Efficacy and safety of selected Chinese herbal medicine preparations in treating carotid atherosclerosis: a systematic review and meta-analyses

Abstract

Background:

Although conventional therapies for Carotid atherosclerosis (CAS) remain the standard treatment, their effectiveness is often limited and accompanied by adverse effects. Chinese herbal medicine (CHM) is a promising adjunctive therapy for CAS; however, robust clinical evidence supporting its efficacy and safety remains limited.

Objective:

This systematic review and meta-analysis evaluates the efficacy and safety of CHM for CAS treatment and characterizes its medication patterns.

Methods:

Five databases were searched from inception to December 2025. Randomized controlled trials (RCTs) evaluating oral CHM for CAS were included. Study quality was assessed using the Cochrane Risk of Bias 2 (RoB 2) tool. Data were extracted and analyzed using RevMan v5.3 and R software. Sources of heterogeneity were investigated through meta-regression and subgroup analyses. Network analysis reveals herbal medication patterns across 21 studies.

Results:

Twenty-one RCTs involving 3,078 patients were included. Compared with conventional therapy alone, adjunctive CHM significantly reduced carotid plaque area (MD = 4.94, 95% CI: 3.13 to 6.76, p < 0.01), intima-media thickness (IMT) (MD = 0.12, 95% CI: 0.07 to 0.17, p < 0.05), total cholesterol (TC) (MD = 0.32, 95% CI: 0.22 to 0.42, p < 0.01), triglycerides (TG) (MD = 0.24, 95% CI: 0.11 to 0.37, p < 0.01), and low-density lipoprotein cholesterol (LDL-C) (MD = 0.37, 95% CI: 0.21 to 0.53, p < 0.01), while greatly increasing high-density lipoprotein cholesterol (HDL-C) (MD = −0.20, 95% CI: −0.29 to −0.10, p < 0.01). CHM did not significantly increase the risk of adverse events (RR = 0.84, 95% CI: 0.64 to 1.10, p = 0.20) or impair liver/kidney function. Network analysis identified core actions as clearing phlegm and removing blood stasis, with Danshen (Salvia miltiorrhiza Bge.) and Banxia [Pinellia ternata (Thunb.) Breit.] as pivotal botanical drugs exerting anti-stasis and lipid-regulating effects.

Conclusion:

As an adjunct to conventional therapy, CHM may further reduce carotid IMT and plaque burden, improve lipid metabolism, and demonstrate a favorable safety profile. However, the overall quality and heterogeneity of the included studies limit the strength of the evidence, highlighting the need for well-designed, high-quality RCTs to confirm these findings.

Systematic Review Registration:

https://www.crd.york.ac.uk/PROSPERO/view/CRD420261285381, identifier CRD420261285381.

1 Introduction

Carotid atherosclerosis (CAS) is a major contributor to ischemic stroke and cardiovascular disease (Fu et al., 2024; Parish et al., 2019; Hald et al., 2014; Li et al., 2022a). It most commonly develops at the carotid bifurcation and within the distal common carotid and proximal internal carotid arteries. The pathogenesis of CAS is closely linked to lipid metabolism abnormalities and changes in local hemodynamic forces (Zhang et al., 2022; Li et al., 2021; Motomiya and Karino, 1984). Increased intima-media thickness (IMT), carotid plaque formation, and varying degrees of carotid artery stenosis are recognized as key indicators of disease progression (Nai et al., 2025; Guo et al., 2025; Almevall et al., 2025). Epidemiological studies estimate that the global prevalence of CAS among adults reaches approximately 50.25% (Song et al., 2020), with similarly high prevalence reported in China (Fu et al., 2024). Current conventional management of CAS primarily focuses on lipid-lowering and antiplatelet therapies, both of which have demonstrated clinical benefit (Gresele et al., 2020; Hu et al., 2022a). Statins remain first-line agents for lipid reduction (Jia et al., 2021; Kadoglou et al., 2022; Huang et al., 2025); however, they may cause adverse effects, including myalgia and, in rare cases, rhabdomyolysis (Adhyaru et al., 2018; Thompson et al., 2016; Sizar et al., 2024). Antiplatelet therapy, particularly aspirin, is widely used for cardiovascular prevention, but its benefit in asymptomatic CAS remains limited, and prolonged treatment is associated with an increased risk of bleeding (Gresele et al., 2020; Hu et al., 2022a).

