Effectiveness and safety of combined treatment with herbal medicines and palliative chemotherapy for advanced gastric cancer: A systematic review, and meta-analysis

Dong-Hyeon Kim; Soo-Dam Kim; Hyeong-Joon Jun; Eun-Bin Kwag; Sang-Won Shin; Hwa-Seung Yoo; So-Jung Park

doi:10.1016/j.imr.2024.101098

. 2024 Nov 22;14(1):101098. doi: 10.1016/j.imr.2024.101098

Effectiveness and safety of combined treatment with herbal medicines and palliative chemotherapy for advanced gastric cancer: A systematic review, and meta-analysis

Dong-Hyeon Kim ^a,^b, Soo-Dam Kim ^c, Hyeong-Joon Jun ^d, Eun-Bin Kwag ^b,^e, Sang-Won Shin ^f, Hwa-Seung Yoo ^g, So-Jung Park ^a,^h,^⁎

PMCID: PMC11795544 PMID: 39911985

Abstract

Background

Advanced gastric cancer (AGC) is a leading cause of cancer-related deaths worldwide, with its treatment complicated by challenges such as high recurrence rates, severe side effects, and limited effectiveness of current therapies. Herbal medicine (HM) has emerged as an adjunct to palliative chemotherapy (PC), potentially improving tumor response and reducing side effects. This study conducted a meta-analysis to evaluate the effectiveness and safety of HM in palliative therapy for inoperable stage Ⅲ and Ⅳ AGC patients.

Methods

Databases were searched until August 2023, encompassing 10 electronic databases, including PubMed, Embase, Cochrane Library, CNKI, and ScienceON. The inclusion criteria focused on randomized controlled trials (RCTs) combining herbal medicine with palliative therapy for patients with AGC. Primary outcomes assessed were tumor response rates, overall survival, adverse drug reactions (ADRs), and patients' quality of life (QoL).

Results

In our analysis of 101 RCTs comparing PC alone to PC combined with HM, the meta-analysis demonstrated statistically significant improvements in overall response rate (ORR), disease control rate (DCR), survival rates, as well as a reduction in adverse drug reactions (ADRs) and an enhancement in quality of life (QoL) for patients receiving HM in combination with PC (p < 0.00001, I² = 0 %).

Conclusion

The combination of HM with PC significantly enhances tumor response and survival rates while reducing overall adverse drug reactions (ADRs) and improving quality of life (QoL) in patients with stage Ⅲ and Ⅳ AGC. HMs not only improve the efficacy of PC but also help alleviate side effects, including myelosuppression, digestive symptoms, nausea, vomiting, diarrhea, liver and renal injuries, and neurotoxicity.

Protocol registration: PROSPERO, CRD 42022354133.

Keywords: Advanced gastric cancer, Herbal medicine, Palliative chemotherapy, Meta-analysis

1. Introduction

Gastric cancer (GC) is the fourth leading cause of cancer-related death and the fifth most common cancer globally as of 2020, according to the Global Cancer Observatory (GCO). The incidence rate of GC in men is twice that of women.¹ Unfortunately, GC often carries a poor prognosis, with approximately 60 % of patients diagnosed with advanced disease globally.² Once GC progresses to an advanced stage, surgical intervention becomes considerably less feasible, and the disease tends to advance rapidly. Tumors extending into the muscle layer but not invading surrounding organs are classified as middle-stage gastric cancers, while those infiltrating nearby organs are categorized as advanced-stage gastric cancer. Currently, chemotherapy serves as the cornerstone treatment for advanced GC (AGC), divided into three main categories: palliative chemotherapy (PC), adjuvant chemotherapy, and neoadjuvant chemotherapy. Clinical practice guidelines recommend palliative chemotherapy as a treatment option for patients with incurable or recurrent disease.³

Standard chemotherapy for AGC uses targeted agents or cytotoxic drugs per National Comprehensive Cancer Network (NCCN) guidelines.³ Treatment is increasingly standardized and personalized. Initial treatment targets Human Epidermal Growth Factor Receptor 2(HER2) in advanced metastatic cases. Common chemotherapy regimens for AGC often include platinum-based therapies. These include combinations such as FOLFOX (folinic acid, fluorouracil [5-Fu] and oxaliplatin), SOX (tegafur [S-1] and oxaliplatin), and XELOX (capecitabine and oxaliplatin). Despite its effectiveness, chemotherapy can cause gastrointestinal reactions, bone marrow suppression, and peripheral neuropathy. These side effects often force patients to modify or discontinue their chemotherapy treatment. Consequently, for patients with inoperable AGC, the median survival rate is < 1 year, and the 5-year survival rate is 6.7 %, which is still very low.¹

Herbal medicine (HM) is widely used as complementary and alternative therapy for AGC patients in Korea and other East Asian countries, The Society for Integrative Oncology is also deeply interested in this issue.⁴^,⁵ However, there is currently an ongoing development of a standardized herbal treatment plan for AGC in Korea.6, 7, 8 The treatment approach for AGC has evolved from the holistic concept provided by traditional medicine to evidence-based treatment methods. Unlike conventional medicine, which often uses the same prescription for patients with the same condition, traditional Korean medicine utilizes various herbal prescriptions based on pattern identification, making it difficult to develop evidence-based treatment methods. This approach aligns with the concept of "Different treatments for the same disease," highlighting the diversity in therapeutic approaches within traditional Korean medicine.⁹ However, the traditional approach has shown remarkable results in reducing toxicity, improving treatment efficacy, extending patient lifespan, alleviating clinical symptoms, enhancing immunity, and improving quality of life (QoL).¹⁰ Numerous randomized controlled trials (RCTs) utilizing various herbal treatments for patients with AGC have been reported. This study aims to conduct a meta-analysis to evaluate the effectiveness and safety of combining herbal medicine with palliative chemotherapy in the treatment of advanced gastric cancer.

2. Methods

This protocol was registered with The International Prospective Register of Systematic Reviews (PROSPERO: CRD 42022354133). The reporting of this review adheres to the recommendations of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) (Supplement 1).¹¹

2.1. Criteria for inclusion and exclusion

2.1.1. Study types

This review included only Randomized Controlled Trials (RCTs) explicitly stating the use of randomization.

2.1.2. Participant types

Participants included those diagnosed with TNM stage Ⅲ-Ⅳ gastric cancer, confirmed by pathology, with no restrictions on age or sex.

2.1.3. Intervention types and controls

Studies that combined HMs, such as multi-ingredient formulations, in the intervention group without restrictions on administration were considered. Additionally, studies where chemotherapy, particularly platinum-based regimens like FOLFOX, SOX, and XELOX, was used according to NCCN guidelines, and HMs were part of the intervention group (compared to chemotherapy alone in the control group), were also included, regardless of treatment duration or clinical setting.

2.1.4. Outcome measures

The primary outcome was tumor response, assessed according to the Response Evaluation Criteria in Solid Tumors (RECIST¹²) or the WHO Solid Tumor Therapeutic Evaluation Criteria.¹³ In particular, the primary outcomes of interest were the objective response rate (ORR) and disease control rate (DCR). ORR was defined as the sum of complete response (CR) and partial response (PR), while DCR included CR, PR, and stable disease (SD).

Secondary outcomes included survival rates, quality of life (QoL), and adverse drug reactions (ADRs). Survival outcomes included overall survival (OS) and 1- to 5-year survival rates. OS was defined as the duration from the initiation of the trial to the recorded date of death from any cause or the date of the last follow-up. QoL was specifically assessed using the Karnofsky Performance Status (KPS) score, where improvement was defined as a score increase of 20 points or more between pre-treatment and post-treatment evaluations. ADRs were also evaluated, and although the grading of side effects according to CTCAE v5.0¹⁴ was not included, the incidence rate of each ADR reported in the studies were complied. The ADRs assessed included myelosuppression, neutropenia, thrombocytopenia, anemia, digestive symptoms (nausea, vomiting, diarrhea), hepatic dysfunction, renal dysfunction, neurotoxicity, and oral mucositis, as recommended by CTCAE v5.0. Studies that only reported the total effective rate or the efficacy of the Traditional Chinese Medicine (TCM) symptom score were excluded.

2.2. Literature searches

To identify studies on the effectiveness and safety of combining traditional herbal medicine with chemotherapy for patients with advanced gastric cancer (AGC), we searched ten electronic databases: PubMed, Embase, the Cochrane Library, the Chinese National Knowledge Infrastructure (CNKI), Citation Information by NII (CiNii), ScienceON, the Korean Medical Database (KMBase), Regional Information Sharing Systems (RISS), the Korean Information Service System (KISS), and the Outcome and Assessment Information Set (OASIS). We included randomized controlled trials (RCTs) comparing the combination of herbal medicine with chemotherapy to chemotherapy alone. The search was conducted up to August 2023, using the following search terms: “stomach cancer,” “stomach neoplasms,” “gastric cancer,” “gastrointestinal neoplasms,” and “herbal medicine,” “traditional medicine,” “Korean traditional medicine,” “Chinese traditional medicine,” “East Asian traditional medicine,” and “plants,” along with “randomized controlled trial.”

We limited our search to articles published between January 2010 and August 2023 to ensure that only recent and relevant studies were included, while excluding outdated data. The detailed search strategy is provided in Supplement 2.

2.3. Study selection

Search results were managed using Endnote version 20, and duplicates were removed. Two independent researchers (DHK and SDK) reviewed titles and abstracts, excluding studies that did not satisfy the inclusion criteria. Full texts were reviewed, and studies satisfying the criteria were included following consultation between the two researchers. In cases of disagreement, a third researcher (EBK) resolved the issue. The reasons for excluding studies were documented.

2.4. Data extraction

All articles were read by two independent researchers (DHK and SDK), who extracted data from the articles according to predefined criteria. The extracted data included the author's name(s), year of publication, sample size, age, sex, stage, herbal medicine intervention, chemotherapy intervention, treatment dosage and duration, main outcomes, and adverse effects. When the reported data were insufficient or unclear, the author contacted the first author or corresponding authors by e-mail or telephone to request missing data or clarify deta.

