Efficacy of Herbal Medicine Therapy Combined With Palliative Chemotherapy in Unresectable Advanced NSCLC: A Systematic Review and Meta-Analysis

Abstract

Background:

Lung cancer, a leading cause of mortality, is often complicated by severe treatment-related side effects. Traditional herbal medicine (THM), particularly Fuzheng-Based Qi and Yin Therapy (FBQYT), has emerged as a promising adjuvant therapy to mitigate these effects and enhance immune response. This meta-analysis evaluates the efficacy and safety of THM as an adjunct to palliative chemotherapy.

Methods:

A systematic search was conducted in PubMed, EMBASE, ScienceON, RISS, KMBASE, OASIS, Cochrane Library, KISS, CNKI, and CiNii up to April 2025. Outcomes included tumor response, quality of life (QoL), adverse drug reactions (ADRs), and tumor markers. Eighty randomized controlled trials (RCTs) involving stage III/IV lung cancer patients were analyzed using Review Manager Software 5.4.1.

Results:

Combining chemotherapy with THM significantly improved the objective response rate (ORR, RR 1.41) and disease control rate (DCR, RR 1.20). It also enhanced quality of life, increasing Karnofsky Performance Status (KPS) score (MD 8.53) and KPS improvement (RR 1.51), alongside improvements in Quality of Life Questionnaire-Core 30 (QLQ-C30) total score (MD 13.05). Tumor markers and most ADRs were reduced, except for neutropenia, liver injury, and diarrhea (P > .05). Survival rates, progression-free survival (PFS), and median survival time (MST) were higher in the THM group.

Conclusion:

Integrating THM with palliative chemotherapy enhances tumor response, QoL, and survival rates while reducing adverse effects. Further rigorous RCTs are needed to confirm these findings and address methodological limitations.

Registration: PROSPERO CRD 42024523418.

Keywords

non-small cell lung cancer traditional herbal medicine chemotherapy integrative oncology clinical evidence

Introduction

Lung cancer remains the leading cause of cancer-related mortality worldwide, accounting for 18.7% of all cancer deaths in 2022.¹ It is also the most commonly diagnosed cancer, broadly classified into non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC). NSCLC accounts for approximately 80% of cases and includes subtypes such as adenocarcinoma, squamous cell carcinoma, and large cell carcinoma. In contrast, SCLC accounts for 10% to 15% of cases.¹ Notably, early-stage NSCLC often presents with non-specific symptoms, and the limited sensitivity of current screening methods frequently leads to diagnosis at an advanced stage.² Treatment strategies for lung cancer, including chemotherapy, are selected based on the type of cancer, stage of the disease, and the patient’s overall health status. For NSCLC, treatment options vary depending on the stage of progression. In addition to chemotherapy and immunotherapy, localized treatments such as surgery and radiation therapy are also considered.³

Chemotherapy for advanced NSCLC (stage III or IV) is a systemic treatment that targets rapidly dividing cancer cells. Common chemotherapy regimens include platinum-based agents such as cisplatin and carboplatin, as well as non-platinum agents such as paclitaxel and docetaxel. However, these drugs are often associated with systemic side effects such as nausea, fatigue, and leukopenia.⁴ Immunotherapy, which enhances the immune system’s ability to target cancer cells, utilizes immune checkpoint inhibitors such as pembrolizumab and nivolumab. These agents block immune evasion mechanisms, allowing the immune system to target the tumor more effectively. However, immunotherapy can trigger immune-related adverse events, such as dermatitis, colitis, and pneumonitis.⁵

In cases of advanced or terminal lung cancer where curative treatment is not feasible, palliative chemotherapy is implemented to improve the quality of life and alleviate symptoms for cancer patients. This treatment aims to reduce tumor size, slow the progression of cancer, and extend survival. However, chemotherapy can also cause adverse effects on normal tissue cells, leading to undesirable reactions such as gastrointestinal disturbances, bone marrow suppression, and other side effects.⁶

To address the adverse effects of chemotherapy and improve therapeutic outcomes, traditional herbal medicine (THM) has gained attention as a complementary and alternative treatment for cancer. THM is widely used alongside chemotherapy, particularly in palliative care for terminal-stage lung cancer patients. Recent studies have shown that in cases of unresectable stage III and IV lung cancer, patients treated with THM in combination with chemotherapy experienced several benefits. These benefits included tumor size reduction, symptom improvement, enhanced quality of life, and fewer chemotherapy-related side effects compared to patients receiving chemotherapy alone.⁷ Additionally, patients in the integrative treatment group demonstrated extended survival time and overall better therapeutic responses.⁸ These findings suggest that THM may play a valuable role in enhancing the effectiveness and tolerability of chemotherapy in advanced lung cancer.

In this study, we introduce the term Fuzheng-Based Qi and Yin Therapy (FBQYT) to describe the THM regimen grounded in the principle of Fuzheng (supporting and reinforcing the body’s vital energy). This approach encompasses therapies aimed at “tonifying qi and nourishing yin” to address deficiencies and enhance overall vitality. The introduction of FBQYT provides a concise and precise term for referring to this therapeutic strategy throughout the study.⁹ This principle is particularly relevant in the context of terminal lung cancer, where patients often exhibit both qi and yin deficiency as a result of the advanced disease stage and the adverse effects of chemotherapy, such as fluid imbalance and malnutrition.¹⁰

Patients with a combined deficiency of Qi and Yin typically present with fatigue, shortness of breath, night sweating, dry mouth and throat, and a persistent dry cough with scanty sputum.⁹ These symptoms reflect a complex pattern of constitutional weakness, internal dryness, and impaired warming function, commonly observed in advanced stages of lung cancer or following intensive anticancer treatments.⁷

As the disease progresses and tumors metastasize, the depletion of qi, blood, yin, and yang becomes increasingly severe. In these cases, THM formulations grounded in the “Fuzheng” approach, including tonifying qi and nourishing yin, are frequently employed. Modern research has demonstrated that “fuzheng” therapy can inhibit tumor progression, alleviate chemotherapy-related side effects, and enhance patients’ quality of life.

This study aims to evaluate the efficacy and safety of integrating fuzheng-based therapies, particularly those focused on tonifying qi and nourishing yin, with palliative chemotherapy for unresectable advanced lung cancer. By assessing their effects on tumor reduction and survival, we aim to provide clinical evidence supporting the incorporation of THM into contemporary cancer treatment.

Methods

Study Design and Eligibility Criteria

This meta-analysis aimed to evaluate the efficacy and safety of integrating the FBQYT method of Traditional Asian Medicine (TAM) with palliative chemotherapy in patients with lung cancer. The study adhered to the PRISMA guidelines and was registered with PROSPERO (CRD42024523418).

Eligible studies included randomized controlled trials (RCTs) involving patients with stage III or IV lung cancer who were ineligible for surgical resection and were receiving palliative chemotherapy. Most trials employed standard platinum-based doublet chemotherapy, typically cisplatin or carboplatin in combination with paclitaxel or gemcitabine as widely recommended for advanced NSCLC. A few trials also included targeted therapies such as EGFR-TKIs; however, their limited number precluded meaningful subgroup analysis. Participants were assigned to 2 groups: one receiving a combination of TAM and palliative chemotherapy, and the other receiving palliative chemotherapy alone.

FBQYT-based interventions generally consisted of herbal decoctions containing key components such as Astragalus membranaceus, Atractylodes macrocephala, Poria cocos, and Ophiopogon japonicus. These formulations were typically administered orally as water-based decoctions, usually twice daily for durations ranging from 4 to 12 weeks, with total daily dosages between 100 and 300 g. The detailed compositions, dosages, and preparation methods of commonly used prescriptions are summarized in Supplemental Tables S1 to S3.

To ensure methodological rigor, non-randomized studies, observational designs, case reports, and studies with incomplete or inconsistent data were excluded. Meta-analysis was conducted only when at least 2 studies demonstrated sufficient homogeneity in participants, interventions, comparators, and outcomes based on predefined protocol criteria.