Chinese herbal medicine (CHM) uses a multi-component, multi-target, multi-pathway therapeutic strategy. Growing evidence suggests that CHM may improve lipid metabolism by reducing low-density lipoprotein cholesterol (LDL-C), triglycerides (TG), and total cholesterol (TC) (Jiang et al., 2025; Ma and Zhang, 2025; Yuan et al., 2025). Clinical studies have also reported favorable effects of herbal therapies on lipid profiles, clinical symptoms, and laboratory indicators in patients with CAS (Chang et al., 2025; Sun et al., 2025).

To provide a more comprehensive assessment of the available evidence, this study systematically reviewed and synthesized data from published randomized controlled trials (RCTs) investigating CHM for CAS. The primary objective was to evaluate its clinical efficacy and safety. Additionally, we employed network topology to explore the medication patterns of CHM for CAS, aiming to provide preliminary evidence to support more rational and optimized clinical application.

2 Study methodology

This study was conducted in accordance with the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) guidelines.

2.1 Registration

The study is registered in the International Prospective Register of Systematic Reviews (PROSPERO; Registration No.: CRD420261285381).

2.2 Inclusion criteria

Primary outcomes: IMT, Carotid plaque area, Carotid plaque volume.

Secondary outcomes: TC, TG, LDL-C, HDL-C.

Safety outcomes: Indicators of liver and kidney function, adverse events (AE), and adverse reactions.

2.3 Study exclusion criteria

2.4 Literature search strategy

Two reviewers independently searched Embase, the Cochrane Library, Web of Science, PubMed, and the China National Knowledge Infrastructure (CNKI) from database inception through December 2025. The search strategy combined Medical Subject Headings (MeSH) with free-text keywords. Detailed search strategies for each database are presented in Table 1.

Following initial screening, the reference lists of all included studies and relevant review articles were manually searched to identify additional eligible studies.

2.5 Literature selection and data extraction

Two reviewers conducted study selection independently, and cross-checked the results to ensure consistency. Reviewers resolved disagreements through discussion and consensus or, when necessary, by consulting subject-matter experts.

The screening process followed predefined eligibility criteria. Studies that did not meet the inclusion criteria were excluded, including irrelevant publications and retracted studies. Then, titles and abstracts were screened, and only RCTs evaluating CHM for the treatment of CAS were retained. Full-text articles were then assessed to remove duplicate publications and studies lacking essential data when the corresponding authors could not be contacted.

Standardized data were extracted independently from the included studies using Microsoft Excel. The extracted information comprised: (a) general study characteristics, including the title, first author, and publication year; (b) baseline participant characteristics, including sample size, sex distribution, age, and disease duration; (c) details of the intervention protocols; (d) information relevant to risk-of-bias assessment; (e) predefined outcome measures of interest.

To explore the medication patterns of CHM for CAS, bipartite networks were constructed linking the compound formulas, their constituent botanical drugs, and the pharmacological actions reported in the included studies.

2.6 Risk-of-bias assessments

Two reviewers independently assessed the methodological quality of the included studies using the revised Cochrane Risk of Bias 2 (RoB 2) tool (Sterne et al., 2019), and cross-checked the results for consistency. The assessment covered seven domains: bias arising from the randomization process; bias due to deviations from intended interventions; bias due to missing outcome data; bias in measurement of the outcome; bias in selection of the reported result. Each domain and the overall risk of bias are rated as low risk, some concerns, or high risk.

2.7 Statistical analysis

Statistical analyses were performed using RevMan v5.3 and R software. Dichotomous outcomes were summarized as relative risks (RRs). Continuous outcomes were expressed as mean differences (MDs) when measurement units were consistent across studies or as standardized mean differences (SMDs) when different measurement scales were used. All effect estimates were reported with corresponding 95% confidence intervals (CIs).