2.5. Risk of bias assessment of included studies

The Cochrane Risk of Bias (RoB) tool was used to evaluate each included trial.¹⁵ Two reviewers independently assessed multiple domains, including random sequence generation, allocation concealment, blinding of participants and personnel, blinding of outcome assessment, completeness of data sets, selective outcome reporting, and other bias such as ambiguous reporting, and undisclosed outcomes. The assessment of attrition bias focused on whether each document provided detailed descriptions of dropouts and if dropouts influenced the outcomes. Based on this analysis, a "Low RoB" rating was assigned. For the assessment of reporting bias, we primarily checked for the presence of a protocol. If a protocol was absent, we also verified whether there was a review and approval by an ethics committee. Additionally, we examined whether any outcomes were omitted. As a result, if the protocol matched the outcomes, it was rated as "Low RoB" (25 %). In cases where the protocol couldn't be verified but the results were complete, they were categorized as "Unclear RoB" (75 %). For the assessment of other biases, we focused on the clarity of the reports. Documents with unclear or simplified descriptions that hindered clear communication of the intended meaning were rated as "Unclear/High RoB." Each domain was categorized as “low”, “high”, or “unclear”. Discrepancies were resolved through consensus discussion and, where necessary, consultation with a third reviewer.

Building upon this foundation, our quality of evidence assessment utilized the GRADE system¹⁶ to classify evidence levels as high, moderate, low, or very low. Initially, RCTs provided high-quality evidence, which could be downgraded due to serious limitations such as risk of bias, inconsistency, indirectness, and imprecision. Each potential source of bias was carefully considered in context. For example, domains were not downgraded for high risk of bias if their overall impact on study outcomes was minimal or adequately addressed in sensitivity analyses. Similarly, while substantial heterogeneity was observed across studies, it did not necessarily lead to downgrading in the inconsistency domain if it did not significantly affect the overall conclusions of the meta-analysis.

Evidence could also be upgraded based on factors such as a large effect size and dose-response relationship. The resulting GRADE evidence profile provided a structured assessment of evidence quality for each outcome, highlighting both strengths and areas requiring further research.

2.6. Data analysis

The meta-analysis followed Cochrane Handbook 6.1¹⁷ guidelines, utilizing Review Manager (RevMan) v.5.4.1 for Windows (The Nordic Cochran Center, Copenhagen, Denmark). Differences between the intervention and control groups were assessed. In the analysis of clinical efficacy, dichotomous data were assessed intrems of risk ratio (RR), and continuous data were assessed in terms of mean difference (MD). Dichotomous and continuous variables were expressed as efficacy values with 95 % confidence intervals (CIs). A random-effects model was used to assess combined effect sizes from efficacy variables, and substantial clinical heterogeneity was expected across the included studies based on diversity among the interventions, study designs, and other conditions. Funnel plots were used to explore potential publication bias.

3. Results

3.1. Study selection

An initial search of medical databases retrieved 702 studies, with 246 duplicates. After removing duplicates, 438 studies remained, and 202 irrelevant studies were excluded based on title and abstract review. A total of 236 studies were evaluated, and 135 studies were subsequently excluded for the following reasons: not the target population (n = 30), not an RCT or protocol (n = 28), inappropriate intervention (n = 15), inappropriate outcome (n = 12), and thesis (n = 50). In total, 101 studies18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118 involving 7744 patients, were included in the qualitative synthesis. The study selection process is illustrated in the PRISMA flowchart criteria (Fig. 1).

Fig 1 — PRISMA 2020 flow diagram for the included studies.

3.2. Study characteristics

The following study characteristics are summarized in Table 1. The included studies were published between 2010 and 2023, with most conducted in Mainland China. The experimental groups received PC combined with various HM formulas as supplementary treatment. Of the 101 studies, 70 (69.3 %) used HM decoctions, 26 (25.7 %) used prescriptions, 3 (3 %) used powders, and 2 (2 %) used pills. All studies provided detailed descriptions of the components of the prescriptions used (Supplement 3), and the regimens of chemotherapy were described in each study. Among the chemotherapy regimens, FOLFOX was utilized most frequently in 30 studies (29.70 %), followed by SOX in 18 studies (17.82 %), XELOX in 10 studies (9.90 %), DCF in 6 studies (5.94 %), and OLF in 5 studies (4.95 %). Other regimens were used in 32 studies (31.68 %). Treatment durations ranged from 3 to 24 weeks.

Table 1.

Characteristics of the included trials.