Identification Criteria for FBQYT Therapies

In this study, therapies were classified as FBQYT only when the original article explicitly stated that the intervention aimed to implement a “Fuzheng” strategy, or to “tonify qi” or “nourish yin.” Inclusion was strictly based on the authors’ theoretical description rather than on herbal composition alone. For example, even if a formulation contained frequently used herbs such as Astragalus membranaceus, Atractylodes macrocephala, or Poria cocos, it was not considered FBQYT unless the study clearly articulated its alignment with the Fuzheng principle or a qi/yin deficiency pattern. Two independent reviewers assessed each study’s textual description to determine whether the therapeutic intent met the FBQYT framework. Discrepancies were resolved through discussion, ensuring consistent application of this definition across all included trials.

Search Strategy

The literature search was conducted using international databases, including PubMed, EMBASE, ScienceON, RISS, KMBASE, OASIS, Cochrane Library, KISS, CNKI, and CiNii. Studies published in English, Chinese, Japanese, and Korean were included. The search period extended up to April 2025. A detailed search strategy for the PubMed database is provided in Table S4 of the Supplemental Material. The search was conducted exclusively using electronic sources.

Study Selection

Search results were compiled using EndNote version 20, and duplicates were removed. Two independent reviewers (KJL and JHK) screened titles and abstracts to exclude studies that did not meet the inclusion criteria. Full texts of potentially eligible articles were assessed, and inclusion decisions were finalized through mutual agreement. In cases of disagreement, a third reviewer (DHK) resolved the issue. All reasons for study exclusion were documented.

Data Extraction

Data extraction was performed independently by 2 reviewers (KJL and JHK). Extracted data included the first author, study period, publication year, participant characteristics, comparisons, details of interventions in both groups, outcomes, and reported adverse events. In cases of missing or unclear data, the reviewers consulted each other and contacted the corresponding author via email for clarification.

Quality Assessment

To evaluate the methodological quality of the included studies, we used the Cochrane Risk of Bias (ROB) tool.¹¹ Two independent reviewers (KJL and JHK) assessed the risk of bias across 7 domains: random sequence generation, allocation concealment, blinding of participants and personnel, blinding of outcome assessment, incomplete outcome data, selective reporting, and other potential sources of bias. Disagreements were resolved through discussion with a third reviewer (DHK).

Additionally, we assessed the overall certainty of the evidence using the GRADE system, which classifies the quality of evidence into 4 levels: high, moderate, low, and very low. By default, randomized controlled trials were considered high-quality evidence but could be downgraded based on serious limitations such as risk of bias, inconsistency, indirectness, imprecision, or publication bias. Conversely, evidence could be upgraded in cases of large effect sizes or the presence of a dose-response gradient. A GRADE evidence profile was developed for each outcome, providing a transparent and systematic assessment of the strength of evidence and highlighting areas where further research may be warranted.

Outcome Measures

The primary outcome of this study was the objective response rate (ORR), defined as the proportion of patients who achieved either a complete response (CR) or partial response (PR). Secondary outcomes included the disease control rate (DCR), quality of life (QoL), adverse drug reactions (ADRs), tumor marker levels, and long-term survival outcomes, such as progression-free survival (PFS), median survival time (MST), and 1 to 3-year survival rates. These outcomes were selected to provide a comprehensive evaluation of the clinical efficacy and safety profile of the integrative therapeutic approach.

Statistical Analysis

We used Review Manager Software 5.4.1 to conduct the meta-analyses.¹² For dichotomous outcomes, we calculated risk ratios (RRs) with 95% confidence intervals (CIs), and for continuous outcomes measured on the same scale, mean differences (MDs) with 95% CIs were used. Heterogeneity was assessed using Higgins’ I² statistic and the Chi-squared (Chi²) test. An I² value greater than 50% was considered to indicate substantial heterogeneity. In such cases, we performed subgroup analyses based on predefined variables such as chemotherapy regimen, type of herbal medicine, and population characteristics. We also conducted sensitivity analyses by excluding studies with a high risk of bias or small sample sizes to assess the robustness of the results. Since substantial heterogeneity was anticipated due to variations in herbal composition, treatment duration, and chemotherapy regimens, a random-effects model was applied throughout all analyses regardless of I² values.

Frequency Analysis

To identify the predominant herbal interventions used in the treatment of lung cancer, we conducted a frequency analysis of the included studies. This analysis aimed to determine the most commonly used herbs by counting the frequency of their occurrences across all included interventions.

Network Analysis Method

Based on the frequency analysis results, we selected herbs with an occurrence frequency ≥4.81, representing the average across all listed herbs. For each herbal medicine (HM) in the systematic review, pairwise combinations of constituent herbs were generated and their frequencies calculated. Only combinations involving the selected high-frequency herbs were retained for network analysis. The extracted herb-pair data were input into Cytoscape software (version 3.10.2) to construct a visualized network representing co-occurrence and connectivity patterns among the herbs. In the resulting network, circular nodes represented individual herbs, while edges represented co-occurrences between herbs within each HM. Node size reflected the frequency of herb use, with larger nodes indicating more commonly used herbs. Edge thickness (weight) corresponded to the frequency of herb-pair co-occurrence, reflecting the strength of association.

To enhance interpretability, the yFiles Circular Layout was applied to arrange nodes in a circular pattern, and the Prefuse Force Directed Layout was used to emphasize stronger associations by drawing related herbs closer together. Herbs located near the center of the network were regarded as more influential due to their higher frequency and connectivity, indicating their key roles in the overall herbal therapeutic framework.

Results

Study Selection

An initial search across 10 electronic databases yielded 2924 records. After removing 701 duplicates, 2223 records remained for title and abstract screening. Of these, 1589 were excluded based on title and abstract review, leaving 634 articles for full-text assessment. Upon applying the eligibility criteria, 553 studies were excluded for the following reasons: 92 did not target the appropriate population, 115 were not randomized controlled trials or were study protocols, 41 involved inappropriate interventions, and 305 reported outcomes that did not meet inclusion criteria. Consequently, 81 randomized controlled trials were included in the final analysis (Figure 1).

Figure 1.

PRISMA flowchart.

Study Characteristics

This meta-analysis includes 81 randomized controlled trials published up to 2025, involving a total of 5955 patients diagnosed with lung cancer at TNM stages III or IV.^13
-93 The experimental groups consisted of patients who received palliative chemotherapy in combination with FBQYT, a form of TAM, as an adjunctive treatment. All patients were inoperable and not eligible for surgical resection. The control groups received standard chemotherapy regimens, including GP, DP, EP, and others (Table 1). A total of 101 chemotherapy regimens were reported across the 81 trials. The most frequently used combinations were NP (31.7%), GP (31.7%), TP (23.2%), and DP (13.4%). Less frequently used regimens, such as EP, PC, and Apatinib, were reported only once and were collectively categorized as “Others” (Supplemental Table S5). The treatment durations ranged from 1 week to 10 years. The primary outcomes assessed were the ORR and DCR. ORR, comprising complete and partial responses, measures the effectiveness of treatment in reducing tumor size. DCR includes complete response, partial response, and stable disease, providing a broader assessment of treatment efficacy. Secondary outcomes included QoL, ADRs, tumor marker levels, and survival rates. These outcomes offer a comprehensive evaluation of both the clinical efficacy and safety of combining FBQYT with chemotherapy in lung cancer treatment.

Table 1.

Characteristics of Included Trials.