Between-study heterogeneity was assessed using the Chi-square test (α = 0.10) and quantified with the I² statistic. A fixed-effects model was applied when heterogeneity was low (I² ≤ 25%), whereas a random-effects model was used for moderate heterogeneity (25% < I² ≤ 75%). When substantial heterogeneity was detected (I² > 75%), potential sources were explored through appropriate analyses. When clinical heterogeneity was evident, subgroup or sensitivity analyses were conducted where feasible; otherwise, the findings were summarized descriptively.

Network visualization and topology analysis were performed using Cytoscape (version 3.10). Degree centrality was computed using the CentiScaPe plugin (version 2.2) to identify core pharmacological actions and pivotal botanical drugs.

2.8 Reference standards

The diagnostic criteria for CAS were based on the Mannheim Carotid Intima-Media Thickness and Plaque Consensus (2004–2006–2011) (Touboul et al., 2012) and the Chinese Consensus on the Diagnosis and Treatment of Atherosclerosis of the Head and Neck Arteries (Cerebrovascular Disease Society and Chinese Society of Neurology, 2017).

3 Results

3.1 Outcomes retrieval

The literature search identified a total of 3,366 records. After the initial screening, 141 duplicate records, four studies with unavailable full texts, and one retracted publication were excluded. Title and abstract screening further eliminated 3,056 records, including basic research articles, case reports, review papers, data analyses, and studies unrelated to CAS, leaving 164 articles for full-text assessment. Following detailed full-text review, studies were excluded because of incomplete data, non-traditional CHM interventions, or a high risk of bias. Ultimately, 21 randomized controlled trials (Gong et al., 2019; Cheng et al., 2021; Fan et al., 2024; Shen et al., 2022; Zhang et al., 2019; Xie et al., 2025; Zhao et al., 2023; Zhang et al., 2022; Wu et al., 2010; Wu et al., 2000; Wei et al., 2026; Wang et al., 2014; Shen et al., 2012; Mao et al., 2011; Liu et al., 2016; Liu et al., 2019; Liu et al., 2014; Jiang and Zhang, 2022; Chen and He, 2024; Zeng et al., 2021; Cao and Wang, 2013) met the eligibility criteria and were included in the final analysis (Figure 1).

FIGURE 1

3.2 Study characteristics

All RCTs in this meta-analysis were conducted in China and enrolled 3,078 participants, with 1,555 assigned to the CHM group and 1,523 to the control group. Baseline demographic and clinical characteristics were comparable between the intervention and control groups across all included studies. All participants underwent carotid IMT assessment before treatment, and no statistically significant differences in baseline IMT or other measured characteristics were observed between the CHM and control groups (p > 0.05; Table 2).

All included studies received approval from their respective institutional ethics committees and were conducted in accordance with Good Clinical Practice guidelines. The botanical drug formulations used were all included in the Pharmacopeia of the People’s Republic of China, and the prescribed dosages were within the Pharmacopeia-specified therapeutic ranges, ensuring compliance with established standards for quality, safety, and clinical application. Supplementary Table S1 present detailed characteristics of the included studies and botanical drug interventions.

3.3 Quality assessment of literature

Several studies, including those by Cheng et al., 2021. (Cheng et al., 2021), Shen et al., 2022. (Shen et al., 2022), Xie et al., 2025. (Xie et al., 2025), Zhao et al., 2023. (Zhao et al., 2023), Zhang et al., 2022. (Zhang et al., 2022), Wu et al., 2010. (Wu et al., 2010), Wu et al., 2000. (Wu et al., 2000), Shen et al., 2012. (Shen et al., 2012), Liu et al., 2019. (Liu et al., 2019), and Chen and He, 2024. (Chen and He, 2024), did not provide sufficient methodological information regarding allocation concealment or the blinding of participants, investigators, and outcome assessors. Chen and He, 2024. (Chen and He, 2024) did not clearly describe how they addressed missing outcome data.