References	Sample size E:C (M/F, Age) / Stage	Herbal medicine	Chemotherapy	Treatment period	Outcome measures	Main results
Wang 2016a¹⁸	E: 40 (22/18, 56.5) C: 35 (18/17, 56.7)/Ⅲ-Ⅳ	Bazhen Decoction	FOLFOX4	6 weeks	1) RECIST (ORR) 2) RECIST (DCR)	1) RR 1.83 [1.05, 3.19] 2) RR 1.38 [1.01, 1.87]
Li 2014a¹⁹	E: 40 (28/12, 56.9) C: 32 (20/12, 55.7)/Ⅲb-Ⅳ	Bazhen Decoction (M)	XELOX	8 weeks	1) RECIST (ORR) 2) RECIST DCR) 3) KPS improvement rate	1) RR 1.36 [0.94, 1.99] 2) RR 1.15 [0.93, 1.42] 3) RR 1.68 [0.93, 3.04]
Chen 2018²⁰	E: 22 C: 21 (27/19, 53.6)/Ⅲ-Ⅳ	Bazhen Decoction (M)	XELOX	6 weeks	1) RECIST (ORR) 2) RECIST (DCR) 3) KPS score	1) RR 1.07 [0.51, 2.25] 2) RR 1.15 [0.82, 1.60] 3) MD 6.23 [2.98, 9.48]
Yang 2011²¹	E: 24 (11/13, 52) C: 24 (12/12, 53)/Ⅲb-Ⅳ	Bazhen Decoction (M)	DCF	6 weeks	1) RECIST (ORR) 2) RECIST DCR) 3) KPS improvement rate	1) RR 1.36 [0.80, 2.33] 2) RR 1.11 [0.83, 1.49] 3) RR 3.00 [1.13, 7.99]
Zheng 2015²²	E: 43 (31/12, 60.4) C: 42 (24/18, 59.1)/Ⅳ	Buqi Jianwei Decoction	FOLFOX	6 weeks	1) RECIST (ORR) 2) RECIST DCR) 3) KPS improvement rate	1) RR 1.24 [0.64, 2.42] 2) RR 1.29 [0.96, 1.74] 3) RR 2.44 [1.05, 5.69]
Pei 2020²³	E: 36 (20/16, 56.4) C:36 (19/17, 54.7)/Ⅲb-Ⅳ	Buzhong Yiqi Decoction	TCF	8 weeks	1) RECIST (ORR) 2) RECIST (DCR)	1) RR 1.54 [0.91, 2.60] 2) RR 1.15 [0.90, 1.48]
Qin 2012²⁴	E: 27 (19/8, 59.0) C: 26 (20/6, 57.7)/Ⅲ-Ⅳ	Buzhong Yiqi Decoction (M)	SOX	8 weeks	1) RECIST (ORR) 2) RECIST (DCR) 3) KPS score	1) RR 1.05 [0.57, 1.94] 2) RR 1.11 [0.85, 1.44] 3) MD 10.57 [4.33, 16.81]
Wang 2020a²⁵	E: 30 (19/11, 50.2) C: 30 (20/10, 49.3)/Ⅱ-Ⅳ	Buzhong Yiqi Decoction (M)	XELOX	6 weeks	1) RECIST (ORR) 2) RECIST (DCR) 3) KPS score	1) RR 1.07 [0.63, 1.81] 2) RR 0.95 [0.64, 1.41] 3) MD 6.80 [2.10, 11.50]
Zhang 2021²⁶	E: 45 (31/14, 63.1) C: 45 (30/15, 62.8)/Ⅲ-Ⅳ	Buzhong Yiqi Decoction (M)	DOC	8 weeks	1) RECIST (ORR) 2) RECIST (DCR)	1) RR 1.59 [1.02, 2.48] 2) RR 1.70 [1.25, 2.31]
Wang 2019²⁷	E: 50 (30/20, 70.2) C: 50 (32/18, 70.4)/Ⅲ-Ⅳ	Chrysanthemum Pill	S-1	8 weeks	1) RECIST (ORR) 2) RECIST DCR) 3) KPS improvement rate	1) RR 1.17 [0.87, 1.56] 2) RR 1.09 [0.96, 1.25] 3) RR 1.86 [1.11, 3.12]
Dong 2016²⁸	E: 36 (24/12, 52) C: 36 (23/13, 53)/Ⅲb-Ⅳ	Dahuangzhechong Pill	SP	20 weeks	1) RECIST (ORR) 2) RECIST (DCR) 3) KPS score	1) RR 1.00 [0.69, 1.45] 2) RR 1.03 [0.85, 1.26] 3) MD 8.50 [5.03, 11.97]
Ding 2021²⁹	E: 40 (24/16, 59.4) C: 40 (22/18, 59.1)/Ⅲb-Ⅳ	Dangshen Xiaozheng Quyu Decoction	OLF	6 weeks	1) RECIST (ORR) 2) KPS improvement rate	1) RR 1.18 [0.60, 2.32] 2) RR 1.50 [0.90, 2.51]
Fei 2014³⁰	E: 40 (26/14, 58.3) C: 40 (28/12, 56.7)/Ⅲ-Ⅳ	Fuzheng Huayu Prescription	DCF	3 weeks	1) RECIST (ORR) 2) RECIST (DCR)	1) RR 1.60 [1.00, 2.57] 2) RR 1.10 [0.87, 1.38]
Lu 2016³¹	E: 29 C: 28 (30/27, 56.5)/Ⅲ-Ⅳ	Fuzheng Huayu Prescription	XELOX	6 weeks	1) RECIST (ORR) 2) RECIST (DCR)	1) RR 5.79 [1.92, 17.52] 2) RR 1.54 [1.05, 2.27]
Jing 2017³²	E: 48 C: 48 N/A (P > 0.05)/Ⅲb-Ⅳ	Fuzheng Kang'ai Decoction	SOX	6 weeks	1) RECIST (ORR) 2) RECIST (DCR)	1) RR 1.67 [1.01, 2.75] 2) RR 1.26 [1.03, 1.55]
Zhao 2019³³	E: 46 (29/17, 63.6) C: 46 (31/15, 62.7)/Ⅲb-Ⅳ	Fuzheng Kang'ai Decoction	SOX	6 weeks	1) RECIST (ORR) 2) RECIST (DCR)	1) RR 1.35 [0.84, 2.18] 2) RR 1.24 [1.01, 1.53]
Li 2016a³⁴	E: 34 C: 34 (42/26, 46.8)/Ⅲ-Ⅳ	Fuzheng Kang'ai Prescription	mFOLFOX4	8 weeks	1) RECIST (ORR) 2) RECIST (DCR)	1) RR 1.50 [1.05, 2.15] 2) RR 1.00 [0.84, 1.19]
Sun 2020³⁵	E: 40 (27/13, 63.1) C: 40 (26/14, 62.7)/Ⅲ-Ⅳ	Self-made Fuzheng Kang'ai Prescription	FOLFOX6	6 weeks	1) RECIST (ORR) 2) RECIST (DCR)	1) RR 2.50 [1.08, 5.79] 2) RR 1.29 [1.02, 1.61]
Liu 2020³⁶	E: 49 (28/21, 58.3) C: 49 (29/20, 58.5)/Ⅲ-Ⅳ	Fuzheng Sanjie Prescription	SOX	18 weeks	1) RECIST (ORR) 2) RECIST (DCR)	1) RR 1.37 [1.06, 1.76] 2) RR 1.09 [0.97, 1.23]
Zhu 2016a³⁷	E: 45 (31/14, 61.7) C: 45 (33/12, 62.1)/Ⅲ-Ⅳ	Self-made Fuzheng Xiaozheng Decoction	FOLFOX6	6 weeks	1) RECIST (ORR) 2) RECIST (DCR)	1) RR 1.83 [0.74, 4.53] 2) RR 1.33 [1.06, 1.68]
Li 2015³⁸	E: 40 (23/17, 54.6) C: 40 (26/14, 55.2)/Ⅲ-Ⅳ	Guben Jiandu Deoction	PFC	8 weeks	1) RECIST (ORR) 2) RECIST (DCR) 3) KPS improvement rate	1) RR 1.45 [0.77, 2.73] 2) RR 1.15 [0.86, 1.54] 3) RR 1.77 [1.05, 2.98]
Niu 2017³⁹	E: 100(38/62, 59.6) C: 100(40/60, 58.7)/Ⅲ-Ⅳ	Guipi Decoction	TFL	8 weeks	Survival rate (1y)	RR 1.73 [1.11, 2.70]
Li 2014b⁴⁰	E: 23 (16/7, 62.3) C: 21 (11/10, 56.9)/Ⅳ	Guishao Liujunzi Decoction	TS	12 weeks	1) RECIST (ORR) 2) RECIST (DCR) 3) KPS improvement rate	1) RR 1.12 [0.58, 2.14] 2) RR 1.11 [0.75, 1.63] 3) RR 1.83 [0.84, 3.99]
Wang 2018a⁴¹	E: 60 (34/26, 64.2) C: 60 (31/29, 68.6)/Ⅲ-Ⅳ	Guishao Liujunzi Decoction	SOX	12 weeks	1) RECIST (ORR) 2) RECIST (DCR) 3) KPS improvement rate	1) RR 1.10 [0.86, 1.41] 2) RR 1.02 [0.90, 1.15] 3) RR 1.43 [0.93, 2.19]
Zeng 2020⁴²	E: 47 (32/15, 63.4) C:46 (30/16, 63.9)/Ⅲb-Ⅳ	Huazhuo Jiedu Qingyou Prescription	FOLFOX4	24 weeks	1) RECIST (ORR) 2) RECIST (DCR) 3) Survival rate (1y)	1) RR 1.10 [0.86, 1.41] 2) RR 1.02 [0.90, 1.15] 3) RR 1.73 [1.11, 2.70]
Yu 2012⁴³	E: 30 (21/9, 64.4) C: 30 (20/10, 62.2)/Ⅲ-Ⅳ	Huoxue Huayu Yangyin Prescription	FOLFOX4	12 weeks	1) RECIST (ORR) 2) RECIST (DCR)	1) RR 1.08 [0.62, 1.89] 2) RR 0.96 [0.78, 1.19]
Shi 2019⁴⁴	E: 30 (19/11, 50.4) C: 30 (16/14, 50.5)/Ⅲ-Ⅳ	Jianpi Fuzheng Decoction	mFOLFOX6	6 weeks	1) RECIST (ORR) 2) RECIST (DCR)	1) RR 1.39 [1.00, 1.94] 2) RR 1.21 [1.00, 1.46]
Huang 2012⁴⁵	E: 40 (29/11, 39.3) C: 40 (31/9, 37.8)/Ⅲb-Ⅳ	Jianpi Fuzheng Decoction	FOLFOX	8 weeks	KPS score	MD 9.90 [4.02, 15.78]
Zhu 2017⁴⁶	E: 35 (19/16, 71.3) C: 35 (20/15, 71.4)/Ⅲb-Ⅳ	Jianpi Fuzheng Decoction	FOLFOX4	8 weeks	1) Survival rate (1y) 2) Survival rate (3y) 3) Overall Survival 4) KPS score	1) RR 1.32 [1.05, 1.65] 2) RR 1.57 [0.97, 2.54] 3) MD 3.50 [3.14, 3.86] 4) MD 7.37 [4.29, 10.45]
Xiong 2013⁴⁷	E: 40 C: 40 (39/41, 65.2)/Ⅳ	Jianpi Hewei Prescription	FOLFOX4	4 weeks	1) RECIST (ORR) 2) RECIST (DCR) 3) KPS score	1) RR 1.13 [0.66, 1.94] 2) RR 1.03 [0.85, 1.25] 3) MD 8.60 [5.20, 12.00]
Huang 2014⁴⁸	E: 30 (17/13, 53.4) C: 30 (16/14, 53.2)/Ⅳ	Jianpi Huayu Decoction	FOLFOX4	8 weeks	1) RECIST (ORR) 2) RECIST (DCR) 3) KPS improvement rate	1) RR 1.17 [0.65, 2.09] 2) RR 1.04 [0.86, 1.25] 3) RR 2.20 [1.27, 3.81]
Liu 2019⁴⁹	E: 48 (26/22, 54.4) C: 48 (25/23, 55.1)/Ⅳ	Jianpi Huayu Decoction	FOLFOX4	8 weeks	KPS score	MD 5.31 [3.00, 7.62]
Jia 2018⁵⁰	E: 20 (13/7, 65.3) C: 20 (12/8, 65.2)/Ⅲ-Ⅳ	Jianpi Huayu Prescription	SP	6 weeks	1) RECIST (ORR) 2) RECIST (DCR)	1) RR 1.07 [0.73, 1.57] 2) RR 1.12 [0.91, 1.38]
Zhao 2016⁵¹	E: 39 (28/11, 57.0) C:39 (26/13, 58.3)/Ⅲ-Ⅳ	Jianpi Huayu Prescription	SOX	6 weeks	1) RECIST (ORR) 2) RECIST (DCR) 3) KPS score	1) RR 1.17 [0.75, 1.82] 2) RR 1.03 [0.86, 1.23] 3) MD 5.70 [2.99, 8.41]
Huang 2016⁵²	E: 34 (18/16, 46.5) C: 33 (18/15, 46.7)/Ⅲb-Ⅳ	Jianpi Huoxue Prescription	SOX	8 weeks	1) RECIST (ORR) 2) RECIST (DCR) 3) Survival rate (1y) 4) KPS score	1) RR 1.28 [0.97, 1.69] 2) RR 1.11 [0.92, 1.35] 3) RR 1.86 [1.12, 3.09] 4) MD 9.69 [6.94, 12.44]
Wang 2013⁵³	E: 15 C: 15 N/A(P > 0.05)/Ⅲb-Ⅳ	Jianpi Quyu Decoction	POF	8 weeks	1) RECIST (ORR) 2) RECIST (DCR) 3) KPS score	1) RR 1.20 [0.47, 3.09] 2) RR 1.09 [0.73, 1.62] 3) MD 10.67 [3.01, 18.33]
Meng 2020⁵⁴	E: 45 (32/13, 57.5) C: 45 (30/15, 57.9)/Ⅲ-Ⅳ	Jianpi Quyu Decoction	SOX	6 weeks	KPS score	MD 14.00 [8.54, 19.46]
Chui 2018⁵⁵	E: 40C: 40 (46/34,36∼69)/Ⅳ	Self-made Jianpi Wenzhong Decoction	DC	6 weeks	1) RECIST (ORR) 2) RECIST (DCR) 3) KPS improvement rate	1) RR 1.27 [0.66, 2.45] 2) RR 1.07 [0.82, 1.40] 3) RR 1.86 [1.15, 3.00]
Zhang 2012⁵⁶	E: 23 C: 23(25/21, 65.6)/Ⅳ	Jianpi Xiao'ai Decoction	DLF	12 weeks	1) RECIST (ORR) 2) RECIST (DCR) 3) KPS improvement rate	1) RR 1.60 [0.93, 2.74] 2) RR 1.11 [0.88, 1.39] 3) RR 3.00 [1.13, 7.94]
Wu 2018⁵⁷	E: 28 (15/13, 57.6) C: 22 (12/10, 58.2)/Ⅲ-Ⅳ	Jianpi Xiao'ai Prescription	mFOLFOX6	8 weeks	1) RECIST (ORR) 2) RECIST (DCR) 3) KPS improvement rate	1) RR 1.75 [1.00, 3.04] 2) RR 1.09 [0.86, 1.38] 3) RR 1.57 [0.94, 2.63]
Weng 2020⁵⁸	E: 31 (17/14, 62.3) C: 31 (18/13, 60.3)/Ⅲ-Ⅳ	Jianpi Xiaoji Decoction	SOX	3 weeks	1) RECIST (ORR) 2) RECIST (DCR)	1) RR 1.38 [0.83, 2.31] 2) RR 1.19 [0.88, 1.60]
Chen 2016⁵⁹	E: 30 (25/5, 60.6) C: 30 (27/3, 59.9)/Ⅲ-Ⅳ	Jianpi Xiaopi Decoction	FOLFOX4	8 weeks	KPS score	MD 6.15 [2.62, 9.68]
Chen 2012⁶⁰	E: 30 (21/9, 55.6) C: 30 (24/6, 54.6)/Ⅲb-Ⅳ	Jianpi Yiliu Decoction	FOLFOX	6 weeks	1) KPS score 2) KPS improvement rate	1) MD 5.48 [2.75, 8.21] 2) RR 2.17 [0.95, 4.94]
Ma 2017⁶¹	E: 40 (25/15, 46.2) C: 40 (23/17, 45.9)/Ⅲ-Ⅳ	Jianpi Yiqi Sanjie Decoction	FOLFOX	8 weeks	1) RECIST (ORR) 2) RECIST (DCR) 3) KPS improvement rate	1) RR 1.63 [1.04, 2.53] 2) RR 1.18 [0.92, 1.51] 3) RR 1.64 [1.00, 2.71]
Wang 2018b⁶²	E: 21 (14/7, 65.8) C: 21 (12/9, 66.4)/Ⅳ	Jianpi Yiqi Sanjie Decoction	SOX	12 weeks	1) RECIST (ORR) 2) RECIST (DCR)	1) RR 3.00 [0.68, 13.20] 2) RR 1.88 [1.02, 3.45]
Jin 2016⁶³	E: 35 (21/14, 56.3) C: 35 (20/15, 57.1)/Ⅳ	Jianpi Yiqi Yangyin Huoxue Prescription	DPF	4 weeks	RECIST (ORR)	ORR RR 2.33 [1.43, 3.80]
Lai 2010⁶⁴	E: 25 (20/5, 44) C: 30 (24/6, 48)/Ⅳ	Jianpi Yishen Decoction	TFL	8 weeks	1) RECIST (ORR) 2) RECIST (DCR) 3) KPS improvement rate	1) RR 1.20 [0.69, 2.09] 2) RR 1.05 [0.82, 1.34] 3) RR 1.73 [0.89, 3.37]
Wang 2015a⁶⁵	E: 30 (21/9, 70.2) C: 30 (23/7, 72.6)/Ⅲb-Ⅳ	Jianpi Yishen Decoction	PCC	8 weeks	1) RECIST (ORR) 2) RECIST (DCR) 3) KPS improvement rate	1) RR 1.67 [1.00, 2.76] 2) RR 1.12 [0.93, 1.35] 3) RR 2.14 [1.02, 4.49]
Xu 2018⁶⁶	E: 35 (23/12, 71.3) C: 35 (24/11, 70.8)/Ⅲ-Ⅳ	Jianpi Yishen Decoction	PCC	6 weeks	1) RECIST (ORR) 2) RECIST (DCR)	1) RR 1.71 [1.08, 2.73] 2) RR 1.14 [0.96, 1.35]
Zheng 2011⁶⁷	E: 35 (29/6, 64) C: 30 (27/3, 63)/Ⅲb-Ⅳ	Jianpi Yishen Prescription	FOLFOX	6 weeks	1) RECIST (ORR) 2) RECIST (DCR) 3) KPS improvement rate	1) RR 1.07 [0.60, 1.92] 2) RR 1.09 [0.83, 1.43] 3) RR 2.04 [1.05, 3.97]
