically, the dataset included 22 RCTs on bailemian, enrolling 1387 patients and 1080 controls; 9 RCTs investigated SST, comprising 461 patients and an equal number of controls; 21 RCTs focused on CLMD, with 1044 patients and 1041 controls; 4 RCTs on CSP involved 166 patients and 155 controls; 22 RCTs assessed guipi decoction, including 1054 patients and 1048 controls; 16 RCTs on HLWDD encompassed 741 patients and 708 controls; 4 RCTs on jieyu pill had 144 patients and 122 controls; longdan xiegan decoction (LXD) was examined in 9 RCTs with 493 patients and 472 controls; 5 RCTs on qiyeshenanpian included 614 patients and 335 controls; shumian capsule was the focus of 13 RCTs, involving 815 patients and 810 controls; 29 RCTs on suanzaoren included 1400 patients and 1376 controls; wuling capsule was examined in 12 RCTs with 502 patients and 483 controls; ZRAS was studied in 20 RCTs, involving 987 patients and 1055 controls.

All 186 RCTs assessed the efficacy (PSQI score, clinical effectiveness rate) or safety (the rate of adverse reactions) of botanical drugs. Most of the trials adopted the CCMD diagnostic criteria. The median follow-up period for these trials ranged from 1 week to 16 weeks. All studies were conducted in China. Detailed baseline characteristics of the included studies were presented in Table 1. Main metabolites of botanical drugs were depicted in Table 2.

Table 1.

Basic characteristics of the included studies.