Dan L et al. (Liu et al., 2019) assigned participants using an odd-even alternation sequence rather than true randomization, resulting in a high risk of bias in randomization. Moreover, the randomization methods were insufficiently described in the studies by Cheng et al., 2021. (Cheng et al., 2021), Shen et al., 2022. (Shen et al., 2022), Wu et al., 2010. (Wu et al., 2010) and Wu et al., 2000. (Wu et al., 2000), which incompletely reported the prespecified outcomes described in their Methods sections, resulting in a judgment of “some concerns” for selective outcome reporting. All remaining domains across the included studies were assessed as having a low risk of bias.

Beyond the risk-of-bias assessment, we also evaluated the completeness of intervention reporting based on Supplementary Table S1. Batch numbers and voucher specimens were rarely reported, which may limit the traceability and full reproducibility of the herbal interventions.

Figure 2 shows the results of the risk-of-bias assessment.

FIGURE 2

4 Meta-analysis

4.1 Evaluation of primary outcomes

4.1.1 Intima-media thickness

All 21 included studies (Gong et al., 2019; Cheng et al., 2021; Fan et al., 2024; Shen et al., 2022; Zhang et al., 2019; Xie et al., 2025; Zhao et al., 2023; Zhang et al., 2022; Wu et al., 2010; Wu et al., 2000; Wei et al., 2026; Wang et al., 2014; Shen et al., 2012; Mao et al., 2011; Liu et al., 2016; Liu et al., 2019; Liu et al., 2014; Jiang and Zhang, 2022; Chen and He, 2024; Zeng et al., 2021; Cao and Wang, 2013) reported carotid IMT as an outcome measure. Considerable heterogeneity was observed across the studies (I² = 99%); therefore, a random-effects model was used for the meta-analysis. The pooled analysis demonstrated that, compared with the control group, the CHM group achieved a significantly greater reduction in IMT, with a pooled mean difference (MD) of 0.12 (95% CI: 0.07 to 0.17; p < 0.00001) (Figure 3).

FIGURE 3

4.1.2 Comparison of plaque area

Twelve studies (31, 33, 35–40, 47–49, 51) reported carotid plaque area. Given the substantial between-study heterogeneity (I² = 100%), a random-effects model was used for the meta-analysis. The pooled results showed that patients receiving CHM experienced a significantly greater reduction in carotid plaque area than those in the control group (MD = 4.94, 95% CI: 3.13 to 6.76, p < 0.01) (Figure 4).

FIGURE 4

4.2 Evaluation of secondary outcomes

4.2.1 Comparison of TC levels

Twenty studies (Gong et al., 2019; Cheng et al., 2021; Fan et al., 2024; Shen et al., 2022; Zhang et al., 2019; Xie et al., 2025; Zhang et al., 2022; Wu et al., 2010; Wu et al., 2000; Wei et al., 2026; Wang et al., 2014; Shen et al., 2012; Mao et al., 2011; Liu et al., 2016; Liu et al., 2019; Liu et al., 2014; Jiang and Zhang, 2022; Chen and He, 2024; Zeng et al., 2021; Cao and Wang, 2013) reported TC levels. As no significant between-study heterogeneity was detected (I² = 0%), a fixed-effects model was applied for the meta-analysis. The pooled results demonstrated that the CHM group achieved a significantly greater reduction in TC levels than the control group (MD = 0.32, 95% CI: 0.22 to 0.42, p < 0.00001) (Figure 5).

FIGURE 5

4.2.2 Comparison of TG levels changes

All 21 studies (Gong et al., 2019; Cheng et al., 2021; Fan et al., 2024; Shen et al., 2022; Zhang et al., 2019; Xie et al., 2025; Zhao et al., 2023; Zhang et al., 2022; Wu et al., 2010; Wu et al., 2000; Wei et al., 2026; Wang et al., 2014; Shen et al., 2012; Mao et al., 2011; Liu et al., 2016; Liu et al., 2019; Liu et al., 2014; Jiang and Zhang, 2022; Chen and He, 2024; Zeng et al., 2021; Cao and Wang, 2013) reported TG levels. Owing to moderate between-study heterogeneity (I² = 73%), a random-effects model was used for the meta-analysis. The pooled results demonstrated that the CHM group achieved a significantly greater reduction in TG levels than the control group, with a pooled MD of 0.24 (95% CI: 0.11 to 0.37, p < 0.01) (Figure 6).