Study	Sample size/Stage	Intervention	Control	Duration	Outcome measures
Hu (2013)¹³	E:32, C:28/Ⅲ-Ⅳ	BaiLongLingSha Decoction	GP	12 wk	ORR, DCR, KPS improvement rate, ADRs
Shao (2016)¹⁴	E:30, C:30/ⅢB-Ⅳ	BaiHeGuJin Decoction	GP or DP (Carboplatin)	8 wk	ORR, DCR, ADRs
Li (2016a)¹⁵	E:39, C:39/ⅢA,ⅢB,Ⅳ	Basic Anticancer Formula	TP	12 wk	ORR, DCR, QLQ-C30, Survival rate
Rong (2014)¹⁶	E:100, C:97/Ⅲ-Ⅳ	BuFeiXiaoJie Formula	DP or TP	8 wk	ORR, DCR, KPS improvement rate, Tumor markers (CEA, CYFRA21-L), Survival rate, ADRs, MST(m)
Gong (2020)¹⁷	E:63, C:63/Ⅲ-Ⅳ	BuYuan Decoction	GP	4 wk	ADRs
Wang (2015)¹⁸	E:30, C:30/ⅢB-Ⅳ	FeiFuKang Formula	Chemo + Radio treatment	8 wk	ORR, DCR, Survival rate, MST(m)
Huang (2007)¹⁹	E:23, C:22/ⅢA,ⅢB,Ⅳ	FeiJi Formula	NP	8 wk	ORR, DCR, Tumor markers (VEGF)
Guo (2017)²⁰	E:29, C:32/ⅢB, Ⅳ	FeiYanNing Formula	NP, TP, GP + Placebo	8 wk	FACT-L
Xu (2007)²¹	E:60, C:56/ⅢA, ⅢB, Ⅳ	FeiYanNing Formula	NP, GP, MVP	3 y	Tumor markers (CEA,CYFRA21-L, VEGF), ADRs
Zhang (2013)²²	E:30, C:28/NR	FuZheng Formula	GP	8 wk	ORR, DCR, KPS improvement rate
Liu (2015)²³	E:30, C:32/ⅢA,ⅢB,Ⅳ	FuZhengFangAi Formula	TP,DP (Dexamethasone)	8 wk	KPS, ADRs
Gu (2014)²⁴	E:25, C:25/ⅢB-Ⅳ	FuZhengFeiLiu Formula	DP	6 wk	ORR, DCR, FACT-L
Bu (2014)²⁵	E:30, C:30/Ⅲ-Ⅳ	FuZhengHuaTan Formula	GP	8 wk	KPS, ADR
Li (2002)²⁶	E:57, C:55/Ⅲ-Ⅳ	FuZhengJieDu Formula	MVP	6-8 wk	ORR, DCR, KPS, ADRs, MST(m), PFS
Yang (2016)²⁷	E:30, C:30/Ⅲ-Ⅳ	FuZhengJieDu QuYu	NP, TP, GP, DP	>8 wk	ADRs
Wang (2021)²⁸	E:40, C:40/ⅢB, Ⅳ	FuZhengJieDuKangAi Formula	GP, AP	6 wk	KPS, ADRs
Wang (2013)²⁹	E:39, C:37/Ⅳ	FuZhengKangAi Decoction	GP, NP, TP	12 wk	QLQ-C30, PFS
Yang (2018)³⁰	E:23, C:22/ⅢB-Ⅳ	FuZhengKangAi Formula	Gefitinib	6-7 wk	ORR, DCR, ADRs, MST(m), PFS
Li (2008)³¹	E:30, C:30/NA	FuZhengKangLi Deoction	NP	8 wk	ORR, DCR, ADRs
Zhang (2019)³²	E:30, C:30/Ⅳ	FuZhengKangYan Formula	Gefitinib	2 y	ORR, DCR, KPS, PFS, ADRs
Fang (2013)³³	E:45, C:45/Ⅳ	FuZhengQuXie Formula	TP, GP	6 wk	ORR, KPS improvement rate, ADRs
Xiao (2017)³⁴	E:48, C:48/Ⅲ-Ⅳ	FuZhengSanJie Formula	GP	6 wk	ORR, DCR, KPS improvement rate, ADR
Kong (2016)³⁵	E:50, C:50/ⅢA,ⅢB,Ⅳ	FuZhengYiLiu Decoction	NP	6 wk	ADR
Han (2012)³⁶	E:35, C:25/ⅢB, Ⅳ	FuZhengZengXiao Decoction	DP	3 wk	ORR, DCR
Yang (2015)³⁷	E:42, C:42/Ⅲ-Ⅳ	GuBenJieDu Decoction	Dexamethasone, Cimetidine, Promethazine	12 wk	DCR, KPS
Chen (2020)³⁸	E:34, C:34/Ⅲ-Ⅳ	GuFeiXiaoJiYin Formula	Vincristine+Cisplatin	12 wk	ORR, DCR, Tumor markers (VEGF), ADRs
Gao (2016)³⁹	E:19, C:19/ⅢB-Ⅳ	HuangQiDanggui Decoction	GP or NP	6 wk	ADRs
An (2016)⁴⁰	E:30, C:30/Ⅲ-Ⅳ	JianPiYiShen Decoction	NP	3 wk	ORR, DCR, KPS improvement rate, ADRs
Zhang (2016)⁴¹	E:58, C:58/ⅢB-Ⅳ	JianPiYiShen Decoction	NP	3 wk	KPS improvement rate
Zhang (2018)⁴²	E:58, C:58/Ⅲ-Ⅳ	JianPiYiShenBuXue Decoction	TP	6 wk	ORR, DCR, Tumor markers (CEA, CYFRA21-L), ADRs
Wang (2014)⁴³	E:25, C:25/NA	JianPiRunFeiJieDu Decoction	NP	6 wk	ORR, DCR, KPS improvement rate
Gong (2018)⁴⁴	E:131, C:108/ⅢB-Ⅳ	KangLiuZengXiao, FeiYanNing Decoction	NP + Placebo (JuPiZhuRu, Symptom-Focused Decoction)	10 y	Survival rate, MST(m)
Wu (2010)⁴⁵	E:32, C:29/ⅢA, ⅢB,Ⅳ	KangLiuZengXiao Formula	NP	8 wk	ORR, DCR, Tumor markers (CEA, CYFRA21-L, VEGF), MST(m), ADRs
Yan (2011)⁴⁶	E:37, C:37/Ⅲ-Ⅳ	KangLiuZengXiao Formula	NP	8 wk	ORR, DCR, KPS improvement rate, Tumor markers (CEA, CYFRA21-L)
Zhu (2011)⁴⁷	E:32, C:31/Ⅲ-Ⅳ	KangLiuZengXiao Formula	NP	8 wk	KPS improvement rate, ADRs
Yuan (2013)⁴⁸	E:60, C:60/Ⅲ,Ⅳ	LiFeiXiaoAi Decoction	TP, NP, GP	6 wk	DCR, KPS, 1 y
You (2016)⁴⁹	E:49, C:50/Ⅲ-Ⅳ	LiuJunQuTanJieDu Decoction	GP	6 wk	ORR, DCR, KPS improvement rate, Tumor markers (VEGF), ADRs
Xia (2015)⁵⁰	E:10, C:9/ⅢB-Ⅳ	MaiMenDong Decoction	EP	12 wk	ORR, DCR, ADRs
Xu (2014)⁵¹	E:30, C:30/ⅢA, ⅢB, Ⅳ	PeiTuJieDu Decoction	PC	12 wk	Tumor markers (CEA, VEGF), ADRs
Zhang (2014)⁵²	E:40, C:40/ⅢB-Ⅳ	PeiTuShengJin Formula	Chemotherapy	1 wk	ORR, DCR, KPS improvement rate, ADRs
Liu (2016)⁵³	E:45, C:45/Ⅲ-Ⅳ	QiangShen TianJing Formula	GP or NP	12 wk	ADR
Lu (2016)⁵⁴	E:30, C:30/ⅢB,Ⅳ	QingFeiSanJie Decoction	TP	6 wk	ORR, DCR, ADRs
Xie (2016)⁵⁵	E:32, C:32/ⅢB,Ⅳ	QingFeiRuanJian Decoction	NA	4 wk	ORR, DCR, KPS, Survival rate
Yan (2016)⁵⁶	E:36, C:36/ⅢB-Ⅳ	QingFeiXiaoLiu	NP	6 wk	ORR, DCR, KPS, ADRs
Wang (2016a)⁵⁷	E:25, C:25/Ⅲ-Ⅳ	QiYuWeiRui Decoction	GP	6 wk	KPS, ADRs
Wang (2016b)⁵⁸	E:30, C:30/NA	ShengMaiYin and others	TP	6 wk	ORR, DCR, Survival rate
He (2021)⁵⁹	E:52, C:52/ⅢA,ⅢB,Ⅳ	ShaShenMaiDong Decoction	Nutritional support	4 wk	KPS
Li (2015a)⁶⁰	E:50, C:50/Na	ShaShenMaiDong Decoction	DP, GP	6 wk	KPS, KPS improvement rate
Xiao (2011)⁶¹	E:22, C:21/Ⅲ-Ⅳ	ShaShenMaiDong Decoction	TP	8 wk	QLQ-C30, ADRs
Wang (2016c)⁶²	E:53, C:53/ⅢB,Ⅳ	ShaShenMaiDong Decoction SiJunZi Decoction	GP	12 wk	ADRs
Huang (2015)⁶³	E:35, C:35/Ⅲ-Ⅳ	ShenYiSui Formula	DP	3 wk	ORR, DCR
Sun (2006)⁶⁴	E:54, C:61/NA	ShenYi Capsule	NP	12 wk	KPS
Li (2016b)⁶⁵	E:18, C:20/Ⅳ	ShenQiSanDou Decoction	TP	4 wk	KPS improvement rate, ADRs
Sun (2016)⁶⁶	E:43, C:43/ⅢB-Ⅳ	ShenQiFuZheng Decoction	NP	16 wk	ORR, DCR, KPS
Xu (2016)⁶⁷	E:57, C:55/ⅢB-Ⅳ	ShenQiFuZheng Decoction	GP	2 wk	ORR, DCR, KPS improvement rate, ADRs
Wu (2019)⁶⁸	E:82, C:81/Ⅱ, IIIA, IIIB, Ⅳ	ShengXue Formula	Cisplatin	12 wk	ORR, DCR, QLQ-C30
Pang (2011)⁶⁹	E:15, C:16/ⅢB,Ⅳ	XiaoLiu Decoction	NP	6-8 wk	KPS improvement rate
Sun (2009)⁷⁰	E:20, C:20/ⅢA,ⅢB,Ⅳ	XiaoLiuBaoFeiWan	NP	12 wk	FACT-L
Li (2017)⁷¹	E:18, C:20/ⅢA,ⅢB,Ⅳ	XiaoYan Decoction	Apatinib	12 wk	ORR, DCR, ADR
Zhu (2018)⁷²	E:37, C:35/Ⅲ,Ⅳ	XiaoYan Decoction	DP	9 wk	KPS, Survival rate, MST(m)
Xiao (2015)⁷³	E:37, C:37/ⅢB-Ⅳ	XianYu Decoction, SiJunZi Decoction	GP	6 wk	ORR, DCR, KPS improvement rate
Bu (2016)⁷⁴	E:25, C:25/ⅢB, Ⅳ	YiQiBuFei, HuaTanSanJie Decoction	TP	6 wk	ORR, DCR
Xiao (2016)⁷⁵	E:48, C:48/ⅢB-Ⅳ	YiQiBuShenFu Formula	GP	12 wk	ORR, DCR, KPS improvement rate
Zheng (2016)⁷⁶	E:44, C:43/Ⅲ-Ⅳ	YiQiChuPi Formula	GP, DP, TP	12 wk	ORR, DCR
Wang (2019)⁷⁷	E:40, C:40/Ⅲ-Ⅳ	YiQiGuBenXiaoAi Formula	NP, PT, PD, PG	3 wk	KPS improvement rate
Liu (2000)⁷⁸	E:56, C:34/Ⅲ-Ⅳ	YiQiHuoXue Formula	CE, CAP, MAF	3 wk	ORR, DCR
Zhao (2012)⁷⁹	E:31, C:30/Ⅲ-Ⅳ	YiQiHuoXueTongLuo Decoction	Chemotherapy	8 wk	ORR, DCR, KPS, ADRs
Zhou (2016)⁸⁰	E:47, C:48/ⅢA, ⅢB, Ⅳ	YiQiKangAi Decoction	TP	3 wk	Survival rate, MST(m)
Huang (2014)⁸¹	E:33, C:30/ⅢA,ⅢB,Ⅳ	YiQiQingFei Decoction	Gemcitabine	8 wk	ADRs
Liu (2013)⁸²	E:30, C:32/ⅢA,ⅢB,Ⅳ	YiQiQingFei Decoction	NP	8 wk	KPS
Li (2015b)⁸³	E:30, C:30/Ⅲ,Ⅳ	YiQiXiaoZheng Formula	Symptomatic treatment	4 wk	KPS, PFS
Liang (2022)⁸⁴	E:40, C:40/Ⅲ-Ⅳ	YiQiYangXue Decoction	GP	9 wk	ORR, DCR, ADRs
Jiang (2013)⁸⁵	E:30, C:30/Ⅲ-Ⅳ	YiQiYangYin Formula	DP or GP	6 wk	ORR, DCR, KPS improvement rate
Wang (2018)⁸⁶	E:33, C:30/ⅢA-Ⅳ	YiQiYangYin Formula	G, T, D	24 wk	KPS improvement rate, ADRs
Zhou (2003)⁸⁷	E:46, C:45/Ⅲ, Ⅳ	YiQiYangYin Formula	GP	16-24 wk	ORR, KPS improvement rate, Survival rate
Cheng (2011)⁸⁸	E:21, C:21/NA	YiQiYangYin Formula	NP	16-24 wk	ORR
Li (2013)⁸⁹	E:29, C:28/ⅢB-Ⅳ	YiQiYangYin Formula	TP	6 wk	ORR, DCR, KPS improvement rate
Zhu (2016)⁹⁰	E:41, C:41/ⅢB,Ⅳ	YiQiYangYin Formula	TP	24 wk	QLQ-C30, ADRs
Ye (2011)⁹¹	E:20, C:20/NA	YiQiYangYin,QingReJieDu Method	NP	NA	ORR, DCR, KPS, Tumor marker (CEA)
Song (2016)⁹²	E:30, C:30/Ⅲ-Ⅳ	YiQiYangYinQingFei Method	TP	3 wk	KPS
Ding (2024)⁹³	E:36, C:36/Ⅳ	ZhiGanCao Decoction	PD-1	12 wk	ORR, KPS, Tumor marker (CEA), ADRs