Study	Patients of IG	Male	Female	Patients of CG	Male	Female	Age of IG, CG (mean ± SD)	Age of CG, CG (mean ± SD)	Treatment intervention	Interventions dose, route	Control intervention	Control measures, dose, route	Outcome measure	Diagnostic instrument	follpw-up (week)
Chen RF 2006	46	12	34	38	9	29	25–65	25–65	Bailemian	1.08 g, pod, bid, 4 wk	TWBX	9 g, pod, bid, 4 wk	*	CCMD-3	4
Du XQ 2011	42	15	27	40	12	28	24–74	26–68	Bailemian	0.81 g, pod, tid, 4 wk	Diazepatn	5 mg, pod, qd, 4 wk	*	CCMD-3	4
He ZW 2010	60	38	22	60	38	22	39.6 ± 3.3	39.4 ± 3.1	Bailemian	1.08 g, pod, tid, 2 wk	BZYXW	15 g, pod, bid, 2 wk	*,†,‡	CCMD-3	2
Hu CL 2017	60	35	25	60	36	24	38.8 ± 2.6	38.5 ± 2.8	Bailemian	1.08 g, pod, tid, 2 wk	BZYXW	15 g, pod, bid, 2 wk	*	CCMD-3	2
Huang Y 2017	60	35	25	60	33	27	75.27 ± 14.73	76.93 ± 13.89	Bailemian	1.08 g, pod, bid, 8 wk	Estazolam	1 mg, pod, qd, 8 wk	*,†	CCMD-3	8
Mai J 2009	30	12	18	30	14	16	38.20 ± 3.12	38.60 ± 3.31	Bailemian	1.08 g, pod, bid, 3 wk	Triazolam	0.25 mg, pod, qd, 3 wk	*,†,‡	CCMD-3	3
Qiu XQ 2013	34	19	15	34	20	14	35.0 ± 13.5	38.0 ± 15.5	Bailemian	1.08 g, pod, tid, 1 wk	Suanzaoren	0.4 g, pod, qd, 1 wk	*	CCMD-2R	1
Shi XR 2019	62	34	28	62	32	30	45.02 ± 5.25	45.54 ± 5.28	Bailemian	1.08 g, pod, bid, 1 wk	Wuling capsule	0.99 g, pod, tid, 1 wk	*,‡	ICD-10	1
Si JW 2014	44	/	/	44	/	/	46–54	46–54	Bailemian	0.81 g, pod, tid, 2 wk	Diazepatn	5 mg, pod, qd, 2 wk	*,‡	CCMD-3	2
Tang XJ 2008	30	14	16	30	12	18	45.02 ± 12.51	47.66 ± 13.97	Bailemian	1.08 g, pod, bid, 2 wk	TWBX	9 g, pod, bid, 2 wk	*	CCMD-3	2
Wang HQ 2019	50	14	36	40	12	28	45.68 ± 3.54	41.08 ± 3.61	Bailemian	1.08 g, pod, bid, 4 wk	TWBX	9 g, pod, bid, 4 wk	*	CCMD-3	4
Wang DJ 2013	40	/	/	40	/	/	18–60	17–60	Bailemian	1.08 g, pod, bid, 8 wk	Diazepatn	5 mg, pod, qd, 8 wk	*,‡	CCMD-3-R	8
Wang L 2021	44	25	19	44	24	20	48.56 ± 3.39	48.87 ± 3.47	Bailemian	1.08 g, pod, bid, 4 wk	Estazolam	1 mg, pod, qd, 4 wk	*,†,‡	CCMD-3	4
Yin JL 2016	32	/	/	32	/	/	36.52 ± 9.10	35.14 ± 6.25	Bailemian	1.08 g, pod, bid, 4 wk	Diazepatn	5 mg, pod, qd, 4 wk	*,‡	ICD-10	4
Zhang SJ 2017	44	16	28	39	16	23	50.4 ± 14.0	51.3 ± 13.5	Bailemian	1.08 g, pod, bid, 2 wk	Wuling capsule	0.99 g, pod, tid, 2 wk	†,‡	ICD-10	2
				41	14	27	50.4 ± 14.0	48.7 ± 12.1	Bailemian	1.08 g, pod, bid, 2 wk	Oxazepam	15 mg, pod, qd, 2 wk	*,†,‡	ICD-10	2
Zhang TH 2015	18	5	13	18	6	12	65.4 ± 8.37	66.2 ± 6.49	Bailemian	1.08 g, pod, bid, 2 wk	Estazolam	2 mg, pod, qd, 2 wk	*	CCMD-3	2
Zhang YL 2015	132	54	78	47	18	29	29–69	19–63	Bailemian	1.08 g, pod, bid, 2 wk	Estazolam	2 mg, pod, qd, 2 wk	*	CCMD-3	2
Zhao ZX 2006	88	/	/	78	/	/	25–65	25–65	Bailemian	1.08 g, pod, bid, 2 wk	Suanzaoren	0.4 g, pod, qd, 2 wk	*	CCMD-2R	2
Zhou B 2015	30	7	23	30	9	21	45–78	45–78	Bailemian	1.08 g, pod, bid, 4 wk	Estazolam	1 mg, pod, qd, 4 wk	*,‡	CCMD-3	4
Zhou WF 2014	45	/	/	45	/	/	18–65	18–65	Bailemian	1.08 g, pod, bid, 2 wk	Diazepatn	3.75 mg, pod, qd, 2 wk	*,‡	CCMD-3	2
Zhou XY 2018	56	/	/	56	/	/	/	/	Bailemian	1.08 g, pod, bid, 2 wk	Wuling capsule	0.99 g, pod, tid, 2 wk	*	CCMD-3	2
Zou JD 2014	340	112	228	112	38	74	45.44 ± 13.71	43.73 ± 14.78	Bailemian	1.08 g, pod, bid, 4 wk	TWBX	9 g, pod, bid, 4 wk	†,‡	ICSD-3	5
Zeng ZL 2014	50	32	18	50	28	22	26–72	26–72	SST	1.25 g, pod, tid, 8 wk	Alprazolam	0.8 mg, pod, qd, 8 wk	†	CCMD-3	9
Liu Q 2009	30	12	18	30	13	17	18–52	17–52	SST	0.75 g, pod, tid, 6 wk	Estazolam	2.5 mg, pod, qd, 6 wk	*	CCMD-3	6
Song RX 2015	98	38	60	98	38	60	51.5 ± 2.3	52.3 ± 3.1	SST	0.75 g, pod, tid, 4 wk	Estazolam	2 mg, pod, qd, 4 wk	*	CCMD-3	4
Tian J 2010	30	14	16	30	12	18	70 ± 7	67 ± 5	SST	0.75 g, pod, tid, 8 wk	Estazolam	1 mg, pod, qd, 8 wk	*,‡	CCMD-3	8
Yan Q 2012	46	18	28	46	19	27	34–68	33–69	SST	0.75 g, pod, tid, 8 wk	Estazolam	1 mg, pod, qd, 8 wk	*	CCMD-3	8
Yu ZA 2009	50	24	29	50	22	29	/	/	SST	1.25 g, pod, tid, 8 wk	Alprazolam	0.8 mg, pod, qd, 8 wk	†	CCMD-3	8
Zhang L 2018	51	28	23	51	27	24	38.7 ± 4.6	39.2 ± 4.8	SST	0.75 g, pod, tid, 4 wk	Estazolam	2 mg, pod, qd, 4 wk	*,‡	CCMD-3	4
Zhang XE 2012	46	18	28	46	19	27	34–68	33–69	SST	0.75 g, pod, tid, 4 wk	Estazolam	2 mg, pod, qd, 4 wk	*,‡	CCMD-3	4
Zhao KQ 2010	60	32	28	60	28	32	20–82	16–76	SST	1.25 g, pod, tid, 8 wk	Oryzanol	20 mg, pod, tid, 8 wk	*	CCMD-3	8
Chen WC 2021	40	14	26	40	15	25	44.49 ± 3.48	44.53 ± 3.45	CLMD	/	Estazolam	1 mg, pod, qd, 2 wk	*	CCMD-3	2
Chen XZ 2017	46	15	31	46	19	27	41.3 ± 6.2	39.5 ± 7.8	CLMD	/	Estazolam	1 mg, pod, qd, 4 wk	*,†	CCMD-3	4
Feng EB 2022	90	39	51	90	37	53	59.17 ± 8.66	59.44 ± 8.69	CLMD	/	Estazolam	1 mg, pod, qd, 8 wk	*,†,‡	CCMD-3	8
He SY 2023	35	16	19	35	17	18	36.31 ± 2.98	35.23 ± 2.89	CLMD	/	Estazolam	1 mg, pod, qd, 3 wk	*,†	CCMD-3	3
Huang QY 2016	30	10	20	30	9	21	50.01 ± 1.29	49.65 ± 1.32	CLMD	/	Estazolam	1 mg, pod, qd, 4 wk	*,‡	CCMD-3	4
Lai SH 2016	53	33	20	53	35	18	34.6 ± 3.4	35.3 ± 3.2	CLMD	/	Estazolam	1 mg, pod, qd, 4 wk	*	CCMD-3	4
Lei HM 2017	31	15	16	29	14	15	35.38 ± 10.2	35.59 ± 10.8	CLMD	/	Estazolam	1 mg, pod, qd, 3 wk	*	CCMD-3	3
Li N 2010	45	19	26	45	17	28	35–65	33–67	CLMD	/	ZRAS	0.18 g, pod, qd, 4 wk	*	CCMD-3	4
Liu Y 2022	43	25	18	43	23	20	45.31 ± 5.18	45.33 ± 5.21	CLMD	/	Estazolam	1 mg, pod, qd, 4 wk	*,†	CCMD-3	4
Luo JH 2020	30	18	12	30	23	7	35.32 ± 6.56	33.53 ± 5.68	CLMD	/	Zolpidem tartrate	10 mg, pod, qd, 4 wk	*,†,‡	CCMD-3	4
Lv GL 2023	52	31	21	53	30	23	43.31 ± 8.98	43.25 ± 8.13	CLMD	/	Estazolam	1 mg, pod, qd, 4 wk	*,†	ICSD-3	4