FIGURE 6

4.2.3 Comparison of LDL level changes

All 21 studies (Gong et al., 2019; Cheng et al., 2021; Fan et al., 2024; Shen et al., 2022; Zhang et al., 2019; Xie et al., 2025; Zhao et al., 2023; Zhang et al., 2022; Wu et al., 2010; Wu et al., 2000; Wei et al., 2026; Wang et al., 2014; Shen et al., 2012; Mao et al., 2011; Liu et al., 2016; Liu et al., 2019; Liu et al., 2014; Jiang and Zhang, 2022; Chen and He, 2024; Zeng et al., 2021; Cao and Wang, 2013) reported changes in low-density lipoprotein cholesterol (LDL-C) levels. Considerable between-study heterogeneity was observed (I² = 97%); therefore, a random-effects model was applied for the meta-analysis. The pooled analysis showed that the CHM group achieved a significantly greater reduction in LDL-C levels than the control group (MD = 0.37, 95% CI: 0.21 to 0.53, p < 0.01), indicating a statistically significant treatment effect (Figure 7).

FIGURE 7

4.2.4 Comparison of HDL level changes

Nineteen studies (Fan et al., 2024; Shen et al., 2022; Zhang et al., 2019; Xie et al., 2025; Zhao et al., 2023; Zhang et al., 2022; Wu et al., 2010; Wu et al., 2000; Wei et al., 2026; Wang et al., 2014; Shen et al., 2012; Mao et al., 2011; Liu et al., 2016; Liu et al., 2019; Liu et al., 2014; Jiang and Zhang, 2022; Chen and He, 2024; Zeng et al., 2021; Cao and Wang, 2013) reported high-density lipoprotein cholesterol (HDL-C) levels. Owing to substantial between-study heterogeneity (I² = 98%), a random-effects model was used for the meta-analysis. The pooled results indicated that the CHM group experienced a significantly smaller reduction in HDL-C levels than the control group (MD = −0.20, 95% CI: −0.29 to −0.10, p < 0.01), suggesting a favorable effect of CHM on preserving HDL-C levels (Figure 8).

FIGURE 8

4.3 Safety indicators

Seven studies (Gong et al., 2019; Shen et al., 2022; Zhang et al., 2019; Wei et al., 2026; Mao et al., 2011; Liu et al., 2016; Cao and Wang, 2013) reported adverse events. Relative risk (RR) was used as the effect measure, and a fixed-effects model was applied because of the low level of between-study heterogeneity (I² = 29%). The pooled analysis demonstrated that CHM was not associated with a significantly increased risk of adverse events compared with the control group (RR = 0.84, 95% CI: 0.64–1.10, p = 0.20) (Figure 9).

FIGURE 9

Further, 12 studies (Gong et al., 2019; Fan et al., 2024; Zhao et al., 2023; Zhang et al., 2022; Wu et al., 2010; Shen et al., 2012; Mao et al., 2011; Liu et al., 2016; Zeng et al., 2021; Cao and Wang, 2013) assessed hepatic and renal function. The findings consistently indicated that CHM treatment had no statistically significant adverse effects on liver or kidney function (p > 0.05), supporting its favorable safety profile.

5 Meta-regression analysis and exploration of sources of heterogeneity

5.1 Univariate meta-regression analysis

Meta-regression analysis was performed to investigate potential sources of heterogeneity using intervention type, disease severity, TCM syndrome, mean age, and treatment duration as covariates. The results identified disease severity as the principal contributor to between-study heterogeneity, accounting for 8.10% of the observed variance (R² = 8.10%). The difference in treatment effect between the moderate-to-severe IMT thickening subgroup and the mild IMT thickening subgroup approached statistical significance (regression coefficient = 0.114, 95% CI: −0.019 to 0.247, p = 0.092). None of the remaining covariates independently explained the heterogeneity observed across the included studies.