Wang 2015b⁶⁸	E: 39 (25/14, 49.1) C: 39 (29/10, 50.2)/Ⅲ-Ⅳ	Jianpi Yiwei Decoction	FMC	8 weeks	1) RECIST (ORR) 2) RECIST (DCR) 3) KPS improvement rate	1) RR 2.57 [1.21, 5.45] 2) RR 1.32 [1.07, 1.63] 3) RR 3.17 [1.42, 7.07]
Wang 2011a⁶⁹	E: 34 (22/12,32∼75) C: 34 (23/11,34∼73)/Ⅲ-Ⅳ	Jianzhong Huashi Decoction	XP	3 weeks	KPS improvement rate	RR 9.00 [2.26, 35.82]
Xing 2017⁷⁰	E: 42 (26/16, 66.9) C: 42 (24/18, 66.1)/Ⅲ-Ⅳ	Self-made Kang'ai Decoction	FOLFOX	8 weeks	1) RECIST (ORR) 2) RECIST (DCR)	1) RR 1.64 [0.99, 2.73] 2) RR 1.18 [1.00, 1.38]
Fang 2018⁷¹	E: 30 C: 30 (32/28, 55)/Ⅲb-Ⅳ	Lizhong Decoction (M)	XELOX	3 weeks	KPS improvement rate	RR 1.67 [0.87, 3.20]
Feng 2015⁷²	E: 31 (NA, 56.9) C: 31 (NA, 57.2)/Ⅲ-Ⅳ	Liujunzi Decoction	DCF	6 weeks	1) RECIST (ORR) 2) RECIST (DCR) 3) KPS improvement rate	1) RR 1.06 [0.67, 1.70] 2) RR 1.00 [0.85, 1.18] 3) RR 2.10 [1.19, 3.69]
Lin 2017⁷³	E: 35 (20/15, 53) C: 34 (18/16, 51)/Ⅲ-Ⅳ	Liujunzi Decoction	FOLFOX	4 weeks	1) RECIST (ORR) 2) RECIST (DCR) 3) KPS improvement rate	1) RR 1.02 [0.70, 1.47] 2) RR 0.97 [0.76, 1.25] 3) RR 1.78 [1.06, 3.00]
Fan 2013⁷⁴	E: 19 C: 19 (20/18, 62.3)/Ⅲ-Ⅳ	Liujunzi Decoction	FOLFOX	24 weeks	KPS improvement rate	RR 2.40 [1.05, 5.49]
Wang 2016b⁷⁵	E: 23 (10/13, 67) C: 22 (10/12, 67)/Ⅲ-Ⅳ	Liujunzi Decoction (M)	FOLFOX4	8 weeks	KPS improvement rate	RR 2.80 [1.21, 6.50]
Guo 2016⁷⁶	E: 75 (47/28, 56.1) C: 75 (49/26, 55.5)/Ⅲ-Ⅳ	Qiangpi Yiqi Prescription	S-1	24 weeks	1) RECIST (ORR) 2) RECIST (DCR)	1) RR 1.29 [0.84, 1.98] 2) RR 1.10 [0.96, 1.26]
He 2014⁷⁷	E: 22 (15/7, 56.5) C: 22 (16/6, 56.9)/Ⅲ-Ⅳ	Qizhu Prescription	FOLFOX4	12 weeks	1) RECIST (ORR) 2) RECIST (DCR) 3) KPS improvement rate	1) RR 1.50 [0.49, 4.59] 2) RR 1.15 [0.74, 1.81] 3) RR 1.20 [0.66, 2.18]
Zhang 2020a⁷⁸	E: 43 (24/19, 50.4) C: 43 (26/17, 49.1)/Ⅲ-Ⅳ	Shengyang Yiwei Decoction	SOX	9 weeks	1) RECIST (ORR) 2) RECIST (DCR)	1) RR 1.41 [1.00, 1.99] 2) RR 1.13 [0.90, 1.40]
Kong 2021⁷⁹	E: 30 C: 30 (40/20, 60.9)/Ⅲb-Ⅳ	Shenhubanxia Decoction	DOS	9 weeks	1) RECIST (ORR) 2) RECIST (DCR)	1) RR 1.82 [1.07, 3.10] 2) RR 1.13 [0.91, 1.39]
Li 2016b⁸⁰	E: 50 (29/21, 62.2) C: 50 (26/24, 58.7)/Ⅲ-Ⅳ	Shenlingbaizhu Powder	TS	12 weeks	1) RECIST (ORR) 2) RECIST (DCR) 3) KPS improvement rate	1) RR 1.23 [0.82, 1.84] 2) RR 1.11 [0.89, 1.39] 3) RR 1.83 [0.84, 3.99]
Zhang 2017⁸¹	E: 40 (25/15, 56.7) C: 40 (28/12, 56.2)/Ⅲ-Ⅳ	Shenlingbaizhu Powder	TS	8 weeks	1) RECIST (ORR) 2) RECIST (DCR) 3) KPS improvement rate	1) RR 1.67 [0.95, 2.93] 2) RR 1.27 [0.90, 1.80] 3) RR 2.00 [1.12, 3.56]
Lai 2018⁸²	E: 30 (22/8, 45) C: 30 (24/6, 44)/Ⅳ	Shenlingbaizhu Powder	TCF	4 weeks	KPS improvement rate	RR 2.29 [1.10, 4.74]
Yu 2019a⁸³	E: 45 (27/18, 61.7) C: 45 (25/20, 62.4)/Ⅲ-Ⅳ	Shenyi Jianzhong Decoction	SOX	12 weeks	1) RECIST (ORR) 2) RECIST (DCR)	1) RR 0.92 [0.61, 1.37] 2) RR 1.08 [0.91, 1.28]
Liu 2018⁸⁴	E: 41 (22/19, 50.8) C:41 (21/20, 51.0)/Ⅲ-Ⅳ	Shenyi Jianzhong Decoction	SOX	12 weeks	1) RECIST (ORR) 2) RECIST (DCR)	1) RR 1.19 [0.72, 1.97] 2) RR 1.29 [1.01, 1.63]
Wang 2017⁸⁵	E: 41 (25/16, 52.7) C: 41 (22/19, 53.2)/Ⅲ-Ⅳ	Shenyi Jianzhong Decoction (M)	S-1	12 weeks	1) RECIST (ORR) 2) RECIST (DCR) 3) KPS improvement rate	1) RR 1.04 [0.77, 1.40] 2) RR 1.06 [0.88, 1.27] 3) RR 1.90 [1.01, 3.57]
Yang 2018⁸⁶	E: 40 (21/19, 59.4) C: 40 (23/17, 54.3)/Ⅲb-Ⅳ	Shenyu Yangwei Decoction	XELOX	6 weeks	1) RECIST (ORR) 2) RECIST (DCR) 3) KPS improvement rate	1) RR 1.69 [1.00, 2.87] 2) RR 1.18 [0.92, 1.51] 3) RR 1.63 [1.04, 2.53]
Jia 2019⁸⁷	E: 31 (20/11, 56.8) C: 31 (22/9, 56.8)/Ⅲ-Ⅳ	Shiquandabu Decoction	XELOX	6 weeks	1) RECIST (ORR) 2) RECIST (DCR)	1) RR 1.75 [1.06, 2.90] 2) RR 1.24 [0.93, 1.65]
Cao 2010⁸⁸	E: 51 C: 54 (66/39, 58)/Ⅲ-Ⅳ	Sijunkang'ai Decoction	FOLFOX4	8 weeks	1) RECIST (ORR) 2) RECIST (DCR) 3) KPS improvement rate	1) RR 1.31 [0.78, 2.18] 2) RR 1.20 [0.97, 1.48] 3) RR 1.25 [0.97, 1.60]
Wu 2020⁸⁹	E: 47 (28/19, 55.5) C: 47 (27/20, 56.5)/Ⅲ-Ⅳ	Wei'aining Decoction	FOLFOX6	12 weeks	1) RECIST (ORR) 2) RECIST (DCR)	1) RR 1.26 [0.93, 1.70] 2) RR 1.07 [0.93, 1.25]
Yin 2016⁹⁰	E: 36 (17/19, 61.7) C: 36 (16/20, 62.8)/Ⅲ-Ⅳ	Wei'aining Decoction	FOLFOX	12 weeks	KPS improvement rate	RR 1.83 [0.74, 4.42]
Gu 2020⁹¹	E: 51 (28/23, 70.1) C: 51 (30/21, 69.7)/Ⅲ-Ⅳ	Wei'aining Decoction	SOX	12 weeks	KPS score	MD 8.59 [6.30, 10.88]
Zhang 2020b⁹²	E: 53 C: 53 (59/47, 56.3) /Ⅲb-Ⅳ	Xiangsha Liujunzi Decoction	SOX	4 weeks	1) RECIST (ORR) 2) RECIST (DCR)	1) RR 1.52 [1.06, 2.19] 2) RR 1.27 [1.04, 1.55]
Ni 2015⁹³	E: 33 (22/11, 69.3) C: 33 (21/12, 68.9)/Ⅲ-Ⅳ	Xiangsha Liujunzi Decoction	DCF	6 weeks	1) Survival rate (1y) 2) Survival rate (2y) 3) Survival rate (3y)	1) RR 1.35 [0.91, 2.02] 2) RR 1.45 [0.80, 2.64] 3) RR 2.25 [0.77, 6.59]
Tang 2017⁹⁴	E: 24 C: 24 (29/19, 59.8) / Ⅲ-Ⅳ	Xiangsha Liujunzi Decoction	S-1	8 weeks	KPS improvement rate	RR 2.80 [1.20, 6.55]
Li 2016c⁹⁵	E: 40 (21/19, 64.6) C: 40 (22/18, 64.1)/Ⅲ-Ⅳ	Xiangsha Liujunzi Decoction (M)	DCF	3 weeks	1) RECIST (ORR) 2) RECIST (DCR) 3) Survival rate (1y) 4) Survival rate (2y)	1) RR 1.67 [1.13, 2.45] 2) RR 1.27 [1.04, 1.54] 3) RR 1.33 [0.99, 1.79] 4) RR 1.73 [1.58, 2.81]
Tong 2018⁹⁶	E: 38 (21/18, 62.7) C: 37 (24/16, 63.5)/Ⅲ-Ⅳ	Xiangsha Liujunzi Decoction (M)	XELOX	12 weeks	1) RECIST (ORR) 2) RECIST (DCR) 3) KPS improvement rate	1) RR 1.34 [0.61, 2.95] 2) RR 1.23 [0.90, 1.67] 3) RR 2.34 [0.91, 5.98]
Hu 2019⁹⁷	E: 40 (23/17, 57.0) C: 40 (21/19, 57.5)/Ⅲ-Ⅳ	Xiangsha Liujunzi Decoction (M)	XELOX	6 weeks	1) RECIST (ORR) 2) RECIST (DCR)	1) RR 1.20 [0.71, 2.03] 2) RR 1.43 [1.01, 2.02]
Gu 2013⁹⁸	E: 32 (20/12, 54.9) C: 35 (22/13, 52.3) /Ⅲb-Ⅳ	Xiaotan Sanjie Prescription	SOX	16 weeks	RECIST (ORR)	RR 1.30 [0.82, 2.06]
Yu 2018⁹⁹	E: 41 (25/16, 74.2) C: 44 (20/24, 73.5)/Ⅲ-Ⅳ	Yiqi Jianpi Prescription	S-1	16 weeks	1) RECIST (ORR) 2) RECIST (DCR) 3) Survival rate (1y) 4) KPS improvement rate	1) RR 1.17 [0.79, 1.73] 2) RR 1.10 [0.94, 1.29] 3) RR 1.23 [0.92, 1.65] 4) RR 1.56 [1.07, 2.27]
Gao 2019¹⁰⁰	E: 50 (NA, 68.1) C: 50 (NA, 66.7)/Ⅲ-Ⅳ	Yiqi Jianpi Huaji Prescription	DC	9 weeks	1) RECIST (ORR) 2) RECIST (DCR) 3) KPS score	1) RR 1.25 [0.74, 2.12] 2) RR 1.24 [0.98, 1.58] 3) MD 8.13 [6.21, 10.05]
Bu 2016¹⁰¹	E: 20 C: 20 (27/13, 59.5)/Ⅲ-Ⅳ	Yiqi Jianpi Huoxue Decoction	DOF	8 weeks	1) RECIST (ORR) 2) RECIST (DCR) 3) KPS score	1) RR 1.67 [0.75, 3.71] 2) RR 1.12 [0.91, 1.48] 3) MD 5.00 [1.34, 8.66]
Ge 2017¹⁰²	E: 30 (17/13, 59.7) C: 30 (16/14, 58.2)/Ⅲ-Ⅳ	Yiqi Jianpi Huoxue Decoction	FOLFOX	8 weeks	1) RECIST (ORR) 2) RECIST (DCR)	1) RR 1.56 [1.08, 2.26] 2) RR 1.07 [0.96, 1.20]
Jiang 2017¹⁰³	E: 48 (26/22, 60.8) C: 48 (27/21, 60.1)/Ⅲ-Ⅳ	Yiqi Jianpi Huoxue Decoction	FMC	8 weeks	1) RECIST (ORR) 2) RECIST (DCR)	1) RR 1.91 [1.04, 3.51] 2) RR 1.03 [0.78, 1.36]
Pang 2018¹⁰⁴	E: 40 (25/15, 50.2) C: 40 (22/18, 49.3)/Ⅲ-Ⅳ	Yiqi Jianpi Jiedu Prescription	FOLFOX4	8 weeks	1) RECIST (ORR) 2) RECIST (DCR)	1) RR 2.00 [1.02, 3.91] 2) RR 1.25 [0.99, 1.58]
Zhou 2015¹⁰⁵	E: 15 (10/5, 56.9) C: 14 (9/5, 56.1) /Ⅲb-Ⅳ	Yiqi Jianpi Qingre Huayu Decoction	OLF	8 weeks	1) RECIST (ORR) 2) RECIST (DCR)	1) RR 1.63 [1.02, 2.62] 2) RR 1.08 [0.89, 1.30]
Zhu 2016b¹⁰⁶	E: 42 (26/16, 58.5) C: 42 (28/14, 57.8)/Ⅲ-Ⅳ	Yiqi Jianpi Yangwei Prescription	DSP	4 weeks	1) RECIST (ORR) 2) RECIST (DCR) 3) KPS score	1) RR 1.43 [0.84, 2.43] 2) RR 1.15 [0.96, 1.39] 3) MD 4.76 [2.48, 7.04]
Xiong 2012¹⁰⁷	E: 30 (20/10, 64.5) C: 28 (18/10, 63.5)/Ⅲb-Ⅳ	Yiqi Qingdu Huayu Prescription	OLF	24 weeks	1) RECIST (ORR) 2) RECIST (DCR) 3) Survival rate (1y) 4) Survival rate (2y) 5) Survival rate (3y)	1) RR 1.12 [0.58, 2.17] 2) RR 1.14 [0.93, 1.38] 3) RR 1.07 [0.79, 1.46] 4) RR 1.73 [0.80, 2.01] 5) RR 1.49 [0.82, 2.72]
Ma 2018¹⁰⁸	E: 30 C: 30 (37/23, 57.9) /Ⅲb-Ⅳ	Yiqi Qingre Jiedu Prescription	DCF	6 weeks	1) RECIST (ORR) 2) RECIST (DCR) 3) KPS score 4) KPS improvement rate	1) RR 1.45 [0.82, 2.59] 2) RR 1.27 [1.01, 1.61] 3) MD 1.64 [0.33, 2.95] 4) RR 1.44 [0.73, 2.86]
Ji 2016¹⁰⁹	E: 26 (15/11, 69.5) C: 26 (16/10, 70.5)/Ⅲ-Ⅳ	Yiqi Shenghua Decoction	FOLFOX	8 weeks	1) RECIST (ORR) 2) RECIST (DCR) 3) Survival rate (1y) 4) Survival rate (3y) 5) Survival rate (5y)	1) RR 1.38 [0.87, 2.20] 2) RR 1.14 [0.92, 1.42] 3) RR 1.04 [0.87, 1.25] 4) RR 1.45 [0.85, 2.50] 5) RR 1.33 [0.54, 3.31]
Wang 2018c¹¹⁰	E: 46 (25/21, 62.5) C:49 (30/19, 64.7)/Ⅲ-Ⅳ	Yiqi Yangyin Prescription	XELOX	8 weeks	1) RECIST (ORR) 2) RECIST (DCR) 3) KPS score	1) RR 1.13 [0.89, 1.43] 2) RR 1.04 [0.92, 1.18] 3) MD 4.42 [0.86, 7.98]
Liu 2021¹¹¹	E: 45 (25/20, 59.3) C: 45 (25/20, 60.1)/Ⅲ-Ⅳ	Yiwei Shengyang Decoction (M)	DOF	9 weeks	1) RECIST (ORR) 2) RECIST (DCR)	1) RR 1.67 [1.10, 2.52] 2) RR 1.08 [0.94, 1.24]
Li 2020¹¹²	E: 49 (32/17, 55.7) C: 49 (31/18, 52.4)/Ⅲ-Ⅳ	Yiwei Xiao'ai Decoction	OLF	9 weeks	1) RECIST (ORR) 2) RECIST (DCR)	1) RR 1.87 [1.15, 3.04] 2) RR 1.08 [0.87, 1.35]
Huang 2020¹¹³	E: 43 (27/16, 65.9) C: 43 (25/18, 64.3)/Ⅲ-Ⅳ	Yiwei Xiao'ai Decoction	OLF	9 weeks	Survival rate (3y)	RR 1.59 [1.03, 2.45]
Shen 2017¹¹⁴	E: 34 (19/15, 54.2) C: 34 (21/13, 56.1) /Ⅲb-Ⅳ	Zhengyang Lilao Decoction	TCF	4 weeks	1) RECIST (ORR) 2) RECIST (DCR) 3) KPS score	1) RR 0.95 [0.61, 1.46] 2) RR 0.97 [0.85, 1.11] 3) MD 10.33 [4.72, 15.94]
Yu 2019b¹¹⁵	E: 53 (25/28,67.6) C: 53 (28/25,68.5)/Ⅲ-Ⅳ	Zhengyang Lilao Decoction	Bevacizumab	3 weeks	1) RECIST (ORR) 2) RECIST (DCR) 3) Overall Survival 4) KPS score	1) RR 1.68 [1.11, 2.57] 2) RR 1.44 [1.03, 2.02] 3) MD 5.04 [4.21, 5.87] 4) MD 10.52 [6.02, 15.02]
Wang 2020b¹¹⁶	E: 41 (26/15, 57.2) C: 41 (27/14, 58.0)/Ⅲ-Ⅳ	Ziyin Jianpi Quyu Decoction	SOX	12 weeks	1) RECIST (ORR) 2) RECIST (DCR)	1) RR 1.29 [0.74, 2.22] 2) RR 1.10 [0.88, 1.37]
Jiang 2018¹¹⁷	E:134(77/57 60.8) C:134(71/63 62.0)/Ⅲ-Ⅳ	Unnamed Decoction	SOX	12 weeks	1) RECIST (ORR) 2) RECIST (DCR)	1) RR 1.28 [1.03, 1.60] 2) RR 1.14 [1.01, 1.29]
Wang 2011b¹¹⁸	E: 36 (26/10, 65.8) C: 36 (24/12, 62.4)/Ⅲ-Ⅳ	Unnamed Prescription	FOLFOX4	16 weeks	1) RECIST (ORR) 2) RECIST (DCR) 3) KPS improvement rate	1) RR 1.63 [1.02, 2.62] 2) RR 1.08 [0.89, 1.30] 3) RR 1.52 [1.13, 2.06]