Wang B 2016	40	15	25	40	16	24	44.63 ± 9.17	43.31 ± 8.68	CLMD	/	Oryzanol	200 mg, pod, qd, 4 wk	*,†,‡	CCMD-3	4
Wang JL 2017	51	/	/	49	/	/	/	/	CLMD	/	Zolpidem tartrate	10 mg, pod, qd, 4 wk	*,†,‡	CCMD-3	4
Wang LZ 2016	30	8	22	30	11	19	44.07 ± 5.31	41.76 ± 5.54	CLMD	/	TOL	1.2 g, pod, bid, 4 wk	*,†	ICSD-3	4
Wen LM 2021	102	51	51	102	50	52	72.22 ± 8.09	72.16 ± 8.39	CLMD	/	Estazolam	2 mg, pod, tid, 4 wk	*,†	CCMD-3	4
Xin H 2017	140	53	87	140	63	77	45.4 ± 5.4	47.0 ± 6.2	CLMD	/	Estazolam	1 mg, pod, qd, 2 wk	*,†	CCMD-3	2
Xu CF 2014	32	18	14	32	19	13	46.1 ± 7.6	45.3 ± 6.8	CLMD	/	Estazolam	1 mg, pod, qd, 2 wk	*	CCMD-3	2
Yuan YH 2022	40	10	30	40	11	29	47.5 ± 6.9	47.2 ± 6.8	CLMD	/	Estazolam	2 mg, pod, qd, 4 wk	*,†,‡	CCMD-3	4
Zheng GL 2014	40	16	24	40	17	23	40.35 ± 10.31	39.35 ± 10.01	CLMD	/	Estazolam	2 mg, pod, qd, 4 wk	*	CCMD-3	4
Zhong W 2018	39	14	25	39	14	25	/	/	CLMD	/	Estazolam	2.5 mg, pod, qd, 4 wk	*,‡	CCMD-3	4
Zhu HX 2021	35	21	14	35	22	13	53.9 ± 5.1	53.5 ± 4.9	CLMD	/	Estazolam	1 mg, pod, qd, 3 wk	*	CCMD-3	3
Lin MM 2023	45	18	27	44	25	19	35.25 ± 7.66	35.12 ± 6.80	CSP	100 mL, pod, bid, 4 wk	Zopiclone	3.75, pod, qd, 4 wk	*,‡	CCMD-3	4
Yang DF 2015	60	23	37	60	26	34	18–68	19–65	CSP	100 mL, pod, bid, 4 wk	Estazolam	1 mg, pod, qd, 4 wk	*,†	CCMD-3	4
Yin S 2008	33	/	/	31	/	/	32.16 ± 4.04	31.47 ± 3.17	CSP	100 mL, pod, bid, 2 wk	Estazolam	2 mg, pod, qd, 2 wk	*,‡	CCMD-3	2
Zhang AL 2010	28	11	17	20	8	12	45.93 ± 4.30	45.95 ± 6.81	CSP	100 mL, pod, bid, 4 wk	TWBX	3 g, pod, tid, 4 wk	*	CCMD-3	4
Chen W 2014	45	27	18	44	27	17	46.3 ± 6.8	46.3 ± 6.8	Guipi decoction	/	Alprazolam	0.4 mg, pod, qd, 4 wk	*,‡	CCMD-3	4
Fu JJ 2013	55	21	34	55	23	32	20–65	21–64	Guipi decoction	/	Estazolam	2 mg, pod, qd, 4 wk	*	CCMD-3	3
Guo CY 2011	60	/	/	60	/	/	/	/	Guipi decoction	/	Estazolam	2 mg, pod, qd, 2 wk	*,†	CCMD-3	6
He XY 2015	77	45	32	63	40	23	49.5 ± 7.4	48.4 ± 6.9	Guipi decoction	/	Estazolam	2 mg, pod, qd, 4 wk	*,†,‡	CCMD-3	4
Jia QZ 2013	65	/	/	64	/	/	/	/	Guipi decoction	/	Estazolam	2 mg, pod, qd, 6 wk	*	CCMD-3	6
Kong LK 2016	43	23	20	43	22	21	50.10 ± 2.22	50.05 ± 2.17	Guipi decoction	/	Diazepatn	10 mg, pod, qd, 4 wk	*	CCMD-3	4
Li J 2012	36	13	23	32	12	20	42–75	42–75	Guipi decoction	/	Estazolam	2 mg, pod, qd, 2 wk	*,‡	CCMD-3	2
Liu GQ 2015	50	/	/	35	/	/	/	/	Guipi decoction	/	Estazolam	1 mg, pod, qd, 4 wk	*,†	CCMD-3	4
				35	/	/	/	/	Guipi decoction	/	Suanzaoren	2.4 g, pod, qd, 4 wk	*,†	CCMD-3	4
Liu JM 2016	50	22	28	50	24	26	44.6 ± 1.3	45.2 ± 1.1	Guipi decoction	/	Estazolam	2 mg, pod, qd, 6 wk	*,‡	CCMD-3	6
Liu YG 2018	24	17	7	24	18	6	45.3 ± 4.7	45.4 ± 4.8	Guipi decoction	/	Estazolam	1 mg, pod, qd, 4 wk	*	CCMD-3	4
Lv TM 2015	47	21	26	47	23	24	57.2 ± 2.3	58.7 ± 2.4	Guipi decoction	/	Estazolam	1 mg, pod, qd, 3 wk	*	CCMD-3	3
Miao YN 2015	54	23	31	54	22	32	58.9 ± 2.4	59.0 ± 2.1	Guipi decoction	/	Estazolam	1 mg, pod, qd, 3 wk	*	CCMD-3	3
Qi XM 2018	47	22	25	46	24	22	55.94 ± 11.49	56.30 ± 10.77	Guipi decoction	/	Estazolam	1 mg, pod, qd, 4 wk	*	CCMD-3	4
Qian YH 2021	30	17	13	30	18	12	51.22 ± 10.15	51.24 ± 10.17	Guipi decoction	/	Estazolam	1 mg, pod, qd, 4 wk	*,‡	CCMD-3	4
Su LD 2010	48	17	31	48	20	28	/	/	Guipi decoction	/	Estazolam	2 mg, pod, qd, 4 wk	*	CCMD-3	4
Wang BD 2020	35	3	33	35	3	32	49 ± 4.3	49 ± 4.1	Guipi decoction	/	Estazolam	2 mg, pod, qd, 4 wk	*	CCMD-3	4
Xu Y 2016	35	12	23	35	8	27	47.14 ± 17.26	46.00 ± 15.37	Guipi decoction	/	Lorazepam	20 mg, pod, qd, 4 wk	*,‡	ICSD-3	4
Xue GT 2016	60	32	28	56	30	26	33.59 ± 6.12	36.24 ± 7.36	Guipi decoction	/	Estazolam	1 mg, pod, qd, 4 wk	*,‡	CCMD-3	4
Yang C 2015	42	/	/	42	/	/	/	/	Guipi decoction	/	Estazolam	1 mg, pod, qd, 4 wk	*,†	CCMD-3	4
Yao ZQ 2018	52	21	31	52	19	33	45.87 ± 9.62	44.69 ± 9.15	Guipi decoction	/	Estazolam	1 mg, pod, qd, 4 wk	†,‡	CCMD-3	4
Zhao Y 2013	34	/	/	34	/	/	/	/	Guipi decoction	/	Estazolam	1 mg, pod, qd, 12 wk	*,†	CCMD-3	12
Zhu XZ 2017	65	31	34	64	30	34	53.69 ± 6.71	52.65 ± 6.58	Guipi decoction	/	Diazepatn	5 mg, pod, tid, 4 wk	*,†	CCMD-3	4
Chao Z 2013	35	21	14	15	10	5	33.09 ± 9.23	35.64 ± 8.15	HLWDD	/	Estazolam	0.4 mg, pod, qd, 2 wk	*,‡	CCMD-2	2
Chen XY 2020	30	18	12	30	16	14	18–75	18–74	HLWDD	/	Estazolam	1 mg, pod, qd, 4 wk	*	CCMD-3	4
Chen XM 2019	40	25	15	40	23	17	38.8 ± 4.6	38.6 ± 4.3	HLWDD	/	Estazolam	5 mg, pod, qd, 3 wk	*,‡	CCMD-3	3
Chen ZL 2010	40	12	20	40	11	17	39–62	40–60	HLWDD	/	Estazolam	2 mg, pod, qd, 4 wk	*,‡	CCMD-3	4
Gong XQ 2018	40	16	24	40	18	22	42.39 ± 6.75	42.16 ± 6.84	HLWDD	/	Zopiclone	3 mg, pod, qd, 2 wk	*,‡	CCMD-3	2
Han YH 2012	58	26	32	58	24	31	37.09 ± 11.23	37.64 ± 12.15	HLWDD	/	Estazolam	5 mg, pod, qd, 2 wk	*,‡	CCMD-3	2
Lin B 2014	60	19	41	60	22	38	22–65	21–67	HLWDD	/	Estazolam	5 mg, pod, qd, 2 wk	*,‡	CCMD-3	2
Liu M 2014	48	/	/	48	/	/	/	/	HLWDD	/	Estazolam	5 mg, pod, qd, 4 wk	*,‡	CCMD-3	4
Ruan YX 2014	112	55	57	96	47	49	37.89 ± 8.93	38.29 ± 9.18	HLWDD	/	Estazolam	1 mg, pod, qd, 4 wk	*,†,‡	CCMD-3	4
Sheng XM 2020	43	19	24	43	16	27	44.55 ± 6.21	44.51 ± 6.11	HLWDD	/	Estazolam	5 mg, pod, qd, 2 wk	*,†,‡	CCMD-3	2
Su HM 2013	70	31	39	70	33	37	45.94 ± 4.6	46.12 ± 6.32	HLWDD	/	Estazolam	2 mg, pod, qd, 4 wk	*	CCMD-3	4
Ta SM 2018	46	12	34	46	10	36	46.22 ± 3.86	46.19 ± 3.84	HLWDD	/	Estazolam	2 mg, pod, qd, 3 wk	*,‡	CCMD-3	3
Wei JQ 2022	31	19	12	31	18	13	54.4 ± 3.3	54.6 ± 3.4	HLWDD	/	Estazolam	1 mg, pod, qd, 4 wk	*,†	CCMD-3	4
Ye SJ 2015	28	/	/	31	/	/	18–65	18–65	HLWDD	/	Estazolam	1 mg, pod, qd, 3 wk	*,†,‡	CCMD-3	3