5.2 Multifactorial meta-regression analysis

Variance inflation factors (VIFs) were calculated to assess multicollinearity among the covariates, including disease severity, mean age, and treatment duration. No evidence of significant multicollinearity was identified, with VIF values of 1.25 for disease severity, 1.20 for mean age, and 1.11 for treatment duration. These findings indicated that the variables could be included simultaneously in a multivariable meta-regression model. Based on the covariate with the highest R² in the univariable analysis, multivariable meta-regression models were constructed by sequentially incorporating additional covariates.

Among the two-factor models, the combination of disease severity and mean age provided the greatest explanatory power (R² = 14.34%), followed by disease severity combined with treatment duration (R² = 13.64%) and disease severity combined with TCM syndrome pattern (R² = 10.54%).

For the three-factor models, the combination of disease severity, mean age, and treatment duration demonstrated the best model performance, explaining 31.93% of the between-study heterogeneity (R² = 31.93%), a substantial improvement over the best-performing two-factor model (R² = 14.34%) (Figure 10). These findings suggest that baseline atherosclerotic severity, as reflected by IMT grade, together with patients’ mean age and treatment duration, jointly influences the intervention’s therapeutic efficacy, collectively accounting for nearly one-third of the heterogeneity observed across the included studies.

FIGURE 10

5.3 Subgroup analysis

Based on the meta-regression findings, subgroup analyses were performed according to disease severity, mean age, and treatment duration. To determine the optimal stratification strategy, an exhaustive search was conducted by systematically evaluating all possible age cutoffs (50–68 years) and treatment duration cutoffs (2–7 months). Despite these analyses, between-study heterogeneity remained substantial, with I² values consistently exceeding 90% in most subgroup comparisons. The final subgrouping criteria were: (a) disease severity, classified as mild IMT thickening versus moderate-to-severe IMT thickening/carotid plaque; (b) mean age, ≥58 years versus <58 years; and (c) treatment duration, >3 months versus ≤3 months.

The subgroup analysis showed that Group A comprised three studies and demonstrated a pooled effect size of MD = 0.11 (95% CI: 0.05 to 0.18, p = 0.0009), with high between-study heterogeneity (I² = 88%). Group B, also including three studies, showed a pooled effect size of MD = 0.18 (95% CI: 0.15 to 0.21, p < 0.00001) and low heterogeneity (I² = 24%). Group C, consisting of eight studies, yielded a pooled effect size of MD = 0.10 (95% CI: 0.02 to 0.18, p = 0.01), although substantial heterogeneity persisted (I² = 95%). Group D included five studies and showed a pooled effect size of MD = 0.20 (95% CI: 0.01 to 0.39, p = 0.04), with similarly high heterogeneity (I² = 97%) (Figure 11).

FIGURE 11

6 Publication bias and sensitivity analyses

Sensitivity analyses were conducted using a leave-one-out approach to evaluate the robustness of the pooled results. Sequentially excluding each study did not materially alter the overall effect estimates, indicating that the findings were stable and not disproportionately influenced by any single study. A funnel plot was constructed to assess potential publication bias for changes in TC before and after treatment. The plot appeared largely symmetrical, suggesting no evident publication bias among the included studies (Figure 12).

FIGURE 12

7 Exploration of medication patterns

All 21 studies used compound Chinese botanical formulations, consisting of 93 distinct botanical drugs with a total usage frequency of 171 instances. Among these, 35 medicines were repeatedly prescribed, accounting for 75 repeated occurrences (Supplementary Table S3). The most frequently used botanical medicines were Danshen (Salvia miltiorrhiza Bunge.) and Banxia [Pinellia ternata (Thunb.)Makino].

To explore the underlying medication patterns across the included studies, the pharmacological actions of the prescribed formulas and their constituent botanical drugs were extracted, followed by network topology analysis (Figure 13). In the formula–pharmacological action network, clear phlegm (Degree = 10), removing blood stasis (Degree = 7), and activating blood circulation (Degree = 7) emerged as core nodes, representing the principal therapeutic pathways. In the ormula–botanical drug–pharmacological action network, Danshen (Degree = 34) and Banxia (Degree = 24) occupied key hub positions. Their primary attributed pharmacological actions were associated with removing blood stasis (Degree = 33) and regulating lipids (Degree = 28).