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E, experimental; C, control; M, modified; MD, mean difference, RR: Risk Ratio; DC, docetaxel and cisplatin; DCF, docetaxel, cisplatin, and fluorouracil; DLF, cisplatin, leucovorin, and fluorouracil; DOC, docetaxel, oxaliplatin, and capecitabine; DOF, docetaxel, oxaliplatin, and 5‐fluorouracil; DOS, docetaxel, oxaliplatin and S-1; DPF, docetaxel, cisplatin, and fluorouracil; DSP, docetaxel, S-1 and cisplatin; FOLFOX, folinic acid, fluorouracil, and oxaliplatin; FMC, fluorouracil, mitomycin, and cisplatin; OLF, oxaliplatin, leucovorin, and fluorouracil; PCC, pirarubicin, capecitabine, and cisplatin; PFC, paclitaxel, fluorouracil and cisplatin; POF, paclitaxel, oxaliplatin, and fluorouracil; SP, S-1 and cisplatin; SOX, S-1 (tegafur, gimeracil, and oteracil) and oxaliplatin; TCF, paclitaxel, cisplatin, and 5-flourouracil; TFL, paclitaxel, fluorouracil and leucovorin; TS, paclitaxel and S-1; XELOX, capecitabine and oxaliplatin; XP, capecitabine and cisplatin.