Abbreviation: NP, Vinorelbine, Cisplatin; TP, Paclitaxel, Cisplatin; GP, Gemcitabine, Cisplatin; DP, Docetaxel, Cisplatin; MVP, Mitomycin, Vinblastine, Cisplatin; CE, Cyclophosphamide, Epirubicin; CAP, Cyclophosphamide, Adriamycin, Prednisone; MAF, Methotrexate, Doxorubicin, 5-Fluorourac; EP, Etoposide, Cisplatin; DCCRT, Definitive Concurrent Chemoradiotherap.

Risk of Bias in Included Trials

According to the Cochrane Risk of Bias tool, the included trials generally exhibited a moderate to unclear risk of bias due to limited methodological reporting (Figure 2). Most studies adequately reported random sequence generation; however, 2 trials^36,78 were rated as high risk in this domain. Allocation concealment was not reported in 32 trials,^{14,18,22,25,27
-29,31,33,35,36,39
-41,48
-50,52,53,57,62,64,66,67,74,78,85,87,90
-93} resulting in 31 being judged as unclear risk and 1 as high risk.³⁶ Blinding of participants, personnel, and outcome assessors was generally not feasible, as TAM was administered exclusively to the intervention group. However, 3 studies^20,32,86 employed a placebo and thus allowed for partial blinding. Incomplete outcome data was rated as unclear in 19 studies^{16,20,29,35,45,47,49,50,61,71,72,76,79
-82,86,87,89} due to imbalance in participant numbers, and as high risk in 12 studies^{13,19,21,22,26,36,44,55,64,67,69,78}due to unexplained differences involving more than 4 participants. Selective reporting bias was generally judged as unclear; however, 8 studies^{13,17,20,30,43,74,86,93} were rated as low risk due to the availability of study protocols and ethical approval. Other biases were identified in 3 studies: 1 as high risk⁴⁵ and 2 as unclear^27,60 due to reporting errors and insufficient methodological detail (Figure 3).

Figure 2.

Risk of bias summary.

Figure 3.

Risk of bias graph.

Primary Outcome

Tumor Response Assessment

A comprehensive review of 46 and 44 studies demonstrated a statistically significant increase in both ORR^{13
-16,18,19,22,24,26,30
-34,36,38,40,42,43,45,46,49,50,52,54
-56,62,63,66
-68,71,73
-76,78,79,84,85,87
-89,91,93} and DCR^{13
-16,18,19,22,24,26,30
-32,34,36
-38,40,42,43,45,46,48
-50,52,54
-56,62,63,66
-68,71,73
-76,78,79,84,85,89,91} for patients receiving a combination of THM and chemotherapy compared to those receiving chemotherapy alone. The results showed a relative risk (RR; 1.41, 95% CI [1.30, 1.52], I² = 0%, n = 3294) for ORR, and a RR (1.20, 95% CI [1.15, 1.25], I² = 26%, n = 3213) for DCR (Figures 4 and 5).