Zhang M 2021	40	19	21	40	18	22	46.8 ± 7.0	45.5 ± 6.8	HLWDD	/	TOL	20 mL, pod, bid, 2 wk	†	CCMD-3	2
Zhao YH 2014	20	13	7	20	12	8	35.28 ± 11.2	35.79 ± 11.8	HLWDD	/	Estazolam	5 mg, pod, qd, 2 wk	*	CCMD-3	2
Bai HJ 2007	31	12	19	22	8	14	44.8 ± 14.1	48.9 ± 14.6	Jieyu pill	12 g, pod, tid, 4 wk	Diazepatn	5 mg, pod, qd, 4 wk	*	CCMD-3	4
Hong YB 2004	31	12	19	22	8	14	/	/	Jieyu pill	12 g, pod, tid, 6 wk	Trazodone	0.255 mg, pod, qd, 6 wk	*,‡	CCMD-3	6
Yang XC 2012	30	13	17	30	15	15	41 ± 12	43 ± 13	Jieyu pill	8 g, pod, tid, 4 wk	Estazolam	1 mg, pod, qd, 4 wk	*,†,‡	CCMD-3	4
Zhang LF 2010	52	32	20	48	26	22	17–45	18–46	Jieyu pill	4 g, pod, tid, 4 wk	Estazolam	1 mg, pod, qd, 4 wk	*	CCMD-3	4
Chen X 2013	42	15	27	40	14	26	24–69	25–71	LXD	/	Estazolam	2 mg, pod, qd, 4 wk	*	CCMD-3	4
Li XQ 2021	75	42	33	75	40	35	54.29 ± 11.25	52.21 ± 9.98	LXD	/	Anshenbunao syrup	10 mL, pod, bid, 9 wk	*	CCMD-3	9
Liu QL 2011	79	41	38	79	43	36	28–60	30–60	LXD	/	Alprazolam	2 mg, pod, tid, 3 wk	*	CCMD-3	3
Lu JZ 2016	45	20	25	45	21	24	47.3 ± 3.4	46.5 ± 3.5	LXD	/	Estazolam	2 mg, pod, qd, 4 wk	*	CCMD-3	4
Lv GL 2021	60	30	30	60	33	27	45.6 ± 10.0	45.3 ± 10.2	LXD	/	Estazolam	2 mg, pod, qd, 3 wk	*	CCMD-3	3
Ren DW 2018	30	19	11	30	21	9	35–75	32–69	LXD	/	Estazolam	1 mg, pod, qd, 4 wk	*,†	CCMD-3	4
Shang XL 2021	40	22	18	35	19	16	48.3 ± 16.5	48.9 ± 16.3	LXD	/	Estazolam	1 mg, pod, qd, 8 wk	*	CCMD-3	8
Xu JY 2010	66	36	30	54	30	24	28–63	26–62	LXD	/	Qiyeshenanpian	100 mg, pod, tid, 3 wk	*	CCMD-2R	3
Yuan YS 2008	56	21	35	54	22	32	25–59	26–58	LXD	/	Estazolam	2 mg, pod, qd, 4 wk	*	CCMD-3	4
Chen WJ 2022	216	75	141	72	19	53	59.12 ± 7.93	59.09 ± 7.58	Qiyeshenanpian	17 mg, pod, tid, 4 wk	Placebo	/	*,†,‡	ICD-10	4
He CY 2022	202	/	/	68	/	/	/	/	Qiyeshenanpian	17 mg, pod, tid, 4 wk	Placebo	/	*,‡	ICD-10	4
Liu LS 2017	100	40	60	100	43	57	44.9 ± 14.8	42.3 ± 17.4	Qiyeshenanpian	100 mg, pod, tid, 4 wk	Estazolam	1 mg, pod, qd, 4 wk	*,†,‡	CCMD-3	4
Ni JL 2012	60	/	/	60	/	/	16–57	16–57	Qiyeshenanpian	100 mg, pod, tid, 2 wk	Estazolam	2 mg, pod, qd, 4 wk	*,‡	CCMD-3	2
Zhao LL 2005	36	15	21	35	13	22	14–18	15–18	Qiyeshenanpian	100 mg, pod, tid, 2 wk	Estazolam	5 mg, pod, qd, 2 wk	*,‡	CCMD-3	2
Bu YF 2014	30	15	15	30	16	14	50.57 ± 10.57	50.03 ± 10.50	SMC	1.2 g, pod, bid, 6 wk	Estazolam	1 mg, pod, qd, 6 wk	*,†,‡	CCMD-3	6
Chen YP 2017	30	/	/	30	/	/	/	/	SMC	1.2 g, pod, bid, 4 wk	Estazolam	1 mg, pod, qd, 4 wk	*,†,‡	CCDM-3	4
He EB 2020	30	23	20	30	21	22	55.12 ± 7.17	53.12 ± 8.92	SMC	1.2 g, pod, tid, 4 wk	Estazolam	1 mg, pod, qd, 4 wk	*,†,‡	CCMD-3	4
Lu AY 2008	58	/	/	57	/	/	18–65	18–65	SMC	1.2 g, pod, bid, 4 wk	Diazepatn	5 mg, pod, bid, 4 wk	*,†	CCDM-3	4
Luo ZY 2009	33	15	18	33	16	17	45 ± 20	46 ± 22	SMC	1.2 g, pod, bid, 1 wk	Alprazolam	0.4 mg, pod, qd, 4 wk	†,‡	CCDM-3	1
Song HX 2019	287	164	123	287	158	129	73.36 ± 10.82	72.94 ± 10.47	SMC	1.2 g, pod, bid, 4 wk	Zopiclone	3 mg, pod, qd, 4 wk	*,‡	CCMD-3	4
Sun AH 2015	50	20	30	50	20	30	44.39 ± 10.61	45.13 ± 11.03	SMC	1.2 g, pod, bid, 3 wk	Estazolam	1 mg, pod, qd, 3 wk	*,‡	CCMD-3	4
Xia LF 2015	49	23	27	47	20	27	52.9 ± 11.0	51.3 ± 14.6	SMC	1.2 g, pod, bid, 4 wk	Estazolam	1 mg, pod, qd, 4 wk	*,†,‡	CCDM-3	4
Meng B 2013	35	20	15	35	19	16	71.35 ± 7.58	72.06 ± 8.14	SMC	1.2 g, pod, bid, 4 wk	Alprazolam	0.4 mg, pod, qd, 4 wk	*	CCDM-3	4
Zheng C 2018	40	21	19	40	22	18	47.8 ± 15.4	48.2 ± 14.7	SMC	1.2 g, pod, bid, 4 wk	Estazolam	1 mg, pod, qd, 4 wk	*,†,‡	CCDM-3	4
Zhu X 2018	61	38	33	61	39	22	43.52 ± 5.26	43.96 ± 5.21	SMC	1.2 g, pod, bid, 4 wk	Estazolam	2 mg, pod, qd, 4 wk	*,†,‡	CCDM-3	4
Chen S 2022	8	/	/	11	/	/	/	/	SMC	1.2 g, pod, bid, 4 wk	Placebo	/	*,‡	DSM-5	4
Li L 2021	104	48	56	99	34	65	/	/	SMC	1.2 g, pod, bid, 4 wk	Placebo	/	*	CCDM-3	4
Bai YX 2022	41	/	/	41	/	/	37.24 ± 6.13	37.53 ± 6.22	Suanzaoren	/	Diazepatn	2.5 mg, pod, qd, 2 wk	*,†,‡	CCMD-3	2
Chen H 2014	50	29	21	50	27	23	72.46 ± 8.90	71.46 ± 8.03	Suanzaoren	/	Bailemian	1.08 g, pod, bid, 2 wk	*,‡	CCMD-3	2
Feng HP 2011	78	31	47	69	25	44	20–69	19–68	Suanzaoren	/	Estazolam	2 mg, pod, qd, 4 wk	*	CCMD-3	4
Fu GL 2019	48	25	23	48	24	24	45.1 ± 6.2	44.6 ± 7.9	Suanzaoren	/	Estazolam	2 mg, pod, qd, 12 wk	*,†	ICD-10	16
Gao SC 2013	70	19	51	70	22	48	63.07 ± 3.53	62.36 ± 4.16	Suanzaoren	/	Diazepatn	5 mg, pod, qd, 4 wk	*	ICD-10	4
Jiang XH 2012	40	20	20	40	20	20	/	/	Suanzaoren	/	Diazepatn	5 mg, pod, qd, 4 wk	*	CCMD-3	4
Li L 2005	35	18	16	35	21	14	37.6 ± 2.4	38.1 ± 2.2	Suanzaoren	/	Diazepatn	5 mg, pod, bid, 4 wk	*	CCMD-3	4
Li JF 2020	37	/	/	37	/	/	27–73	27–73	Suanzaoren	/	Estazolam	1 mg, pod, qd, 2 wk	*,†,‡	CCMD-3	2
Li LS 2013	76	34	42	68	30	38	19–58	18–57	Suanzaoren	/	Estazolam	2 mg, pod, qd, 2 wk	*	CCMD-3	2
Liu L 2019	44	23	21	44	22	22	56.06 ± 10.27	54.28 ± 11.37	Suanzaoren	/	Diazepatn	5 mg, pod, qd, 2 wk	*,†,‡	CCMD-3	2
Liu YB 2021	35	15	20	35	17	18	46.3 ± 2.3	46.0 ± 2.0	Suanzaoren	/	Estazolam	1 mg, pod, qd, 2 wk	†,‡	CCMD-3	2
Ma YF 2019	60	31	29	60	32	28	38.15 ± 4.87	37.44 ± 5.09	Suanzaoren	/	Estazolam	1 mg, pod, qd, 8 wk	*,†	CCMD-3	8
She YQ 2009	60	/	/	59	/	/	36.68 ± 8.53	35.32 ± 9.13	Suanzaoren	/	Estazolam	5 mg, pod, qd, 4 wk	*,†	CCMD-3	4
Tian HY 2019	66	35	31	66	30	36	50.13 ± 7.82	49.24 ± 7.01	Suanzaoren	/	Estazolam	2 mg, pod, qd, 4 wk	*,†	CCMD-3	4
Wang JB 2014	30	10	20	30	11	19	46.3 ± 7.4	44.1 ± 8.2	Suanzaoren	/	Estazolam	2 mg, pod, qd, 4 wk	*,‡	CCMD-3	6
Wang H 2013	30	14	16	30	15	15	/	/	Suanzaoren	/	Lorazepam	2 mg, pod, qd, 4 wk	*,‡	CCMD-3	4