3.3. Risk of bias of included studies

Eighty-nine studies used computer software or random number tables for randomization, while 12 studies did not specify their randomization method. Only 10 % of the studies explicitly mentioned allocation concealment. Blinding participants or personnel was not feasible in most RCTs, as only the experimental group received THM. This resulted in a high or unclear risk of performance bias, with many studies rated accordingly. None of the studies provided protocols for result selection, preventing assessment of adherence to a prespecified analysis plan. Consequently, all studies were rated as having concerns or high risk of bias in this domain (Fig. 2).

Fig 2 — Risk of bias (A) graph; (B) summary.

3.4. Intervention effects

3.4.1. Tumor response assessment

A total of 84 studies18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38^,40, 41, 42, 43, 44^,⁴⁷^,⁴⁸^,50, 51, 52, 53^,55, 56, 57, 58^,61, 62, 63, 64, 65, 66, 67, 68^,⁷⁰^,⁷²^,⁷³^,76, 77, 78, 79, 80, 81^,83, 84, 85, 86, 87, 88, 89^,94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112^,114, 115, 116, 117, 118 used RECIST as the primary endpoint to assess tumor response. However, three studies²⁹^,⁶³^,⁹⁸ did not provide sufficient data on SD, so they were excluded from the DCR analysis.

The ORR showed a RR of 1.34 (95 % CI: 1.28 to 1.41, p < 0.00001, I² = 0 %, N = 84, n = 6442). Similarly, the DCR had a RR of 1.12 (95 % CI: 1.10 to 1.15, p < 0.00001, I² = 0 %, N = 81, n = 6225). These results, as shown in Supplement 4, indicate a significant improvement in both ORR and DCR with the combination of palliative chemotherapy and herbal treatment.

3.4.2. Survival rate assessment

A meta-analysis of 10 studies³⁹^,⁴²^,⁴⁶^,⁵²^,⁹²^,⁹⁵^,⁹⁹^,¹⁰⁷^,¹⁰⁹^,¹¹³ using a REM evaluated 1- to 5-year survival rates, showing significant improvements with HMs and chemotherapy. In the 9 studies³⁹^,⁴²^,⁴⁶^,⁵²^,⁹²^,⁹⁵^,⁹⁹^,¹⁰⁷^,¹⁰⁹ analyzed the 1-year survival rate, the RR was 1.29 (95 % CI: 1.13 to 1.48, p = 0.0003, I² = 43 %, N = 9, n = 771). For the 2-year survival rate, analyzed in 3 studies,⁹²^,⁹⁵^,¹⁰⁷ the RR was 1.40 (95 % CI: 1.03 to 1.91, p = 0.03, I² = 0 %, N = 3, n = 204). The 3-year survival rate, analyzed in 5 studies,⁴⁶^,⁹²^,¹⁰⁷^,¹⁰⁹^,¹¹³ showed an RR of 1.57 (95 % CI: 1.23 to 2.00, p = 0.0003, I² = 0 %, N = 5, n = 332). No studies reported on the 4-year survival rate, and only one study¹⁰⁹ reported the 5-year survival rates, with an RR of 1.33 (95 % CI: 0.54 to 3.31, p = 0.53, N = 1, n = 52). OS was analyzed in 2 studies,⁴⁶^,¹¹⁵ with a MD of 4.22 months (95 % CI: 2.72 to 5.73, p < 0.00001, I² = 91 %, N = 2, n = 176) as shown in Supplement 5.

3.4.3. QoL

The meta-analysis showed a significant improvement in QoL for the HM plus chemotherapy group. Twenty-two studies²⁰^,²⁴^,²⁶^,²⁸^,45, 46, 47^,⁴⁹^,51, 52, 53, 54^,⁵⁹^,⁶⁰^,⁹¹^,¹⁰⁰^,¹⁰¹^,¹⁰⁶^,¹⁰⁸^,¹¹⁰^,¹¹⁴^,¹¹⁵ included KPS scores, with a MD of 7.19 (95 % CI: 5.84 to 8.54, p < 0.00001, I² = 76 %, N = 22, n = 1594) indicating statistically significant results.

Similarly, KPS improvement rates from 37 studies¹⁹^,²¹^,²²^,²⁷^,²⁹^,³⁸^,⁴⁰^,⁴¹^,⁴⁸^,55, 56, 57^,⁶⁰^,⁶¹^,⁶⁴^,⁶⁵^,67, 68, 69^,71, 72, 73, 74, 75^,⁷⁷^,80, 81, 82^,⁸⁵^,⁸⁶^,⁸⁸^,⁹⁰^,⁹³^,⁹⁶^,⁹⁹^,¹⁰⁸^,¹¹⁸ showed a RR of 1.72 (95 % CI: 1.56 to 1.89, p < 0.00001, I² = 0 %, N = 36, n = 2497). These findings also indicate statistically significant results, as shown in Supplement 6.

3.4.4. Assessment of ADRs

The meta-analysis showed that patients receiving both HMs and chemotherapy had a lower likelihood of experiencing ADRs such as myelosuppression, neutropenia, thrombocytopenia, anemia, digestive symptoms, nausea, vomiting, diarrhea, hepatic and renal dysfunction, neurotoxicity, and oral mucositis compared to those receiving chemotherapy alone (Table 2). These findings highlight a significant reduction in ADRs associated with HM plus chemotherapy treatment.

Table 2.

The results of meta-analysis of adverse drug reactions of HM+Chemotherapy vs. Chemotherapy with random effect model.