Figure 4.

ORR of FBQYT method THM + chemotherapy.

Figure 5.

DCR of FBQYT method THM + chemotherapy.

Secondary Outcomes

Quality of Life

The Karnofsky Performance Status (KPS) score, based on 21 studies^{23,25,26,28,32,37,48,55
-57,59,60,64,66,72,79,82,83,91
-93} and KPS improvement was based on 23 studies^{13,16,22,33,34,40
,41,43,46,47
,49,52,65,67
,69,73,75
,77,83,85-87,89} were assessed, showing a significantly higher enhancement in the group receiving both THM and chemotherapy compared to the chemotherapy-only group. The KPS score was (MD 8.53), and the KPS improvement was (MD 1.51). Both outcomes were statistically significant (P < .05; Figures 6 and 7). For the FACT-L score, as reported in 3 studies^20,24,70 no significant improvement was observed in Physical Well-Being (PWB, MD 4.68), Social Well-Being (SWB, MD 1.30, 3 trials), Emotional Well-Being (EWB, MD 2.78, 3 trials), Functional Well-Being (FWB, MD 7.38, 3 trials), and Lung Cancer Subscale (LCS, MD 8.28, 3 trials), Total score (MD 16.70, 2 trials)^20,24 with P > .05 for all subscales. In the QLQ-C30 functional scales, based on 5 studies,^{15,29,61,68,90} significant improvement was seen in Physical Functioning (PF, MD 5.17, 5 trials), Role Functioning (RF, MD 8.95, 5 trials), Emotional Functioning (EF, MD 8.85, 5 trials), and Social Functioning (SF, MD 5.87, 4 trials),^15,29,61,90 Total (MD 13.05, 3 trials)^15,29,61 (P < .05), while Cognitive Functioning (CF, MD 5.56, 5 trials) showed no significant improvement (P > .05). In the symptom scales, based on 3 studies,^15,29,61 significant improvement was observed in Fatigue (MD −17.79), Nausea and Vomiting (MD −8.02), Dyspnea (MD −7.11), Insomnia (MD −12.06), Appetite Loss (MD −13.04), and Constipation (MD −6.74) (P < .05), while Pain (MD −4.39), Diarrhea (MD −2.84), and Financial Difficulties (MD −2.96) showed no significant improvement (P > .05; Table 2).

Figure 6.

KPS Score of FBQYT method THM + chemotherapy.

Figure 7.

KPS improvement rate of FBQYT method THM + chemotherapy.

Table 2.

QLQ-C30 and FACT-L of FBQYT Methods THM + Chemotherapy.

QLQ-C30	Studies	Participants	Risk ratio (95% CI)	P-value	Study ID references
QLQ-C30	Studies	Participants	Random effects model	P-value	Study ID references
Physical functioning	5	395	RR 5.17, 95% CI [0.24, 10.09], I² = 89%	.04*	Li (2016a), Wang (2013), Wu (2019), Xiao (2011), Zhu (2016)
Role functioning	5	395	RR 8.95, 95% CI [1.73, 16.18], I² = 94%	.02	Li (2016a), Wang (2013), Wu (2019), Xiao (2011), Zhu (2016)
Emotional functioning	5	395	RR 8.85, 95% CI [2.47, 15.22], I² = 91%	.007***	Li (2016a), Wang (2013), Wu (2019), Xiao (2011), Zhu (2016)
Cognitive functioning	5	395	RR 5.56, 95% CI [−0.09, 11.21], I² = 88%	.05	Li (2016a), Wang (2013), Wu (2019), Xiao (2011), Zhu (2016)
Social functioning	4	279	RR 5.87, 95% CI [−0.24, 11.98], I² = 73%	.06	Li (2016a), Wang (2013), Xiao (2011), Zhu (2016)
Quality of life total	3	197	RR 13.05, 95% CI [8.79, 17.30], I² = 53%	<.00001***	Li (2016a), Wang (2013), Xiao (2011)
Fatigue	3	197	RR −17.79, 95% CI [−23.98, −11.60], I² = 49%	<.00001***	Li (2016a), Wang (2013), Xiao (2011)
Nausea and vomiting	3	197	RR −8.02, 95% CI [−15.85, −0.20], I² = 85%	.04*	Li (2016a), Wang (2013), Xiao (2011)
Pain	3	197	RR −4.39, 95% CI [−11.06, 2.27], I² = 67%	.20	Li (2016a), Wang (2013), Xiao (2011)
Dyspnea	3	197	RR −7.11, 95% CI [−12.56,−1.66], I² = 36%	.01	Li (2016a), Wang (2013), Xiao (2011)
Sleep	3	197	RR −12.06, 95% CI [−20.23,−3.90], I² = 71%	.004**	Li (2016a), Wang (2013), Xiao (2011)
Appetite loss	3	197	RR −13.04, 95% CI [−21.52, −4.55], I² = 80%	.003**	Li (2016a), Wang (2013), Xiao (2011)
Constipation	3	197	RR −6.74, 95% CI [−12.49, −0.98], I² = 49%	.02	Li (2016a), Wang (2013), Xiao (2011),
Diarrhea	3	197	RR −2.84, 95% CI [−8.10, 2.41], I² = 58%	.29	Li (2016a), Wang (2013), Xiao (2011)
Financial difficulties	3	197	RR −2.96, 95% CI [−8.23, 2.32], I² = 80%	.27	Li (2016a), Wang (2013), Xiao (2011)
FACT-L
Physical well-being	3	151	RR 4.68, 95% CI [−0.43, 9.79], I² = 80%	.07	Gu (2014), Guo (2017), Sun (2009)
Social well-being	3	151	RR 1.30, 95% CI [−0.29, 2.90], I² = 86%	.11	Gu (2014), Guo (2017), Sun (2009)
Emotional well-being	3	151	RR 2.78, 95% CI [−0.85, 6.42], I² = 97%	.13	Gu (2014), Guo (2017), Sun (2009)
Functional well-being	3	151	RR 7.38, 95% CI [−1.73, 16.48], I² = 99%	.11	Gu (2014), Guo (2017), Sun (2009)
Lung Cancer Subscale	3	151	RR 8.28, 95% CI [−2.22, 18.78], I² = 80%	.12	Gu (2014), Guo (2017), Sun (2009)
Total	2	111	RR 16.70, 95% CI [−10.02, 43.41], I² = 94%	.22	Gu (2014), Guo (2017)

P < .05, **P < .01, ***P < .001.

Tumor Marker Level

In the THM plus chemotherapy group, there was a greater decrease in tumor markers compared to the chemotherapy-alone group. Specifically, CEA levels (MD −7.34, 8 trials),^{16,21,42,45,46,51,91,93} CYFRA21-1 levels (MD −1.55, 5 trials),^{16,21,42,45,46} and VEGF levels (MD −17.71, 6 trials)^{19,21,38,45,49,51} decreased. All of these reductions were statistically significant, with P < .05 for all (Table 3).

Table 3.

Tumor Markers of FBQYT Methods THM + Chemotherapy.

Tumor markers	Studies	Participants	Mean difference (95% CI)	P-value	Study ID references
Tumor markers	Studies	Participants	Random effects model	P-value	Study ID references
CEA	8	736	RR −7.34, 95% CI [−11.33, −3.36], I² = 91%	<.0001***	Rong (2014), Wu (2010), Xu (2007), Xu (2014), Yan (2011), Ye (2011), Zhang (2018), Ding (2024)
CYFRA21-L	5	564	RR −1.55, 56% CI [−2.13, −0.97], I² = 56%	<.00001***	Rong (2014), Wu (2010), Xu (2007), Yan (2011), Zhang (2018)
VEGF	6	564	RR −17.71, 95% CI [−33.14, −2.28], I² = 84%	.02*	Chen (2020), Huang (2007), Wu (2010), Xu (2007), Xu (2014), You (2016)

P < .05, ***P < .001.