FIGURE 13

8 Discussion

8.1 Efficacy and safety

Previous studies have shown that selected CHM preparations may improve CAS by reducing serum lipid levels and attenuating carotid plaque progression (Song and Chen, 2021; Huang et al.). Building on this evidence, a systematic review and meta-analysis of RCTs were performed to comprehensively evaluate the efficacy and safety of selected CHM preparations for CAS. The findings indicate that, when used as an adjunct to conventional therapy, selected CHM preparations may further reduce carotid IMT and plaque area while improving lipid metabolism. Substantial evidence links both IMT and carotid plaque burden to cardiovascular risk, supporting the clinical significance of these effects. Mitra S et al. (Mitra et al., 2025) demonstrated a linear increase in cardiovascular event risk with increasing IMT.

In comparison, Spence JD et al. (Spence et al., 2002) reported that larger carotid plaque areas are associated with a greater likelihood of future cardiovascular events. Therefore, the additional reductions in IMT and plaque burden observed with adjunctive selected CHM preparations may translate into clinically meaningful cardiovascular benefits beyond those achieved with conventional therapy alone. These results are consistent with previous systematic reviews and clinical studies (Hu et al., 2022b; Roghani-Shahraki et al., 2021).

The negative mean difference observed for HDL-C (MD = −0.20) should not be interpreted as a detrimental effect of CHM. Because treatment effects were calculated as the difference between pre-intervention and post-intervention values, a negative MD indicates that the CHM group experienced a smaller decline in HDL-C than the control group, reflecting a protective effect on HDL-C levels. This observation is biologically plausible and is consistent with previous studies showing that ginsenosides and salvianolic acids can enhance HDL metabolism by promoting ATP-binding cassette transporter A1 (ABCA1)-mediated reverse cholesterol transport (Sun et al., 2024).

Our safety analysis further demonstrated that the selected CHM regimens did not significantly affect hepatic or renal function and were not associated with an increased incidence of adverse events. These findings agree with previous reports (Duan et al., 2023; Li et al., 2022b). This favorable safety profile is particularly relevant in clinical practice, given the well-recognized risk of hepatotoxicity associated with intensive statin therapy. However, caution remains warranted because certain botanical drug ingredients in some formulations have inherent toxic properties (Chinese Pharmacopoeia Commission, 2025), and berberine has also shown potential toxic effects in recent experimental studies (Duan et al., 2023). Moreover, the complex multi-component nature of CHM formulations presents considerable challenges for toxicological evaluation and limits comprehensive assessment of their real-world safety. Therefore, further high-quality research focusing on the safety profiles, toxicity mechanisms, and long-term adverse effects of Chinese herbal medicines is essential to support their broader clinical application and evidence-based use (Liu et al., 2022; Yao, 2026; Zhong et al., 2023).

8.2 Exploration of medication patterns

The analysis showed that compound formulas with blood stasis-removing and phlegm-clearing effects were the most commonly used treatments for CAS, consistent with previous studies (Liang et al., 2025; Zhang et al., 2023; Qiang et al., 2026). Danshen and Banxia emerged as core botanical drugs, characterized by high usage frequencies and central positions within the medication network, further supporting previous findings (Wang and Zhang, 2024; Lu et al., 2023; Lu et al., 2020; Zou et al., 2023; Lee et al., 2021). Danshen extracts have been reported to downregulate the expression of vascular cell adhesion molecule-1 (VCAM-1) and intercellular adhesion molecule-1 (ICAM-1), while reducing the production of pro-inflammatory cytokines, including tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6). These effects may improve vascular function and attenuate the progression of carotid atherosclerosis (Wang and Zhang, 2024; Lu et al., 2023). Banxia may exert lipid-regulating effects by upregulating adipose triglyceride lipase (ATGL) and hormone-sensitive lipase (HSL) expression to promote lipolysis, while activating LC3, ATG5, and ATG7 to initiate lipophagy and accelerate lipid droplet degradation (Lu et al., 2020; Zou et al., 2023; Lee et al., 2021).