Adverse drug reactions	No of RCTs	HM + Chemo (Events/Total)	Chemotherapy (Events/Total)	Total RR [95 % CI]	I² (%)	References
Myelosuppression	22	205/887	323/882	0.66 [0.58,0.76]	0	21,29,30,31,33,38,40,41,42,61,62,69,76,79,80,81,91,93,96,
						104,106,115
Neutropenia	42	500/1648	876/1645	0.60 [0.54,0.66]	41	20,22,24,26,28,35,44,45,46,48,49,51,53,54,55,56,57,59,60,
						65,70,72,73,77,79,84,85,86,88,91,92,94,97,99,103,107,110,
						111,112,113,116,117
Anemia	18	185/692	303/692	0.67 [0.59,0.76]	0	26,47,53,55,56,59,60,65,72,73,77,82,85,86,88,92,103,117
Thrombocytopenia	38	295/1472	530/1473	0.57 [0.51,0.64]	0	20,24,26,35,44,45,46,48,49,51,52,53,54,55,56,57,59,60,64,
						65,70,72,73,78,79,82,84,85,86,91,99,103,110,111,112,
						113,116,117
Digestive symptoms	21	157/751	335/748	0.49 [0.42,0.58]	0	26,29,30,31,33,35,42,56,57,61,62,79,91,92,93,99,104,
						106,110,113,116
Nausea and vomiting	44	523/1767	951/1763	0.56 [0.49,0.63]	54	20,21,22,23,28,34,38,40,41,44,45,46,47,51,52,53,54,55,59,
						64,65,69,70,71,73,76,77,78,80,81,84,85,86,88,93,94,96,97,
						103,107,111,112,116,117
Diarrhea	28	215/1111	444/1108	0.52 [0.46,0.60]	0	21,28,34,38,40,45,46,47,51,52,53,65,69,71,77,80,81,84,85,
						88,93,94,96,97,103,107,111,117
Hepatic dysfunction	28	179/1134	294/1131	0.64 [0.55,0.74]	0	22,24,26,31,33,38,40,41,48,49,51,53,55,57,80,81,86,88,93,
						96,97,99,108,110,112,115,117
Renal dysfunction	13	93/499	159/497	0.64 [0.53,0.77]	4	22,24,26,33,48,49,57,72,86,88,108,112
Neurotoxicity	32	247/1230	457/1184	0.59 [0.53,0.67]	0	20,21,24,26,28,35,41,42,44,46,47,48,49,53,54,55,59,62,64,
						65,70,77,88,93,103,104,106,107,108,112,116,117
Oral mucositis	14	93/524	145/525	0.68 [0.54,0.86]	0	24,26,28,47,53,65,70,85,86,88,96,104,111,112

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RR: Risk Ratio; I²: Moderate heterogeneity (30 % ≤ I² ≤ 75 %), Low heterogeneity (I² ≤ 30 %).

3.5. Publication bias

Funnel plot analysis for tumor response studies (ORR and DCR) showed central clustering with a rightward skew (Supplement 7). For survival rates, one-year survival rates displayed symmetry, while two- and three-year rates skewed towards higher values. Literature on publication bias for five-year survival and overall survival (OS) was limited. ADR data showed central clustering with a leftward skew, indicating potential publication bias.

3.6. Certainty of evidence assessment at grade system

Detailed outcomes, effects, and absolute values are presented in Table 3.

Table 3.

Summary of findings with GRADE.

Outcomes	Studies (RCTs)	No. of patients HM+CT (%), CT (%)	Effect (RR & 95 % CI)	Absolute Effect (per 1000 & 95 % CI)	Certainty of evidence
Tumor Response Assessment
ORR	84	1800/3231(55.7), 1296/3211(40.4)	RR 1.34 (1.28 to 1.41)	541 more per 1000 (517 more to 569 more)	⨁⨁◯◯ Low ^A,B
DCR	81	2676/3124(85.7), 2310/3101(74.5)	RR 1.12 (1.10 to 1.15)	834 more per 1000 (819 more to 857 more)	⨁⨁⨁◯ Moderate ^A
Survival Rate
1-year survival rate	9	258/386 (66.8), 190/385 (49.4)	RR 1.29 (1.13 to 1.48)	699 more per 1000 (628 more to 762 more)	⨁⨁⨁◯ Moderate ^C
2-year survival rate	3	54/103 (52.4), 37/101 (36.6)	RR 1.40 (1.03 to 1.91)	526 more per 1000 (387 more to 661 more)	⨁⨁⨁◯ Moderate ^A
3-year survival rate	5	90/167 (53.9), 56/165 (33.9)	RR 1.57 (1.23 to 2.00)	553 more per 1000 (438 more to 662 more)	⨁⨁⨁◯ Moderate ^A
5-year survival rate	1	8/26 (30.8), 6/26 (23.1)	RR 1.33 (0.54 to 3.31)	307 more per 1000 (114 more to 605 more)	⨁⨁◯◯ Low ^D,E
Overall survival	2	88 / 88	–	MD 4.22 higher (2.72 higher to 5.73 higher)	⨁⨁◯◯ Low ^F,G
Quality of Life Assessment
KPS score	22	797 / 797	–	MD 7.19 higher (5.84 higher to 8.54 higher)	⨁⨁◯◯ Low ^B,C
KPS improvement rate	37	715/1291 (55.4), 391/1278 (30.6)	RR 1.70 (1.55 to 1.85)	520 more per 1000 (476 more to 569 more)	⨁⨁◯◯ Low ^A,B
Adverse Drug Reactions
Myelosuppression	22	205/887 (23.1), 323/882 (36.6)	RR 0.66 (0.58 to 0.76)	242 fewer per 1000 (278 fewer to 212 fewer)	⨁⨁⨁◯ Moderate ^A
Neutropenia	42	500/1648 (30.3), 876/1645 (53.3)	RR 0.60 (0.54 to 0.66)	320 fewer per 1000 (351 fewer to 288 fewer)	⨁⨁◯◯ Low ^A,C
Anemia	18	185/692 (26.7), 303/692 (43.8)	RR 0.67 (0.59 to 0.76)	293 fewer per 1000 (333 fewer to 258 fewer)	⨁⨁⨁◯ Moderate ^A
Thrombocytopenia	38	295/1472 (20.0), 530/1473 (36.0)	RR 0.57 (0.51 to 0.64)	205 fewer per 1000 (230 fewer to 184 fewer)	⨁⨁⨁◯ Moderate ^A
Digestive symptoms	21	157/751 (20.9), 335/748 (44.8)	RR 0.49 (0.42 to 0.58)	219 fewer per 1000 (260 fewer to 188 fewer)	⨁⨁⨁◯ Moderate ^A
Nausea and vomiting	44	523/1767 (29.6), 951/1763 (53.9)	RR 0.56 (0.49 to 0.63)	302 fewer per 1000 (340 fewer to 264 fewer)	⨁⨁◯◯ Low ^A,C
Diarrhea	28	215/1111 (19.4), 444/1108 (40.1)	RR 0.52 (0.46 to 0.60)	208 fewer per 1000 (240 fewer to 184 fewer)	⨁⨁⨁◯ Moderate ^A
Hepatic dysfunction	27	185/1234 (15.0), 301/1231 (24.5)	RR 0.64 (0.55 to 0.74)	166 fewer per 1000 (192 fewer to 143 fewer)	⨁⨁⨁◯ Moderate ^A
Renal dysfunction	13	93/499 (18.6), 159/497 (32.0)	RR 0.64 (0.53 to 0.77)	205 fewer per 1000 (246 fewer to 170 fewer)	⨁⨁⨁◯ Moderate ^A
Neurotoxicity	32	247/1230 (20.1), 457/1184 (38.6)	RR 0.59 (0.53 to 0.67)	228 fewer per 1000 (259 fewer to 205 fewer)	⨁⨁◯◯ Low ^A,B
Oral mucositis	14	93/524 (17.7), 145/525 (27.6)	RR 0.68 (0.54 to 0.86)	188 fewer per 1000 (238 fewer to 149 fewer)	⨁⨁⨁◯ Moderate ^A

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CI, confidence interval; MD, mean difference, RR, risk ratio; Serious ^A, Although the results were statistically significant, the 95 % confidence intervals were wide and included the possibility of no effect, raising concerns about the precision of the results; Serious ^B, Possible publication bias; Serious ^C, Moderate heterogeneity (30 % ≤ I² ≤ 75 %); Serious ^D, The included study(ies) had a unclear risk of selection, performance biases; Serious ^E, The 95 % confidence interval overlapped with no effect; Serious ^F, Rob Risk of bias may influence the findings; Serious ^G, Substantial heterogeneity exists (I² > 75 %).

The analysis of tumor response showed that DCR was evaluated with ‘Moderate' certainty, while ORR was rated with ‘Low' certainty. The assessment of survival rates indicated that one- to three-year survival rates had ‘Moderate' certainty, whereas the five-year survival rate and OS were rated as ‘Low' certainty. The QoL assessment, using the KPS scale showed ‘Low' certainty. The certainty of evidence for ADRs varied: myelosuppression, anemia, thrombocytopenia, digestive symptoms, diarrhea, hepatic and renal dysfunction, and oral mucositis were evaluated with ‘Moderate' certainty, while neutropenia, nausea and vomiting, and neurotoxicity were rated with ‘Low' certainty.

4. Discussion

4.1. Summary of evidence

This systematic review and meta-analysis 101 RCTs including 7744 patients to evaluate the effects of combining HMs with chemotherapy on tumor response and survival rates in palliative patients with AGC. The included studies had a moderate to high risk of bias, particularly in allocation concealment and blinding. The combination therapy significantly improved tumor response rates (ORR and DCR) and 1- to 3-year survival rates. Furthermore, the combination therapy reduced various ADRs and improved QoL measures, such as KPS scores. The evidence of combination therapies' efficacy on the symptoms of AGC patients is limited. However, the results should be interpreted in cautious because the risk of bias of the included studies were high or moderate.

4.2. Applicability of evidence

Our findings suggest that integrating HMs with chemotherapy may be a potential treatment option for AGC, a disease that significantly affects patients' quality of life. The combined therapy of HMs with PC can yield significant outcomes through several mechanisms.

Firstly, this approach adopts a multi-pronged strategy against tumors, inhibiting tumor growth and enhancing tumor response by targeting various biological mechanisms of tumor cells simultaneously.119, 120, 121, 122 Secondly, HMs have the potential to suppress tumor growth and enhance the immune system, either by directly acting on tumor cells or by regulating their activities.¹²³ Moreover, HMs can mitigate the side effects of various chemotherapeutic agents used in tumor treatment and modulate the immune system to suppress tumor invasion.¹²⁴ Thirdly, HMs can improve the overall health status of patients and reduce resistance to anticancer therapy by providing tailored treatment based on individual constitutions and enhancing patients' constitutions and immune systems.¹²⁵

Clinically, the integration of HMs with standard chemotherapy regimens maybe not only improves tumor response but also enhances overall survival and quality of life by mitigating ADRs such as myelosuppression and gastrointestinal toxicity.