Adverse Drug Reactions Assessment

The findings from the meta-analysis revealed that the group receiving both THM and chemotherapy had a reduced likelihood of experiencing adverse drug reactions compared to the chemotherapy-only group. Significant reductions were observed in the incidence of myelosuppression (RR 0.46, 6 trials),^{27,35,45,58,65,66} leukocyte reduction (RR 0.59, 28 trials),^{13,14,16,21,23,26
-28,31,33,38
-40,42,47,49
-52,54,56
-58,67,81,84,86,90} platelet reduction (RR 0.51, 20 trials),^{16,21,23,26
-28,31,33,38
-40,47,49,52,57,58,67,79,81,90} hemoglobin reduction (RR 0.51, 14 trials),^{16,26,28,33,38,39,42,47,49,51,52,57,84,86} renal injury (RR 0.33, 2 trials),^16,28 nausea and vomiting (RR 0.46, 20 trials),^{17,21,23,25,26,31
-33,40,51
-54,56,57,61,67,79,81,90} neurotoxicity (RR 0.48, 5 trials),^{52,54,57,71,84} and gastrointestinal symptoms (RR 0.52, 14 trials),^{14,16,17,30,34,38,42,45,49,50,58,65,66,84} all with P < .05. No significant differences were found for neutropenia (RR 0.38, 4 trials),^27,47,52,86 liver injury (RR 0.76, 10 trials),^{16,21,28,32,42,51,52,57,90,93} and diarrhea (RR 0.55, 6 trials),^{17,30,32,51,56,93} with P > .05 for these adverse effects. All reductions, except for liver injury, diarrhea, and neutropenia, were statistically significant (Table 4). However, THM-specific adverse events were rarely reported or not clearly distinguished from general chemotherapy-related ADRs in the included studies. Therefore, a separate quantitative analysis of ADRs directly attributable to THM was not feasible.

Table 4.

Adverse Drug Reactions of FBQYT Methods THM + Chemotherapy.

ADRs	Studies	Participants	Risk ratio (95% CI)	P-value	Study ID references
ADRs	Studies	Participants	Random effects model	P-value	Study ID references
Incidence of Myelosuppression	6	400	RR 0.47, 95% CI [0.33, 0.68], I² = 0%	<.0001***	Kong (2016), Li (2016b), Sun (2016), Wang (2016c), Wu (2010), Yang (2016)
Leukocyte reduction	28	2146	RR 0.59, 95% CI [0.51, 0.68], I² = 8%	<.00001***	An (2016), Chen (2020), Fang (2013), Gao (2016), Hu (2013), Huang (2014), Li (2002), Li (2008), Liang (2022), Liu (2015), Lu (2016), Rong (2014), Shao (2016), Wang (2016a),Wang (2016b), Wang (2018),Wang (2021), Xia (2015), Xu (2007), Xu (2014), Xu (2016), Yan (2016), Yang (2016), You (2016), Zhang (2014), Zhang (2018), Zhu (2011), Zhu (2016)
Neutropenia	4	266	RR 0.38, 95% CI [0.12, 1.17], I² = 47%	=.09	Wang (2018), Yang (2016), Zhang (2014), Zhu (2011)
Platelet reduction	20	1620	RR 0.51, 95% CI [0.41, 0.64], I² = 0%	<.00001***	An (2016), Chen (2020), Fang (2013), Gao (2016), Huang (2014), Li (2002), Li (2008), Liu (2015), Rong (2014), Wang (2016a), Wang (2016b), Wang (2021), Xu (2007), Xu (2016), Yang (2016), You (2016), Zhang (2014), Zhao (2012), Zhu (2011), Zhu (2016)
Hb reduction	14	1156	RR 0.51, 95% CI [0.40, 0.66], I² = 0%	<.00001***	Chen (2020), Fang (2013), Gao (2016), Li (2002), Liang (2022), Rong (2014), Wang (2016b), Wang (2018), Wang (2021), Xu (2014), You (2016), Zhang (2014), Zhang (2018), Zhu (2011)
Liver injury	10	913	RR 0.76, 95% CI [0.55, 1.05], I² = 0%	.10	Rong (2014), Wang (2016b), Wang (2021), Xu (2007), Xu (2014), Zhang (2014), Zhang (2018), Zhang (2019), Zhu (2016), Ding (2024)
Renal injury	2	277	RR 0.33, 95% CI [0.18, 0.59], I² = 0%	.0002***	Rong (2014), Wang (2021)
Nausea and vomiting	20	1551	RR 0.46, 95% CI [0.33, 0.66], I² = 56%	<.0001***	An (2016), Fang (2013), Gong (2020), Huang (2014), Li (2002), Li (2008), Li (2014), Liu (2015), Liu (2016), Lu (2016), Wang (2016b), Xiao (2011), Xu (2007), Xu (2014), Xu (2016), Yan (2016), Zhang (2014), Zhang (2019), Zhao (2012), Zhu (2016)
Diarrhea	6	460	RR 0.55, 95% CI [0.29, 1.05], I² = 32%	.07	Gong (2020), Xu (2014), Yan (2016), Yang (2018), Zhang (2019), Ding (2024)
Gastrointestinal Symptoms	14	1194	RR 0.52, 95% CI [0.42, 0.64], I² = 0%	<.00001***	Chen (2020), Gong (2020), Li (2016b), Liang (2022), Rong (2014), Shao (2016), Sun (2016), Wang (2016c), Wu (2010), Xia (2015), Xiao (2017), Yang (2018), You (2016), Zhang (2018)
Neurotoxicity	5	308	RR 0.48, 95% CI [0.28, 0.81], I² = 0%	<.006**	Li (2017), Liang (2022), Lu (2016), Wang (2016b), Zhang (2014)

P < .01, ***P < .001.

Survival Rate

The meta-analysis revealed that the combination of THM and chemotherapy significantly improved survival outcomes. Specifically, there was a marked increase in the 1-year survival rate (RR 1.27, 9 trials, Figure 8),^{15,16,18,44,48,55,72,80,87} the 2-year survival rate (RR 1.64, 3 trials,Figure 9),^18,72,87 and the 3-year survival rate (RR 1.82, 3 trials, Figure 10).^44,72,87 Furthermore, the combination therapy significantly enhanced progression-free survival (PFS; RR 2.84, 5 trials, Figure 11)^{26,29,30,32,60} and extended median survival time (MST) by 3.24 months (MD 3.24 months, 8 trials, Figure 12).^{16,18,26,30,44,45,72,80} All these improvements were statistically significant (P < .05 for all outcomes), underscoring the effectiveness of combining THM with chemotherapy in improving long-term survival and patient outcomes.

Figure 8.

One-year survival rate of FBQYT method THM + chemotherapy.

Figure 9.

Two-year survival rate of FBQYT method THM + chemotherapy.

Figure 10.

Three-year survival rate of FBQYT method THM + chemotherapy.

Figure 11.

Progression-Free Survival of FBQYT method THM + chemotherapy.

Figure 12.

Median Survival Time (Months) of FBQYT method THM + chemotherapy.

Publication Bias

To investigate publication bias, funnel plots were created using RR, and MD values extracted from trials that measured ORR, KPS score, and 1-year survival rate. The funnel plot analysis for the ORR study exhibited a symmetrical shape (Figure 13), indicating a balanced distribution of studies across a range of effect sizes and their corresponding precision measures. This symmetry suggests the absence of significant publication bias or small study effects, reinforcing the reliability and robustness of the study’s findings regarding ORR. However, the funnel plots generated based on the KPS score and 1-year survival rate displayed an asymmetrical distribution (Figures 14 and 15), suggesting the potential presence of publication bias in these analyses.

Figure 13.

Funnel plot assessing publication bias (ORR in 45 trials).

Figure 14.

Funnel plot assessing publication bias (KPS score in 20 trials).

Figure 15.

Funnel plot assessing publication bias (1-year survival rate in 9 trials).

Quality of Evidence Assessment

In evaluating tumor response, the ORR and DCR were analyzed across 45 and 44 RCTs, respectively. The QoL outcomes were assessed using the KPS score (20 RCTs), KPS improvement rate (23 RCTs), FACT-L (3 RCTs), and QLQ-C30 (5 RCTs). Additionally, tumor markers (CEA, CYFRA21-1, VEGF), 1 to 3-year survival rates, PFS, MST, and adverse drug reactions including myelosuppression, leukocyte decrease, neutropenia, platelet reduction, hemoglobin decrease, liver and renal injury, nausea, vomiting, diarrhea, nerve infections, and gastrointestinal symptoms were all analyzed. Most outcomes were assessed with “Moderate” certainty. However, PFS and MST were evaluated with high certainty. QLQ-C30 subscales for PF, CF, SF, pain, and dyspnea were rated as low, while diarrhea was rated as very low. The main reasons for downgrading the quality of evidence for certain outcomes were inconsistencies, particularly when 1 or more mean results deviated in the opposite direction, and imprecision, especially when CIs crossed into non-significant ranges or when the total sample size was less than 400. Detailed outcomes, effects, and absolute effects are available in the Supplemental Materials (Table 5).