8.3 Limitations and sources of heterogeneity

8.3.1 Sources of heterogeneity

Most pooled effect estimates in this meta-analysis showed substantial between-study heterogeneity. Although meta-regression and subgroup analyses were conducted to identify potential sources of heterogeneity, the final multivariable model explained only 31.93% of the observed variability (R² = 31.93%), indicating that a considerable proportion of the heterogeneity remains unexplained. Careful examination of the included studies revealed marked differences in botanical drug formulation composition, compatibility principles, dosages, administration methods, and decoction procedures, all of which may have contributed to the residual heterogeneity.

Future clinical trials should adopt standardized treatment protocols and report botanical drug formulations, preparation methods, dosing regimens, and other key methodological parameters in detail to improve comparability. Moreover, when feasible, individual participant data meta-analysis (IPD-MA) should be considered, as it enables more accurate adjustment for patient-level confounding factors and a more comprehensive exploration of heterogeneity, generating stronger and more reliable evidence to inform clinical practice.

8.3.2 Generalizability and safety of the findings

All studies included in this meta-analysis enrolled patients with confirmed carotid atherosclerosis, and the CHM preparations evaluated represent only a limited subset of the extensive range used in clinical practice. Therefore, these findings should not be interpreted as evidence supporting the efficacy of all CHM preparations for carotid atherosclerosis. Instead, they suggest that botanical drug formulations sharing the common medication patterns identified in this analysis may offer therapeutic benefits. Caution is warranted when extrapolating these results to other botanical drug formulations that were not evaluated in the included studies or to broader populations, including individuals with asymptomatic carotid atherosclerosis. Moreover, given the inherent bioavailability limitations of oral CHM preparations, interpret our exploratory findings with caution and require further mechanistic and pharmacokinetic validation.

8.3.3 Overlapping botanical drugs’ impact

All included studies evaluated compound Chinese botanical formulations rather than individual botanical drugs, and the overlap of constituent botanical drugs across formulations should be considered when interpreting the pooled findings. Our aggregate analysis of the prescriptions used in the included studies identified 93 distinct botanical medicines, of which 35 were repeatedly prescribed, accounting for 75 repeated occurrences (Supplementary Table S3). The frequent recurrence of these shared botanical medicines (or their bioactive metabolites) may contribute to the consistent therapeutic effects of selected CHM preparations observed in patients with CAS.

However, because CHM formulations exert therapeutic effects through complex multi-component, multi-target, and multi-pathway interactions, different botanical drug combinations may produce distinct pharmacological effects and influence different biological targets. Based on the currently available evidence, it is not possible to determine whether the observed clinical benefits arise primarily from individual botanical drugs, common bioactive metabolites, or synergistic interactions among multiple botanical drug components. Similarly, the available data do not permit attribution of the favorable safety profile to any specific botanical drug or constituent. Future studies integrating comprehensive phytochemical characterization, mechanistic pharmacological investigations, network pharmacology, and rigorously designed, standardized clinical trials are needed to clarify the contributions of overlapping botanical components and their synergistic interactions in treating carotid atherosclerosis.

8.3.4 Lack of long-term safety data

Most of the included RCTs did not systematically evaluate or report long-term safety outcomes, reflecting a common limitation in research on CHM preparations. Future clinical trials should follow the CONSORT Extension for Chinese Herbal Medicine Formulas to improve the completeness, consistency, and transparency of safety reporting, including comprehensive documentation of adverse events and long-term safety outcomes.

9 Conclusion

This study suggests that selected CHM preparations may effectively reduce carotid IMT, decrease carotid plaque area, and improve lipid metabolism in patients with CAS, without increasing the risk of adverse events or adversely affecting hepatic or renal function. However, well-designed studies with rigorous methodologies and standardized safety assessments should further confirm the safety of these interventions. Network topology analysis further revealed that the core therapeutic approach operates through phlegm-resolving, blood-stasis-removing, and blood-activating actions, with Danshen and Banxia serving as the pivotal botanical drug hubs.

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