In addition, several HM frequently used in integrative oncology include Bazhen decoction,18, 19, 20, 21 Buzhong yiqi decoction,23, 24, 25, 26 Liujunzi decoction,72, 73, 74, 75 Xiangsha liujunzi decoction,92, 93, 94, 95, 96, 97 and Shenling baizhu powder.80, 81, 82 These HM are known for their spleen-strengthening properties, which are believed to support digestive health and vitality. By enhancing spleen function, they may improve nutrient absorption and energy distribution, particularly beneficial for cancer patients undergoing treatment, who often experience compromised energy levels and immune function.

Bazhen Decoction¹²⁶ has shown promise in inhibiting colorectal cancer by targeting key cancer-related genes and pathways, such as PI3K-AKT and P53. Additionally, it enhances T cell activity in the tumor environment, promoting an anti-tumor immune response. While these findings primarily relate to colorectal cancer, the mechanisms of action exhibited by Bazhen Decoction may also have implications for AGC. Given the shared pathways involved in tumorigenesis, further research is warranted to explore its potential therapeutic benefits for AGC, as it may similarly enhance immune response and inhibit tumor progression in this patient population.

Buzhong yiqi decoction¹²⁷^,¹²⁸ has been evaluated for its ability to improve immune function and safety when combined with the immune checkpoint inhibitor PD-L1 in tumor animal experiments. Reports also indicate its effectiveness in improving bowel movement. Its ability to enhance immune response and improve digestive health suggests that it may serve as a complementary treatment option for AGC, warranting further investigation in clinical settings.

Liujunzi decoction129, 130, 131 and Xiangsha liujunzi decoction¹³² have significant advantages in repairing gastric mucosa and enhancing the efficacy and eradication rate of Helicobacter pylori in chronic atrophic gastritis, thereby reducing recurrence rates. Given the established link between chronic atrophic gastritis and the development of gastric cancer, these decoctions may also play a critical role in preventing progression to AGC. Their ability to inhibit inflammation, regulate apoptosis, and suppress angiogenesis contributes to their therapeutic potential, suggesting that these herbal formulas could be instrumental in managing gastric health and mitigating the risk of AGC.

Samryeongbaekchul powder¹³³ contains active ingredients like quercetin, kaempferol, and β-sitosterol, which target key pathways and regulate tumor-related, metabolism-related, and inflammatory pathways. Given the significant role that inflammation and metabolic dysregulation play in the progression of AGC, the active compounds in Samryeongbaekchul powder may provide therapeutic benefits in this context. Molecular docking tests reveal that compounds such as pyrolignous acid, stigmasterol, and β-sitosterol bind effectively to target sites, indicating their potential to inhibit tumor growth and support cancer treatment. This suggests that integrating Samryeongbaekchul powder into treatment regimens could be beneficial for managing AGC.

This integrated approach offers a more effective treatment for tumors, reducing side effects and enhancing the quality of life for patients, especially those with inoperable AGC. This suggests a promising integration of traditional and modern therapies, contributing to a more holistic approach to cancer care.

4.3. Quality of the evidence

Although the outcomes of combined HMs and PC are generally positive, several methodological issues compromise their quality. Several studies demonstrated methodological limitations, particularly regarding detection and reporting biases, with only 25 % having protocols that matched their reported outcomes, indicating potential reporting biases. Nevertheless, the consistency of results across numerous studies strengthens the robustness of these findings.

The significant reductions in ADRs and improvements in QoL metrics provide compelling evidence for the benefits of this combination therapy. Despite methodological shortcomings, the consistent positive outcomes strengthen the reliability of these findings.

4.4. Agreements and disagreements with other reviews

The results of this systematic review are consistent with previous findings on the combination of HMs and chemotherapy in cancer treatment.134, 135, 136 This combination enhances tumor response and reduces side effects. Previous studies have focused on platinum-based chemotherapy combined with HMs, our study aggregated data on all PC treatments, particularly focusing on patients with inoperable AGC. This broader approach allowed us to collect extensive data, indicating that combining HMs with PC is both effectiveness and safety. Our frequency analysis highlights commonly used herbal medicines in AGC treatment, offering insights into their therapeutic roles. This combination not only enhances tumor response but also reduces toxicity, aligning with previous reviews

Despite these benefits, there are still knowledge gaps regarding the specific components and interactions of HMs with standard treatments. The meta-analysis revealed 101 different HMs, highlighting the heterogeneity in their compositions. However, despite the differences in each prescription's components, we observed that some formulations exhibited similar effects within the context of traditional medicine. Importantly, the absence of serious adverse effects in combination therapy shows the potential for such synergistic treatments.

In summary, integrating HMs with PC offers a promising and safety treatment pathway with potential to enhance future cancer therapies. However, more comprehensive and standardized research is necessary for broader clinical application.

4.5. Limitations of review

One limitation of this study is that many included studies compared chemotherapy alone to chemotherapy with HMs, often lacking double-blinding or placebo controls due to ethical concerns in life-threatening conditions. These concerns involve the ethical implications of assigning patients to potentially less effective treatments or sham controls.¹³⁷ Additionally, the clinical heterogeneity associated with herbal medicine and chemotherapy cannot be overlooked. Meta-analyses ideally require consistency in Population, Intervention, Comparison, and Outcome (PICO) criteria. However, our study included a diverse range of herbal prescriptions and chemotherapy regimens for AGC patients.

While this approach offered a comprehensive evaluation method and showed the effectiveness and safety of using HMs in AGC patients receiving PC, future studies should adopt a more focused approach. Specifically, conducting meta-analyses that concentrate on specific herbal prescriptions or chemotherapy regimens would provide more granular insights. Moreover, the heterogeneity of herbal formulations in the included studies adds further complexity to generalizing the results. Additionally, clinical studies on combining targeted therapies and immune checkpoint inhibitors with HMs are lacking, despite their increasing use in AGC patients.

4.6. Conclusion

The combination therapy may significantly improve tumor response, survival rates, and quality of life. Additionally, HMs enhanced the anti-cancer effects of PC and reduced side effects like myelosuppression, digestive symptoms, and neurotoxicity. These findings suggest that this combination therapy could be a valuable approach in integrative oncology. However, the methodological limitations emphasize the need for more rigorous studies to strengthen the evidence base.

CRediT authorship contribution statement

Dong-Hyeon Kim: Formal analysis, Investigation, Data curation, Writing – original draft, Visualization, Project administration. Soo-Dam Kim: Formal analysis, Investigation, Writing – original draft. Hyeong-Joon Jun: Software, Visualization. Eun-Bin Kwag: Validation, Investigation. Sang-Won Shin: Methodology, Writing – review & editing. Hwa-Seung Yoo: Methodology, Writing – review & editing. So-Jung Park: Conceptualization, Writing – review & editing, Supervision, Project administration, Funding acquisition.

Acknowledgments

Declaration of competing interest

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

This research was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number: RS-2020-KH093707 and RS-2023-KH139460).

Ethical statement

Not applicable.

Data availability

The data associated with this systematic review can be made available upon reasonable request to the corresponding author.

Deviation from the protocol

The original protocol specified the inclusion of patients undergoing “adjuvant chemotherapy after gastric cancer surgery.” However, we expanded the inclusion criteria to include patients with “inoperable AGC” to address the clinical relevance of palliative chemotherapy interventions for this group. This adjustment was made to better capture the target population most likely to benefit from the intervention. Patients with advanced gastric cancer represent a subgroup with more significant clinical needs, which aligns more closely with the primary objectives of our study.In addition, the term “Traditional Korean medicine” in the protocol has been specified further to “herbal medicine” to enhance the clarity and specificity of the intervention. This change ensures that the study accurately reflects the intervention being administered and avoids potential ambiguity regarding the scope of treatment.These protocol deviations were implemented after careful consideration and the preservation of study integrity.

This study builds upon findings presented in the author's dissertation, which was submitted to Daejeon University in partial fulfillment of the requirements for the Degree of Korean Medicine in 2024. The manuscript includes substantial revisions, additional analyses, and further discussions to expand upon the original work.

Footnotes

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.imr.2024.101098.

Appendix. Supplementary materials

mmc1.pdf^{(848.2KB, pdf)}

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

mmc1.pdf^{(848.2KB, pdf)}

Data Availability Statement

The data associated with this systematic review can be made available upon reasonable request to the corresponding author.

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PERMALINK

Effectiveness and safety of combined treatment with herbal medicines and palliative chemotherapy for advanced gastric cancer: A systematic review, and meta-analysis

Dong-Hyeon Kim

Soo-Dam Kim

Hyeong-Joon Jun

Eun-Bin Kwag

Sang-Won Shin

Hwa-Seung Yoo

So-Jung Park

Abstract

Background

Methods

Results

Conclusion

1. Introduction

2. Methods

2.1. Criteria for inclusion and exclusion

2.1.1. Study types

2.1.2. Participant types

2.1.3. Intervention types and controls

2.1.4. Outcome measures

2.2. Literature searches

2.3. Study selection

2.4. Data extraction

2.5. Risk of bias assessment of included studies

2.6. Data analysis

3. Results

3.1. Study selection

Fig. 1.

3.2. Study characteristics

Table 1.

3.3. Risk of bias of included studies

Fig. 2.

3.4. Intervention effects

3.4.1. Tumor response assessment

3.4.2. Survival rate assessment

3.4.3. QoL

3.4.4. Assessment of ADRs

Table 2.

3.5. Publication bias

3.6. Certainty of evidence assessment at grade system

Table 3.

4. Discussion

4.1. Summary of evidence

4.2. Applicability of evidence

4.3. Quality of the evidence

4.4. Agreements and disagreements with other reviews

4.5. Limitations of review

4.6. Conclusion

CRediT authorship contribution statement

Acknowledgments

Declaration of competing interest

Funding

Ethical statement

Data availability

Deviation from the protocol

Footnotes

Appendix. Supplementary materials

References

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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