Wang ZM 2021	25	15	10	25	14	11	48.2 ± 3.5	49.5 ± 3.6	Suanzaoren	/	Estazolam	1 mg, pod, qd, 4 wk	*,†	CCMD-3	2
Wu LM 2020	57	20	37	57	28	29	45.16 ± 5.79	45.81 ± 5.58	Suanzaoren	/	SMC	0.4 g, pod, qd, 4 wk	*,†	CCMD-3	4
Wu WF 2020	34	16	18	33	15	18	44.76 ± 10.41	45.03 ± 9.19	Suanzaoren	/	Estazolam	1 mg, pod, qd, 4 wk	†	ICSD-3	8
Xiao CJ 2020	60	/	/	60	/	/	40.63 ± 3.71	40.58 ± 3.62	Suanzaoren	/	Estazolam	1 mg, pod, tid, 4 wk	*,†	CCMD-3	4
Xu JS 2013	44	20	24	44	19	25	34.5 ± 7.4	32.9 ± 8.1	Suanzaoren	/	Alprazolam	0.4 mg, pod, tid, 2 wk	*,‡	CCMD-3	2
Zhang JF 2023	21	6	15	21	7	14	53.17 ± 4.25	52.85 ± 4.32	Suanzaoren	/	Diazepatn	5 mg, pod, qd, 2 wk	*,‡	CCMD-3	2
Zhang QQ 2018	40	19	21	40	18	22	43.33 ± 3.42	42.36 ± 3.57	Suanzaoren	/	Lorazepam	1 mg, pod, tid, 4 wk	*	CCMD-3	4
Zhang YX 2013	60	29	31	60	32	28	39.11 ± 5.29	40.94 ± 4.38	Suanzaoren	/	Estazolam	1 mg, pod, qd, 4 wk	*,†	CCMD-3	4
Zhou LX 2014	30	11	19	30	10	20	42.1 ± 3.4	42.8 ± 3.1	Suanzaoren	/	Oryzanol	20 mg, pod, tid, 4 wk	*,‡	CCMD-3	4
Zhou CB 2018	42	24	18	42	23	19	38.6 ± 3.1	38.7 ± 3.2	Suanzaoren	/	Estazolam	1 mg, pod, qd, 4 wk	*,†	CCMD-3	4
Chan YY 2015	45	/	/	45	/	/	/	/	Suanzaoren	/	Placebo	/	*,†	DSM-5	4
Hu LL 2015	60	/	/	59	/	/	/	/	Suanzaoren	/	Lorazepam	1 mg, pod, tid, 4 wk	†,‡	ICD-10	6
Scholey A 2017	82	/	/	78	/	/	/	/	Suanzaoren	/	Placebo	/	†,‡	ICSD-3	7
Zeng ZC 2013	50	30	20	50	28	22	41.7 ± 4.2	41.2 ± 3.8	Wuling capsule	0.99 g, pod, tid, 4 wk	Estazolam	5 mg, pod, qd, 4 wk	*,†	CCMD-3	4
Chen JX 2014	35	16	19	35	15	18	34.2 ± 9.46	36.8 ± 10.78	Wuling capsule	0.99 g, pod, tid, 4 wk	Estazolam	2 mg, pod, qd, 4 wk	*,†,‡	CCMD-3	4
Feng XD 2008	25	/	/	23	/	/	/	/	Wuling capsule	0.99 g, pod, tid, 8 wk	Estazolam	0.4 mg, pod, qd, 8 wk	*,†	CCMD-3	8
Huang XY 2011	50	21	29	50	19	31	44.58 ± 10.25	44.20 ± 7.83	Wuling capsule	0.99 g, pod, tid, 4 wk	Estazolam	5 mg, pod, qd, 4 wk	*,†	CCMD-3	4
Jin X 2012	24	/	/	24	/	/	/	/	Wuling capsule	0.99 g, pod, tid, 4 wk	Bailemian	1.08 g, pod, bid, 4 wk	*,†	DSM-5	4
Li YM 2006	36	20	16	20	11	9	77 ± 9	72 ± 7	Wuling capsule	0.99 g, pod, tid, 4 wk	Suanzaoren	0.4 g, pod, qd, 4 wk	*	DSM-5	4
Liu XY 2018	36	10	26	35	7	28	57.33 ± 9.76	59.45 ± 12.88	Wuling capsule	0.99 g, pod, tid, 4 wk	Estazolam	1 mg, pod, qd, 4 wk	*,†,‡	CCMD-3	4
Miu WP 2012	35	/	/	34	/	/	58–77	58–77	Wuling capsule	0.99 g, pod, tid, 4 wk	Oryzanol	10 mg, pod, qd, 4 wk	*	CCMD-3	4
Wang J 2021	49	30	19	49	27	22	50.48 ± 7.51	49.85 ± 7.90	Wuling capsule	0.99 g, pod, tid, 4 wk	Estazolam	1 mg, pod, qd, 4 wk	*,†	CCMD-3	4
Zhang WT 2011	31	17	14	31	16	15	25–58	23–57	Wuling capsule	0.99 g, pod, tid, 4 wk	Alprazolam	0.4 mg, pod, qd, 4 wk	*	CCMD-3	4
Zhu HF 2009	32	14	18	30	15	15	46.2 ± 6.5	45.1 ± 6.2	Wuling capsule	0.99 g, pod, tid, 4 wk	Estazolam	2 mg, pod, qd, 4 wk	*,†,‡	CCMD-3	4
Lin Y 2012	99	28	71	102	26	76	/	/	Wuling capsule	0.99 g, pod, tid, 4 wk	Placebo	/	†,‡	ICD-10	4
Feng JW 2021	34	14	20	34	15	19	45.11 ± 5.05	44.54 ± 5.28	ZRAS	2.25 g, pod, qd, 3 wk	Estazolam	2 mg, pod, qd, 3 wk	*,‡	CCMD-3	3
Fu JL 2019	43	23	20	43	22	21	53.28 ± 5.24	53.50 ± 5.18	ZRAS	4.5 g, pod, qd, 4 wk	CLMD	/	*	CCMD-3	4
Gan JG 2013	60	/	/	60	/	/	67.2 ± 5.0	66.5 ± 9.2	ZRAS	4.5 g, pod, qd, 4 wk	Alprazolam	0.8 mg, pod, qd, 4 wk	*,†,‡	CCMD-3	4
Huang Y 2013	45	21	24	45	22	23	18.3 ± 5.4	15.4 ± 6.3	ZRAS	2.25 g, pod, qd, 4 wk	Estazolam	1 mg, pod, qd, 4 wk	*,‡	CCMD-3	4
Li GR 2012	30	13	17	30	15	15	/	/	ZRAS	2.25 g, pod, qd, 2 wk	Estazolam	1 mg, pod, qd, 2 wk	*,†,‡	CCMD-3	2
Liang Y 2016	40	/	/	40	/	/	/	/	ZRAS	2.25 g, pod, qd, 4 wk	Estazolam	1 mg, pod, qd, 4 wk	*,†,‡	CCMD-3	4
Liu HY 2017	60	26	34	60	30	30	/	/	ZRAS	2.25 g, pod, qd, 2 wk	Estazolam	1 mg, pod, qd, 2 wk	*,†	CCMD-3	2
Liu Y 2009	30	12	18	30	13	17	36.9 ± 11.48	37.2 ± 11.36	ZRAS	2.25 g, pod, qd, 4 wk	Estazolam	1 mg, pod, qd, 4 wk	*,†	CCMD-3	4
				30	13	17	36.9 ± 11.48	37.8 ± 11.38	ZRAS	2.25 g, pod, qd, 4 wk	Placebo	/	*,†	CCMD-3	4
Liu Z 2021	52	30	22	52	29	23	48.29 ± 6.64	48.63 ± 7.42	ZRAS	4.5 g, pod, qd, 4 wk	Zopiclone	3 mg, pod, qd, 4 wk	†,‡	ICSD-3	4
Qin GX 2007	63	25	38	62	23	39	36.3	35.8	ZRAS	2.25 g, pod, qd, 2 wk	Clonazepam	1 mg, pod, qd, 2 wk	*,‡	CCMD-3	2
Sun HH 2019	55	24	31	55	28	27	49–73	48–70	ZRAS	2.25 g, pod, qd, 2 wk	Estazolam	1 mg, pod, qd, 2 wk	*,†	CCMD-3	2
Wang J 2017	64	39	25	64	38	26	42.6 ± 10.1	42.5 ± 11.3	ZRAS	2.25 g, pod, qd, 4 wk	Zopiclone	3 mg, pod, qd, 4 wk	*,†,‡	CCMD-3	4
Wang X 2017	41	20	21	41	19	22	/	/	ZRAS	2.25 g, pod, qd, 4 wk	Estazolam	1 mg, pod, qd, 4 wk	*,†,‡	CCMD-3	3
Wu SK 2020	120	48	72	120	45	75	51.07 ± 8.28	50.85 ± 8.96	ZRAS	2.25 g, pod, qd, 4 wk	Placebo	/	*,†,‡	DSM-5	4
Xu C 2011	75	35	40	75	33	42	/	/	ZRAS	2.25 g, pod, qd, 4 wk	Alprazolam	1 mg, pod, qd, 4 wk	*,†,‡	CCMD-3	4
Zhang J 2016	34	16	18	34	17	17	43.5 ± 5.7	43.4 ± 5.3	ZRAS	2.25 g, pod, qd, 3 wk	Estazolam	1 mg, pod, qd, 3 wk	*,‡	CCMD-3	3
Zhang SN 2018	30	9	21	30	4	26	46.17 ± 9.92	49.70 ± 12.22	ZRAS	2.25 g, pod, qd, 4 wk	Zopiclone	7.5 mg, pod, qd, 4 wk	*,†,‡	CCMD-3	4
				30	13	17	46.17 ± 9.92	46.77 ± 11.53	ZRAS	2.25 g, pod, qd, 4 wk	Placebo	/	*,†,‡	CCMD-3	4
Zhang YW 2019	41	21	20	41	22	19	43.5 ± 5.7	43.4 ± 5.6	ZRAS	2.25 g, pod, qd, 3 wk	Estazolam	1 mg, pod, qd, 3 wk	*,‡	CCMD-3	3
Birling Y 2022	38	/	/	47	/	/	/	/	ZRAS	2.25 g, pod, qd, 4 wk	Placebo	/	‡	DSM-5	4
Zhu X 2022	32	14	18	32	11	21	/	/	ZRAS	2.25 g, pod, qd, 4 wk	Zolpidem tartrate	10 mg, pod, qd, 4 wk	‡	DSM-5	4