Table 5.

A Summary of Comprehensive Assessment.

Outcomes	No. of studies (RCTs)	No. of patients (Herbal medicine/control)	Risk of Bias	Inconsistency	Indirectness	Imprecision	Effect (RR & 95% CI)	Absolute effect (per1000 & 95% CI)	Certainty
Tumor response assessment
ORR	46	829/1678 (49.40%)/ 536/1616 (33.16%)	Not serious	Not serious	Not serious	Serious^a	RR 1.41 (1.30, 1.52)	148 more (108 more to 187 more)	⊕⊕⊕⊝ Moderate
DCR	44	1375/1632 (84.25%)/1068/1581 (67.55%)	Not serious	Not serious	Not serious	Serious^a	RR 1.20 (1.15, 1.25)	137 more (103 more to 171 more)	⊕⊕⊕⊝ Moderate
Quality of life assessment
KPS score	21	777/768	Not serious	Not serious	Not serious	Serious^a	—	MD 8.53 higher (6.91 higher to 10.15 higher)	⊕⊕⊕⊝ Moderate
KPS improvement rate	23	649/872 (74.4%)/420/860 (48.8%)	Not serious	Not serious	Not serious	Serious^a	RR 1.51 (1.33, 1.70)	249 more (161 more to 342 more)	⊕⊕⊕⊝ Moderate
QLQ-C30
Physical functioning	5	199/196	Not serious	Not serious	Not serious	Very serious^a,b	—	MD 5.17 higher (0.24 higher to 10.09 higher)	⊕⊕⊝⊝ Low
Role functioning	5	199/196	Not serious	Not serious	Not serious	Serious^b	—	MD 8.95 higher (1.73 higher to 16.18 higher)	⊕⊕⊕⊝ Moderate
Emotional functioning	5	199/196	Not serious	Not serious	Not serious	Serious^b	—	MD 8.85 higher (2.47 higher to 15.22 higher)	⊕⊕⊕⊝ Moderate
Cognitive functioning	5	199/196	Not serious	Not serious	Not serious	Very serious^a,b	—	MD 5.56 higher (0.09 lower to 11.21 higher)	⊕⊕⊝⊝ Low
Social functioning	4	141/138	Not serious	Not serious	Not serious	Very serious^a,b	—	MD 5.87 higher (0.24 lower to 11.98 higher)	⊕⊕⊝⊝ Low
Quality of life total	3	100/97	Not serious	Not serious	Not serious	Serious^b	—	MD 13.05 higher (8.79 higher to 17.30 higher)	⊕⊕⊕⊝ Moderate
Fatigue	3	100/97	Not serious	Not serious	Not serious	Serious^b	—	MD 17.79 lower (23.98 lower to 11.60 lower)	⊕⊕⊕⊝ Moderate
Nausea and vomiting	3	100/97	Not serious	Not serious	Not serious	Serious^b	—	MD 8.02 lower (15.85 lower to 0.20 lower)	⊕⊕⊕⊝ Moderate
Pain	3	100/97	Not serious	Not serious	Not serious	Very serious^a,b	—	MD 4.39 lower (11.06 lower to 2.27 higher)	⊕⊕⊝⊝ Low
Dyspnea	3	100/97	Not serious	Not serious	Not serious	Very serious^a,b	—	MD 7.11 lower (12.56 lower to 1.66 lower)	⊕⊕⊝⊝ Low
Sleep	3	100/97	Not serious	Not serious	Not serious	Serious^b	—	MD 12.06 lower (20.23 lower to 3.9 lower)	⊕⊕⊕⊝ Moderate
Appetite loss	3	100/97	Not serious	Not serious	Not serious	Serious^b	—	MD 13.04 lower (21.52 lower to 4.55 lower)	⊕⊕⊕⊝ Moderate
Constipation	3	100/97	Not serious	Not serious	Not serious	Seriousa^b	—	MD 6.74 lower (12.49 lower to 0.98 lower)	⊕⊕⊕⊝ Moderate
Diarrhea	3	100/97	Not serious	Serious^c	Not serious	Very serious^a,b	—	MD 2.84 lower (8.1 lower to 2.41 higher)	⊕⊝⊝⊝ Very low
Financial difficulties	3	100/97	Not serious	Serious^c	Not serious	Serious^a,b	—	MD 2.96 lower (8.23 lower to 2.32 higher)	⊕⊕⊕⊝ Moderate
Fact-L
Physical well-being	3	74/77	Not serious	Not serious	Not serious	Serious^b	—	MD 4.68 higher (0.43 lower to 9.79 higher)	⊕⊕⊕⊝ Moderate
Social well-being	3	74/77	Not serious	Not serious	Not serious	Serious^b	—	MD 1.30 higher (0.29 lower to 2.90 higher)	⊕⊕⊕⊝ Moderate
Emotional well-being	3	74/77	Not serious	Not serious	Not serious	Serious^b	—	MD 2.78 higher (0.85 lower to 6.42 higher)	⊕⊕⊕⊝ Moderate
Functional Well-Being	3	74/77	Not serious	Not serious	Not serious	Serious^b	—	MD 7.38 higher (1.73 lower to 16.48 higher)	⊕⊕⊕⊝ Moderate
Lung Cancer Subscale	3	74/77	Not serious	Not serious	Not serious	Serious^b	—	MD 8.28 higher (2.22 lower to 18.78 higher)	⊕⊕⊕⊝ Moderate
Total	2	74/77	Not serious	Not serious	Not serious	Serious^b	—	MD 16.70 higher (10.02 lower to 43.41 higher)	⊕⊕⊕⊝ Moderate
Adverse drug reactions
Incidence of myelosuppression	6	29/203 (14.3%)/60/197 (30.5%)	Not serious	Not serious	Not serious	Very serious^a,b	RR 0.46 (0.32, 0.62)	164 fewer (207 fewer to 101 fewer)	⊕⊕⊝⊝ Low
Leukocyte decrease	28	212/1088 (19.49%)/389/1058 (36.77%)	Not serious	Not serious	Not serious	Serious^a	RR 0.59 (0.51, 0.68)	157 fewer (188 fewer to 122 fewer)	⊕⊕⊕⊝ Moderate
Platelet decrease	20	80/820 (9.76%)/164/800 (20.50%)	Not serious	Not serious	Not serious	Serious^a	RR 0.51 (0.41, 0.64)	102 fewer (123 fewer to 75 fewer)	⊕⊕⊕⊝ Moderate
Neutropenia	4	9/135 (6.67%)/32/131 (24.43%)	Not serious	Not serious	Not serious	Serious^a	RR 0.38 (0.12, 1.17)	225 fewer (320 fewer to 62 more)	⊕⊕⊕⊝ Moderate
Hemoglobin decrease	14	70/586 (11.9%)/140/570 (24.5%)	Not serious	Not serious	Not serious	Serious^a	RR 0.51 (0.40, 0.66)	120 fewer (147 fewer to 84 fewer)	⊕⊕⊕⊝ Moderate
Liver injury	10	46/460 (10.0%)/68/453 (15.01%)	Not serious	Not serious	Not serious	Serious^a	RR 0.76 (0.55,1.05)	36 fewer (68 fewer to 8 more)	⊕⊕⊕⊝ Moderate
Renal injury	2	13/140 (9.29%)/39/137 (28.47%)	Not serious	Not serious	Not serious	Very serious^a,b	RR 0.33 (0.18,0.59)	191 fewer (233 fewer to 117 fewer)	⊕⊕⊝⊝ Low
Nausea and vomiting	20	110/735 (14.97%)/208/716 (29.05%)	Not serious	Not serious	Not serious	Serious^a	RR 0.46 (0.33,0.66)	169 fewer (210 fewer to 106 fewer)	⊕⊕⊕⊝ Moderate
Diarrhea	6	23/230 (10.0%)/42/230 (18.2%)	Not serious	Not serious	Not serious	Serious^a	RR 0.55 (0.29,1.05)	82 fewer (130 fewer to 9 more)	⊕⊕⊕⊝ Moderate
Nerve infection	5	16/155 (10.3%)/35/153 (22.9%)	Not serious	Not serious	Not serious	Serious^a	RR 0.48 (0.28,0.81)	119 fewer (165 fewer to 43 fewer)	⊕⊕⊕⊝ Moderate
Gastrointestinal Symptoms	14	90/601 (15.0%)/177/593 (29.8%)	Not serious	Not serious	Not serious	Serious^a	RR 0.52 (0.42, 0.64)	221 fewer (236 fewer to 203 fewer)	⊕⊕⊕⊝ Moderate
Tumor marker level
Tumor marker- CEA	8	373/363	Not serious	Not serious	Not serious	Serious^a	—	MD 7.34 lower (11.33 lower to 3.36 lower)	⊕⊕⊕⊝ Moderate
Tumor marker- CYFRA21-L	5	287/277	Not serious	Not serious	Not serious	Serious^a	—	MD 1.55 lower (2.13 lower to 0.97 lower)	⊕⊕⊕⊝ Moderate
Tumor marker-VEGF	6	236/228	Not serious	Not serious	Not serious	Serious^a	—	MD 17.71 lower (33.14 lower to 2.28 lower)	⊕⊕⊕⊝ Moderate
Survival rate
One-year survival rate	9	270/523 (51.63%)/195/493 (39.55%)	Not serious	Not serious	Not serious	Serious^a	RR 1.27 (1.12, 1.44)	119 more (from 53 more to 194 more)	⊕⊕⊕⊝ Moderate
Two-year survival rate	3	36/113 (31.86%)/21/110 (19.09%)	Not serious	Not serious	Not serious	Serious^a	RR 1.64 (1.04, 2.58)	171 more (from 11 more to 422 more)	⊕⊕⊕⊝ Moderate
Three-year survival rate	3	38/214 (17.76%)/18/188 (9.57%)	Not serious	Not serious	Not serious	Serious^a	RR1.82 (1.02, 3.22)	83 more (from 2 more to 224 more)	⊕⊕⊕⊝Moderate
Median Survival Time (MST)	8	453/413	Not serious	Not serious	Not serious	Not serious	—	MD 3.24 higher (2.34 higher to 4.14 higher)	⊕⊕⊕⊕ High
Progression-Free Survival (PFS)	5	174/164	Not serious	Not serious	Not serious	Not serious	—	MD 2.84 higher (1.93 higher to 3.76 higher)	⊕⊕⊕⊕ High