bid = twice a day, BZYXW = baizi yangxin wan, CCMD-2-R = the Chinese Classification of Mental Disorders, Second Revised Edition, CCMD-3 = the updated version 3 Chinese Classification of Mental Disorders, CG = control group, CLMD = chaihu longgu muli decoction, CSP = chaihu shugan powder, DSM-5 = Diagnostic and Statistical Manual of Mental Disorders-5, HLWDD = Huanglian Wendan decoction, ICD-10 = International Statistical Classification of Diseases and Related Health Problems tenth edition, ICSD-3 = International Classification of Sleep Disorders, Third Edition, IG = intervention group, LXD = longdan xiegan decoction, po = oral administration, qd = once a day, SMC = shumian capsule, SST = shenqi schisandra tablet, tid = 3 times a day, TOL = tianmeng oral liquid, TWBX = tianwang buxin wan, ZRAS = zaoren anshen capsule

^*Clinical effectiveness rate.

^†PSQI.

^‡Adverse effects rate.

Table 2.

Main metabolite of botanical drug.

Botanical drug	Main metabolite
Bailemian	Ziziphus jujuba Mill. [Rhamnaceae; Ziziphi Spinosae Semen], Schisandra chinensis (Turcz.) Baill. [Schisandraceae; Schisandrae chinensis Fructus], Wolfiporia extensa (Peck) Ginns [Polyporaceae; Poria], Polygala tenuifolia Willd. [Polygalaceae; Polygalae Radix], Pinctada martensii (Dunker) [Pteriidae; Margarita]
SST	Panax ginseng C.A.Mey. [Araliaceae; Ginseng Radix et Rhizoma], Astragalus membranaceus (Fisch.) Bunge [Fabaceae; Astragali Radix], Schisandra chinensis (Turcz.) Baill. [Schisandraceae; Schisandrae chinensis Fructus]
CLMD	Bupleurum chinense DC. [Apiaceae; Bupleuri Radix], Scutellaria baicalensis Georgi [Lamiaceae; Scutellariae Radix], Pinellia ternata (Thunb.) Makino [Araceae; Pinelliae Rhizoma], Codonopsis pilosula (Franch.) Nannf. [Campanulaceae; Codonopsis Radix], Wolfiporia extensa (Peck) Ginns [Polyporaceae; Poria], Cinnamomum cassia (L.) J.Presl [Lauraceae; Cinnamomi Ramulus], Bos primigenius Bojanus [Os Draconis], Ostrea gigas Thunberg [Ostreidae; Ostreae Concha], Rheum palmatum L. [Polygonaceae; Rhei Radix et Rhizoma], Zingiber officinale Roscoe [Zingiberaceae; Zingiberis Rhizoma Recens], Ziziphus jujuba Mill. [Rhamnaceae; Jujubae Fructus], Glycyrrhiza uralensis Fisch. [Fabaceae; Glycyrrhizae Radix et Rhizoma Praeparata cum Melle]
CSP	Bupleurum chinense DC. [Apiaceae; Bupleuri Radix], Paeonia lactiflora Pall. [Paeoniaceae; Paeoniae Radix Alba], Citrus aurantium L. [Rutaceae; Aurantii Fructus], Glycyrrhiza uralensis Fisch. [Fabaceae; Glycyrrhizae Radix et Rhizoma], Ligusticum chuanxiong Hort. [Apiaceae; Chuanxiong Rhizoma], Cyperus rotundus L. [Cyperaceae; Cyperi Rhizoma], Citrus reticulata Blanco [Rutaceae; Citri Reticulatae Pericarpium]
Guipi decoction	Codonopsis pilosula (Franch.) Nannf. [Campanulaceae; Codonopsis Radix], Astragalus membranaceus (Fisch.) Bunge [Fabaceae; Astragali Radix], Atractylodes macrocephala Koidz. [Asteraceae; Atractylodis Macrocephalae Rhizoma], Wolfiporia extensa (Peck) Ginns [Polyporaceae; Poria], Glycyrrhiza uralensis Fisch. [Fabaceae; Glycyrrhizae Radix et Rhizoma Praeparata cum Melle], Angelica sinensis (Oliv.) Diels [Apiaceae; Angelicae Sinensis Radix], Dimocarpus longan Lour. [Sapindaceae; Longan Arillus], Ziziphus jujuba Mill. [Rhamnaceae; Ziziphi Spinosae Semen], Aucklandia lappa Decne. [Asteraceae; Aucklandiae Radix], Polygala tenuifolia Willd. [Polygalaceae; Polygalae Radix], Ziziphus jujuba Mill. [Rhamnaceae; Jujubae Fructus]
HLWDD	Coptis chinensis Franch. [Ranunculaceae; Coptidis Rhizoma], Pinellia ternata (Thunb.) Makino [Araceae; Pinelliae Rhizoma], Phyllostachys nigra (Lodd. ex Lindl.) Munro [Poaceae; Bambusae Caulis in Taenium], Citrus aurantium L. [Rutaceae; Aurantii Fructus Immaturus], Wolfiporia extensa (Peck) Ginns [Polyporaceae; Poria], Glycyrrhiza uralensis Fisch. [Fabaceae; Glycyrrhizae Radix et Rhizoma], Citrus reticulata Blanco [Rutaceae; Citri Reticulatae Pericarpium], Zingiber officinale Roscoe [Zingiberaceae; Zingiberis Rhizoma Recens]
Jieyu pill	Bupleurum chinense DC. [Apiaceae; Bupleuri Radix], Cyperus rotundus L. [Cyperaceae; Cyperi Rhizoma], Ligusticum chuanxiong Hort. [Apiaceae; Chuanxiong Rhizoma], Paeonia lactiflora Pall. [Paeoniaceae; Paeoniae Radix Alba], Angelica sinensis (Oliv.) Diels [Apiaceae; Angelicae Sinensis Radix], Glycyrrhiza uralensis Fisch. [Fabaceae; Glycyrrhizae Radix et Rhizoma Praeparata cum Melle]
LXD	Gentiana scabra Bunge [Gentianaceae; Gentianae Radix et Rhizoma], Scutellaria baicalensis Georgi [Lamiaceae; Scutellariae Radix], Gardenia jasminoides J.Ellis [Rubiaceae; Gardeniae Fructus], Alisma plantago-aquatica L. [Alismataceae; Alismatis Rhizoma], Akebia quinata (Houtt.) Decne. [Lardizabalaceae; Akebiae Caulis], Plantago asiatica L. [Plantaginaceae; Plantaginis Semen], Angelica sinensis (Oliv.) Diels [Apiaceae; Angelicae Sinensis Radix], Rehmannia glutinosa (Gaertn.) DC. [Orobanchaceae; Rehmanniae Radix], Bupleurum chinense DC. [Apiaceae; Bupleuri Radix], Glycyrrhiza uralensis Fisch. [Fabaceae; Glycyrrhizae Radix et Rhizoma]
Qiyeshenanpian	Panax notoginseng (Burkill) F.H.Chen [Araliaceae; Notoginseng Radix et Rhizoma], Gastrodia elata Blume [Orchidaceae; Gastrodiae Rhizoma], Uncaria rhynchophylla (Miq.) Miq. ex Havil. [Rubiaceae; Uncariae Ramulus Cum Uncis], Pinctada martensii (Dunker) [Pteriidae; Margarita], Glycyrrhiza uralensis Fisch. [Fabaceae; Glycyrrhizae Radix et Rhizoma]
SMC	Ziziphus jujuba Mill. [Rhamnaceae; Ziziphi Spinosae Semen], Platycladus orientalis (L.) Franco [Cupressaceae; Platycladi Semen], Polygala tenuifolia Willd. [Polygalaceae; Polygalae Radix], Albizia julibrissin Durazz. [Fabaceae; Albiziae Cortex], Bos primigenius Bojanus [Os Draconis]
Suanzaoren	Ziziphus jujuba Mill. var. spinosa (Bunge) Hu ex H.F.Chow [Rhamnaceae; Ziziphi Spinosae Semen]
Wuling capsule	Schisandra chinensis (Turcz.) Baill. [Schisandraceae; Schisandrae chinensis Fructus], Wolfiporia extensa (Peck) Ginns [Polyporaceae; Poria], Acorus tatarinowii Schott [Acoraceae; Acori Tatarinowii Rhizoma], Polygala tenuifolia Willd. [Polygalaceae; Polygalae Radix], Mercuric sulfide (HgS) [Cinnabaris]
ZRAS	Ziziphus jujuba Mill. [Rhamnaceae; Ziziphi Spinosae Semen], Lilium brownii F.E.Br. [Liliaceae; Lilii Bulbus], Wolfiporia extensa (Peck) Ginns [Polyporaceae; Poria], Anemarrhena asphodeloides Bunge [Asparagaceae; Anemarrhenae Rhizoma], Scrophularia ningpoensis Hemsl. [Scrophulariaceae; Scrophulariae Radix]
TWBX	Rehmannia glutinosa (Gaertn.) DC. [Scrophulariaceae; Rehmanniae Radix], Angelica sinensis (Oliv.) Diels [Apiaceae; Angelicae Sinensis Radix], Glycyrrhiza uralensis Fisch. [Fabaceae; Glycyrrhizae Radix et Rhizoma], Ophiopogon japonicus (Thunb.) Ker Gawl. [Asparagaceae; Ophiopogonis Radix], Cornus officinalis Siebold & Zucc. [Cornaceae; Corni Fructus], Paeonia lactiflora Pall. [Paeoniaceae; Paeoniae Radix Alba], Polygala tenuifolia Willd. [Polygalaceae; Polygalae Radix], Ziziphus jujuba Mill. [Rhamnaceae; Jujubae Fructus], Schisandra chinensis (Turcz.) Baill. [Schisandraceae; Schisandrae Chinensis Fructus], Selenium (Se) [Selenium]
BZYXW	Panax ginseng C.A. Meyer [Araliaceae; Ginseng Radix et Rhizoma], Polygala tenuifolia Willd. [Polygalaceae; Polygalae Radix], Adenophora stricta (Maxim.) Hara [Campanulaceae; Adenophorae Radix], Schisandra chinensis (Turcz.) Baill. [Schisandraceae; Schisandrae Chinensis Fructus], Glycyrrhiza uralensis Fisch. [Fabaceae; Glycyrrhizae Radix et Rhizoma], Coptis chinensis Franch. [Ranunculaceae; Coptidis Rhizoma], Rehmannia glutinosa (Gaertn.) DC. [Scrophulariaceae; Rehmanniae Radix], Ziziphus jujuba Mill. [Rhamnaceae; Jujubae Fructus], Ophiopogon japonicus (Thunb.) Ker Gawl. [Asparagaceae; Ophiopogonis Radix], Paeonia lactiflora Pall. [Paeoniaceae; Paeoniae Radix Alba]
TOL	Morinda officinalis How. [Rubiaceae; Morindae Officinalis Radix], Cistanche deserticola Ma. [Orobanchaceae; Cistanche Deserticolae Stipitis], Epimedium sagittatum (Siebold & Zucc.) Maxim. [Berberidaceae; Epimedii Herba], Schisandra chinensis (Turcz.) Baill. [Schisandraceae; Schisandrae Chinensis Fructus], Glycyrrhiza uralensis Fisch. [Fabaceae; Glycyrrhizae Radix et Rhizoma], Paeonia lactiflora Pall. [Paeoniaceae; Paeoniae Radix Alba], Polygonum multiflorum Thunb. [Polygonaceae; Polygoni Multiflori Radix]

BZYXW = baizi yangxin wan, CLMD = chaihu longgu muli decoction, CSP = chaihu shugan powder, HLWDD = Huanglian Wendan decoction, LXD = longdan xiegan decoction, SMC = shumian capsule, SST = shenqi schisandra Tablet, TOL = tianmeng oral liquid, TWBX = tianwangbuxinwan, ZRAS = zaoren anshen capsule.

3.3. Risk-of-bias assessment

All included trials were assessed for risk of bias by Risk of Bias 2.0 Tool in this review. There were some general concerns or high concerns for the risk of bias for the randomization process and selection of the reported result due to the lack of information regarding the allocation concealment. Overall, 127 trials (68.3%) were rated as low risk, 44 trials (23.7%) were rated as moderate risk, and the remaining 15 trials (8.0%) were rated as high risk. Overall, the included studies exhibited a low-to-moderate risk of bias (Fig. 2).

Figure 2.

Bias risk assessment results for insomnia. (A) Risk of bias graph for insomnia; (B) risk of bias summary for insomnia.

3.4. Publication bias

An analysis was conducted to compare the model fit between fixed-effects and random-effects models for each outcome measure, as illustrated in Figure 3. Additionally, the level of inconsistency within these models was assessed by comparing the posterior distribution of deviance differences between the fit–UME model and the consistency model. This method aimed to ascertain the consistency of results derived from the included studies, as demonstrated in Figure 4. Our findings indicated a superior fit of the random-effects model across each outcome measure. Furthermore, the results from the included studies were found to be consistent, bolstering the validity of indirect comparisons. To evaluate publication bias within the included studies, funnel plots were used. The sample size was large, and the results were concentrated in a narrow range at the top of the funnel plot. These plots, presented in Figure 5, demonstrate symmetrical distribution, suggesting limited evidence of publication bias.

Figure 3.

Lever diagram for insomnia. The lever diagram shows the comparison between leverage_ik and Bayesian deviation residuals of all I tests and each of the K arms.

Figure 4.

The conformance test for insomnia evaluates the consistency among included studies by comparing the posterior mean deviations of each data group between the consistency model and the UME model. Bias risk evaluation results are also presented to support the assessment .

Figure 5.

Funnel plots. The funnel plot assesses publication bias in the meta-analysis.

3.5. Network diagram

A network diagram in NMA visually represents the evidence structure of a research analysis. Each treatment is represented as a node. The nodes are connected by lines or edges, with each line indicating a direct comparison made between the treatments in the included studies. The size of each node is proportional to the total number of participants receiving each treatment. The thickness of the lines can indicate the number of studies comparing those treatments (direct comparisons). The available comparisons of PSQI score, clinical effectiveness rate, and the incidence of adverse reactions are displayed in the network diagram. A closed loop in a network diagram represents the presence of both direct and indirect comparisons among the interventions. Direct comparisons are those where treatments have been directly compared against each other in studies, while indirect comparisons are derived from a common comparator. Notably, estazolam, ZRAS, suanzaoren were the most extensively studied insomnia treatments. The most frequently compared pairs were estazolam versus suanzaoren, estazolam versus CLMD, and estazolam versus ZRAS (Fig. 6).

Figure 6.

Network diagram of eligible comparisons. (A) PSQI scores; (B) the effective rate; (C) adverse effects rate. BZYXW = baizi yangxin wan, CLMD = chaihu longgu muli decoction, CSP = chaihu shugan powder, HLWDD = Huanglian Wendan decoction, LXD = longdan xiegan decoction, PSQI = Pittsburgh Sleep Quality Index, SMC = shumian capsule, SST = shenqi schisandra tablet, TOL = tianmeng oral liquid, TWBX = tianwang buxin wan, ZRAS = zaoren anshen capsule.

3.6. Forest map

In NMA, the forest map serves as a crucial tool to visually summarize the outcomes of pairwise comparisons between diverse treatments. The nma.forest() function is adept at generating forest plots, which are instrumental in facilitating the comparison of aggregated results from various drugs at varying efficacy and safety levels.

In the assessment of PSQI scores, SST groups demonstrated superior efficacy relative to alprazolam. Patients treated with oryzanol experienced less effective outcomes in PSQI scores when contrasted with CLMD. In the realm of anti-insomnia effects, CLMD, guipi decoction, suanzaoren, and wuling capsule were more efficacious than estazolam according to PSQI scores. Lorazepam was found to be less effective in improving PSQI scores compared to suanzaoren (Fig. 7A). Regarding the effective rate, groups treated with bailemian, CLMD, CSP, guipi decoction, HLWDD, LXD, qiyeshenanpian, SST, suanzaoren, wuling capsule, and ZRAS demonstrated superior outcomes compared to estazolam. diazepam and tianwang buxin wan (TWBX) exhibited a reduced effective rate relative to bailemian. oryzanol and zolpidem tartrate were less effective compared to CLMD, while alprazolam and lorazepam showed lower efficacy against guipi decoction. Zopiclone’s effective rate was inferior to that of CSP (Fig. 7B). From the perspective of safety, triazolam presented a markedly increased risk of adverse effects compared to bailemian. Conversely, jieyu pill was associated with a significantly reduced risk of adverse effects than estazolam. SST was noted for an increased safety risk of adverse effects when compared to estazolam (Fig. 7C).

Figure 7.

Forest plot of the network meta-analysis of all trials for efficacy and adverse effects in patients with insomnia. (A) direct comparison for PSQI scores; (B) direct comparison for the effective rate; (C) direct comparison for adverse effects rate. BZYXW = baizi yangxin wan, CLMD = chaihu longgu muli decoction, CSP = chaihu shugan powder, HLWDD = Huanglian Wendan decoction, LXD = longdan xiegan decoction, PSQI = Pittsburgh Sleep Quality Index, SMC = shumian capsule, SST = shenqi schisandra tablet, TOL = tianmeng oral liquid, TWBX = tianwang buxin wan, ZRAS = zaoren anshen capsule.

3.7. The heatmap of the ranking table

In NMA, the heatmap of the ranking table serves as an indispensable visualization tool. It graphically delineates the hierarchy of treatment efficacies or safety profiles, displaying treatments along one axis and their respective ranking criteria along another. The heatmap, generated by the nma.league() function, offers a comprehensive estimation of relative effects, facilitating comparisons between any pair of interventions. This heatmap, as depicted in Figure 8 vividly elucidates the ranking of each outcome index. It encompasses both the OR and the 95% CI for each outcome index across all intervention groups.

Figure 8.

Ranking chart heat map for insomnia. This heat map displays comparative analyses of the relative effects between various interventions, encompassing the odds ratio and 95% confidence intervals for each outcome index across all groups, * represents P < .05. (A) PSQI scores ranking chart heat map; (B) the effective rate ranking chart heat map; (C) adverse effects rate ranking chart heat map. BZYXW = baizi yangxin wan, CLMD = chaihu longgu muli decoction, CSP = chaihu shugan powder, HLWDD = Huanglian Wendan decoction, LXD = longdan xiegan decoction, PSQI = Pittsburgh Sleep Quality Index, SMC = shumian capsule, SST = shenqi schisandra tablet, TOL = tianmeng oral liquid, TWBX = tianwang buxin wan, ZRAS = zaoren anshen capsule.

In terms of PSQI scores, guipi decoction outperformed HLWDD, ZRAS, diazepam, bailemian, SMC, estazolam, tianmeng oral liquid, alprazolam, LXD, placebo, zopiclone, oryzanol, triazolam, lorazepam and CSP, showing more favorable point estimates. Statistically, CLMD and suanzaoren outshone ZRAS, SMC, estazolam, alprazolam, placebo, zopiclone, oryzanol, lorazepam, and CSP in PSQI score evaluations. Wuling capsule achieved superior statistical outcomes compared to bailemian, SMC, estazolam, placebo, zopiclone, lorazepam, and CSP for PSQI scores (Fig. 8A). In terms of the effective rate, LXD demonstrated significantly enhanced effectiveness over qiyeshenanpian, SST, jieyu pill, alprazolam, ZRAS, SMC, TWBX, diazepam, estazolam, triazolam, lorazepam, zopiclone, oryzanol, and placebo, confirming its efficacy as an active drug. CLMD showcased greater efficacy than qiyeshenanpian, SST, zolpidem tartrate, alprazolam, ZRAS, SMC, TWBX, diazepam, estazolam, triazolam, lorazepam, zopiclone, oryzanol, and placebo. Guipi decoction, HLWDD, wuling capsule, and suanzaoren were more effective than alprazolam, ZARS, SMC, TWBX, diazepam, estazolam, lorazepam, zopiclone, oryzanol, and placebo. CSP and bailemian’s efficacy markedly surpassed that of ZRAS, SMC, TWBX, diazepam, estazolam, lorazepam, zopiclone, oryzanol, and placebo (Fig. 8B). Regarding safety, jieyu pill was associated with fewer adverse effects compared to trazodone, CLMD, placebo, HLWDD, CSP, suanzaoren, ZRAS, bailemian, qiyeshenanpian, SMC, guipi decoction, zolpidem tartrate, wuling capsule, lorazepam, TWBX, zopiclone, estazolam, alprazolam, oryzanol, clonazepam, diazepam, oxazepam, SST, and triazolam. Trazodone exhibited lower adverse effect risks than bailemian, qiyeshenanpian, SMC, guipi decoction, zolpidem tartrate, wuling capsule, lorazepam, TWBX, zopiclone, estazolam, alprazolam, oryzanol, clonazepam, diazepam, oxazepam, SST, and triazolam. CLMD demonstrated fewer adverse effects than SMC, guipi decoction, wuling capsule, zopiclone, estazolam, alprazolam, oryzanol, clonazepam, diazepam, oxazepam, SST, and triazolam (Fig. 8C).

3.8. SUCRA rankings

SUCRA rankings are a statistical tool used to provide a ranking of treatments based on their effectiveness and safety. SUCRA is derived from the cumulative probability of each treatment being ranked at different positions for a particular outcome. It summarizes the area under the curve of the cumulative ranking probabilities. SUCRA values are expressed as percentages and give a numerical representation of the likelihood of a treatment being among the best options. The higher the SUCRA value, the better the treatment ranks on the efficacy and safety in comparison to others in the network.

For PSQI scores, the top 5 treatments were guipi decoction, SST, CLMD, suanzaoren, and wuling capsule. Notably, the highest rankings for effective rate were achieved by LXD, CLMD, guipi decoction, HLWDD, and CSP. In terms of safety, jieyu pill, trazodone, and CLMD were the top 3, indicating superior safety profiles among all treatments. Conversely, triazolam exhibited the poorest safety, ranking lowest in terms of adverse effects. SST, while being second in improving PSQI scores, unfortunately displayed suboptimal drug safety. Positively, CLMD was recognized for its efficacy and minimal safety risk. Guipi decoction also displayed commendable efficacy, albeit with a moderate safety risk. Crucially, in this study, both the PSQI scores and the effective rate, alongside the safety profile of most Chinese herbal medicines, were generally superior to conventional pharmaceutical treatments (Fig. 9, Table 3).

Figure 9.

Ranking probability histogram and cumulative probability ranking chart for insomnia. The histogram and SUCRA charts intuitively display the sorting probability of each group in the form of histogram and curves. (A) The histogram chart of PSQI scores; (B) SUCRA chart of PSQI scores; (C) the histogram chart of the effective rate; (D) SUCRA chart of the effective rate; (E) the histogram chart of adverse effects rate; (F) SUCRA chart of adverse effects rate. BZYXW = baizi yangxin wan, CLMD = chaihu longgu muli decoction, CSP = chaihu shugan powder, HLWDD = Huanglian Wendan decoction, LXD = longdan xiegan decoction, PSQI = Pittsburgh Sleep Quality Index, SMC = shumian capsule, SST = shenqi schisandra tablet, SUCRA = surface under the cumulative ranking, TOL = tianmeng oral liquid, TWBX = tianwang buxin wan, ZRAS = zaoren anshen capsule.

Table 3.

SUCRA rankings.

Efficacy				Safety
PSQI	SUCRA	Effective rate	SUCRA	Adverse effects rate	SUCRA
Guipi decoction	94.94	LXD	93.88	Jieyu pill	99.00
SST	85.54	CLMD	90.93	Trazodone	93.58
CLMD	85.32	Guipi decoction	83.87	CLMD	82.56
Suanzaoren	84.26	HLWDD	82.20	Placebo	81.03
Wuling_capsule	82.42	CSP	76.79	HLWDD	78.29
Jieyu pill	74.60	Wuling capsule	76.44	CSP	74.92
Qiyeshenanpian	61.69	Suanzaoren	74.21	Suanzaoren	73.41
HLWDD	57.00	Bailemian	70.60	ZRAS	73.36
ZRAS	52.86	Trazodone	64.91	Bailemian	62.10
Diazepatn	51.39	TOL	61.37	Qiyeshenanpian	59.95
Zolpidem tartrate	50.25	Qiyeshenanpian	58.12	SMC	53.98
Bailemian	50.15	SST	54.91	Guipi decoction	52.22
SMC	49.14	Anshenbunao syrup	53.24	Zolpidem tartrate	51.26
Oxazepam	46.63	Jieyu pill	53.07	Wuling capsule	49.71
Estazolam	45.88	BZYXW	49.90	Lorazepam	46.43
TOL	44.77	Zolpidem tartrate	48.18	BZYXW	45.94
BZYXW	40.53	Alprazolam	43.35	TWBX	41.00
Alprazolam	38.96	Clonazepam	43.16	Zopiclone	39.50
LXD	35.45	ZRAS	38.97	Estazolam	25.42
TWBX	34.66	SMC	32.96	Alprazolam	24.76
Placebo	30.99	TWBX	27.15	Oryzanol	23.21
Zopiclone	27.20	Diazepatn	26.73	Clonazepam	22.51
Oryzanol	24.17	Estazolam	21.85	Diazepatn	19.51
Triazolam	20.76	Triazolam	21.67	Oxazepam	19.06
Lorazepam	19.01	Lorazepam	20.77	SST	5.06
CSP	11.48	Zopiclone	14.84	Triazolam	2.23
		Oryzanol	13.23
		Placebo	2.68

BZYXW = baizi yangxin wan, CLMD = chaihu longgu muli decoction, CSP = chaihu shugan powder, HLWDD = Huanglian Wendan decoction, LXD = longdan xiegan decoction, PSQI = Pittsburgh Sleep Quality Index, SMC = shumian capsule, SST = shenqi schisandra tablet, SUCRA = surface under the cumulative ranking, TOL = tianmeng oral liquid, TWBX = tianwang buxin wan, ZRAS = zaoren anshen capsule.

4. Discussion

To our knowledge, this is the first time that multiple botanical drugs used for the treatment of insomnia have been compared in a Bayesian NMA. We performed a comprehensive search for insomnia, addressed crucial outcomes, and assessed risk of bias from an evidentiary level. The PSQI score, clinical effectiveness rate, or rate of adverse events on versus direct and indirect comparisons, thereby enhancing the persuasiveness of the evidence.

4.1. Principal findings

This network systematic review and meta-analysis represent a comprehensive evaluation of the therapeutic efficacy and safety of herbal medicines in the management of insomnia, distinguishing itself as a pivotal contribution to sleep medicine research. Our findings elucidate the potential of specific herbal medicines, notably guipi decoction, CLMD and suanzaoren, as effective and safer alternatives to conventional pharmacological treatments for insomnia. Crucially, in this study, both the PSQI scores and the effective rate, alongside the safety profile of most Chinese herbal medicines, were generally superior to conventional pharmaceutical treatments.

The superior efficacy of these herbal interventions in improving sleep quality, as quantified by the PSQI scores and the effective rate, aligns with historical usage and pharmacological studies indicating their sedative and sleep-modulating properties. The diminished incidence of adverse effects associated with these herbal treatments underscores their safety profile, making them a compelling choice for long-term management of insomnia, particularly in patients who are intolerant or unresponsive to standard pharmacological therapies.

4.2. Mechanisms of herbal medicines

The mechanism of insomnia is generally caused by disturbance in multiple pathways, such as gamma-aminobutyric acid (GABA) receptor, cortisol level, cytokines, melatonin secretion, adenosine receptors and excitatory amino acid.^[232,233] The underlying mechanisms by herbal medicines in the treatment of insomnia remain largely unexplored.

Suan zao ren (Semen Ziziphi Spinosae), one of the most renowned remedies for insomnia, is frequently prescribed for sleep disorders and is extensively utilized in Asian countries, such as Japan, Korea, China.^[234] It has been observed that suan zao ren enhances sleep quality, extends sleep duration, and increases slow wave sleep. Its mechanism is thought to involve the stimulation of GABA and serotonin receptors.^[235]

ZRAS comprises 3 principal metabolites from traditional Chinese medicine: semen ziziphi spinosae, salvia miltiorrhiza, and schisandra chinensis. These metabolites collectively offer a wide range of pharmacological effects, characterized by their multi-targeted nature and synergistic action in treating insomnia. Their therapeutic effects are likely associated with the modulation of neurotransmitters such as serotonin, GABA, and glutamic acid.^[236,237]

Pharmacological research indicates that wuling mycelium, the main metabolite of wuling capsule, enhances brain tissue permeability to the excitatory neurotransmitter glutamate and vitamin B6. This elevation in permeability facilitates an increase in glutamate decarboxylase activity, increases GABA synthesis, and amplifies the activity of GABA receptors. Consequently, this leads to pronounced sedative and sleep-inducing effects.^[26]

Generally, the primary physiological mechanism of CLMD involves modulating the hypothalamic-pituitary-adrenal axis and the brain’s monoamine neurotransmitter (norepinephrine, dopamine, and 5-hydroxytryptamine) levels. In addition, CLMD potentially treats insomnia by suppressing the activation of the mitogen-activated protein kinase kinase/extracellular signal-regulated kinase pathway.^[21]

Jujube seed, white peony root, and silkworm found in shumian capsule are abundant in tryptophan, the precursor to 5-hydroxytryptamine. Thus, consuming shumian capsule can help replenish serotonin deficiencies. Bupleurum in shuman capsules is known to modulate the activities of the sympathetic and parasympathetic nerves, enhancing norepinephrine levels. This aids in regulating slow wave and rapid eye movement sleep. The combination of these 2 functions contributes to the improvement of sleep quality and the restoration of independent sleep, ultimately leading to effective treatment of insomnia.^[24,143,238]

4.3. Strengths

Previous systematic reviews on herbal medicine for insomnia typically consolidated various herbal treatments into a single category, contrasting them against conventional biomedicine or placebos for analytical simplicity. This approach tends to obscure the nuanced differences between the therapeutic agents, inadequately evaluating and contrasting the specific efficacy and safety of each herb or herbal formulation. Consequently, this generalization may overlook the distinct therapeutic potentials and advantages inherent in individual herbal remedies.

This NMA is, an advanced technique, allows for the comparison of multiple neuroprotective interventions simultaneously, even when some of them have not been directly compared in head-to-head trials. In the heatmap of the ranking table, the hierarchy of treatment efficacies or safety profiles is displayed by displaying treatments. SUCRA rankings give a numerical representation of the likelihood of a treatment being among the best options. This provides a more comprehensive overview of available treatments. NMA incorporates both direct and indirect comparisons, increasing the statistical power and the ability to draw conclusions where direct comparison data is limited. NMA can rank interventions based on their effectiveness, providing valuable insights for clinicians and policymakers on the most effective interventions.

Our research provides an exhaustive systematic review and NMA of herbal medicines in treating insomnia, offering a robust evaluation of their efficacy and safety compared to conventional treatments. Our study’s strength lies in its methodological rigor, characterized by the comprehensive aggregation of direct and indirect evidence through Bayesian NMA. This approach not only enhances the reliability of the treatment comparisons but also expands the evidence base by integrating a wide array of herbal medicines, thereby offering a granular insight into their relative therapeutic merits and safety. Our findings have significant clinical implications, suggesting a paradigm shift towards integrating herbal medicines in insomnia management, which could benefit patients seeking effective and safer treatment alternatives. By furnishing evidence-based insights into the comparative effectiveness of herbal medicines, our study aids in broadening the therapeutic landscape for insomnia.

4.4. Limitations

However, it is imperative to acknowledge the limitations inherent in this research. Firstly, the existing evidence in this study predominantly relies on the PSQI score and clinical effectiveness rate as measures of efficacy. However, data from other insomnia scales, such as the Clinician Global Impression-Severity Scale, Traditional Chinese medicine symptom therapeutic Scale, Insomnia Severity Index, and Athens Insomnia Scale, were not included due to insufficient numbers of clinical trials. These findings could yield more comprehensive conclusions about the impact of herbal medicines on insomnia. Secondly, the PSQI score is a self-assessment tool and may lack objectivity compared to physiological indices. Individual interpretations of these scales can vary, potentially leading to biases in symptom reporting, thereby compromising the accuracy of the results.^[239] Thirdly, insomnia is often a chronic condition requiring long-term management, yet these studies did not include long-term follow-up to assess the sustained effectiveness of botanical drugs. A more realistic long-term scenario would involve the continuous use of botanical drugs over months or years in the future. Fourthly, this review merged data from small studies which may have resulted in inadequate statistical power for each study, increasing the risk of imprecision and limiting the reliability of the current evidence for the clinical application of botanical drugs. Finally, the heterogeneity in the methodological quality of the included trials, varying dosages of herbal preparations, and the predominance of studies conducted within specific geographical regions may influence the generalizability of the findings.

4.5. Implications

We have identified an emerging domain in insomnia treatment that merits further exploration. Regarding future research, firstly, the assessment of outcomes measures should not be limited to subjective scales alone but should also include objectively validated measures, like polysomnography. Secondly, given that insomnia disorder can fluctuate over a prolonged course, regardless of treatment, continuous follow-up is essential to ascertain the genuine efficacy and long-term impact of the botanical drugs. Thirdly, we identified key issues in current research that require enhancement in future studies, notably the low quality of study designs and the omission of adverse event reporting. We recommend that the design of RCTs should be strictly conducted according to the Consolidated Standards of Reporting Trials (CONSORT) 2010 statement guidelines,^[240] to guarantee the scientific integrity and rigor of the studies.

5. Conclusion

In conclusion, this NMA first time offers a comprehensive and integrated evaluation and summary of the findings using Chinese herbal medicines for treatment of insomnia, advocating for their judicious integration into clinical practice. These findings advocate for integrating herbal treatments into insomnia management protocols, emphasizing the need for rigorous long-term studies to confirm these preliminary outcomes.

Acknowledgments

The biostatistician, YX, from the Chinese Evidence-Based Medicine Center at West China Hospital, Sichuan University, contributed to the data analysis and reviewed the manuscript during the review process.

Author contributions

Formal analysis: Chun Dang.

Software: Qinxuan Wang.

Writing – original draft: Weiwei Li, Yaoheng Lu.

Writing – review & editing: Ying Xiong.