Abbreviations: CI, confidence interval; MD, mean difference; RR, risk ratio; Serious^a, the confidence interval overlaps with the region of no effect; Serious^b, the total sample size for each group does not exceed 400, Serious^c, 1 or more mean results deviate in the opposite direction.

Frequency Analysis

A total of 192 HMs were identified from the selected literature, with each prescription demonstrating enhanced anti-cancer effectiveness and reduced side effects when combined with palliative chemotherapy. Among these, 80 herbs were classified as high-frequency, each used more than 3 times (median ≥ 2), accounting for 42.71% of the total. The top 10 most frequently used herbs included Astragalus membranaceus (82.72%), Atractylodes macrocephala (44.44%), Ophiopogon japonicus (each 39.51%), Poria cocos (38.27%), Glycyrrhiza uralensis (32.10%), Pseudostellaria heterophylla (27.16%), Codonopsis pilosula (25.93%), Glehnia littoralis and Citrus reticulata (each 24.69%), as well as Pinellia ternata (23.46%). Among herbs used more than 10 times, 37.8% were classified as Tonifying Qi or Nourishing Yin, followed by Heat-Clearing Herbs (24.4%), Blood-Invigorating Herbs (9.8%), Phlegm-Resolving Herbs (6.1%), and Qi-Regulating Herbs (4.88%). Additionally, Astringent Herbs and External Application Herbs accounted for 3.66% each, while Digestive Herbs contributed 2.44%. The remaining 7.32%, categorized as “others,” consisted of Water-Dampness Draining Herbs, Blood-Tonifying Herbs, Cough-Stopping Herbs, Dampness-Transforming Herbs, Surface-Relieving Herbs, and Calm Spirit Herbs, each contributing 1.22%⁹⁴ (Table 6 & Figure 16). Additionally, 54 high-frequency families, each used more than 5 times (mean frequency ≥ 4.81), comprised 27.83% of the total. Network analysis revealed 5283 herbal pair combinations, with Astragalus membranaceus being the most frequently used herb (67 times), and the Astragalus membranaceus-Atractylodes macrocephala pair being the most common combination (31 times). Core herbs extracted from the network showed high centrality (Figure 17A and B). These findings are summarized and categorized based on the Fuzheng principle and Qi-Yin classification (Supplemental Table S1–3). In the centrality analysis, we ranked the herbs by sorting the Average Shortest Path Length from lowest to highest and the other 3 centrality metrics from highest to lowest. The herbs with the highest centrality based on Average Shortest Path Length were Astragali Radix, Atractylodis Macrocephalae Rhizoma, Poria, Ophiopogonis Radix, Glycyrrhiza uralensis, Pseudostellariae Radix, Codonopsis Radix, Glehniae Radix, Citri Reticulatae Pericarpium, and Pinelliae Rhizoma (Table 7).

Table 6.

Herbal Medicine Frequencies in Lung Cancer Therapy.

Botanical name	Drug name	No. of prescriptions	Frequency (%)	Herbal category
Astragalus membranaceus	Astragali Radix	67	82.72	Tonifying Qi
Atractylodes macrocephala	Atractylodis Macrocephalae Rhizoma	36	44.44	Tonifying Qi
Ophiopogon japonicus	Ophiopogonis Radix	32	39.51	Nourishing Yin
Poria cocos	Poria	31	38.27	Tonifying Qi
Glycyrrhiza uralensis	Glycyrrhizae Radix et Rhizoma	26	32.10	Tonifying Qi
Pseudostellaria heterophylla	Pseudostellariae Radix	22	27.16	Tonifying Qi
Codonopsis pilosula	Codonopsis Radix	21	25.93	Tonifying Qi
Glehnia littoralis	Glehniae Radix	20	24.69	Nourishing Yin
Citrus reticulata	Citri Reticulatae Pericarpium	20	24.69	Qi-Regulating
Pinellia ternata	Pinelliae Rhizoma	19	23.46	Phlegm-Resolving
Hedyotis diffusa	Oldenlandiae Herba	19	23.46	Heat-Clearing
Scutellaria barbata	Scutellariae Barbatae Herba	18	22.22	Heat-Clearing
Ligustrum lucidum	Ligustri Lucidi Fructus	18	22.22	Nourishing Yin
Coix lacryma-jobi	Coicis Semen	17	20.99	Water-Dampness Draining
Angelica sinensis	Angelicae Sinensis Radix	15	18.52	Blood-Tonifying
Lycium barbarum	Lycii Fructus	14	17.28	Nourishing Yin
Strobilanthes cusia	Strobilanthis Herba	14	17.28	Heat-Clearing
Rehmannia glutinosa	Rehmanniae Radix Preparata	13	16.05	Nourishing Yin
Polygonatum sibiricum	Polygonati Rhizoma	12	14.81	Nourishing Yin
Psoralea corylifolia	Psoraleae Fructus	11	13.58	Tonifying Qi
Fritillaria thunbergii	Fritillariae Thunbergii Bulbus	10	12.35	Phlegm-Resolving
Curcuma aromatica	Curcumae Radix	10	12.35	Blood-Invigorating
Schisandra chinensis	Schisandrae Fructus	10	12.35	Astringent
Prunus armeniaca	Armeniacae Semen Amarum	10	12.35	Cough-Stopping

Total prescription numbers, n = 81

Figure 16.

Herb categories distribution.

Figure 17.

(A) Visualized networks of herbs (Circular layout): The above figure displays the network connectivity of 53 herbs in a circular layout. The size of the circle increases as the herb is used more frequently, and the thickness of the line between the hubs indicates the frequency of co-occurrence. (B) Visualized networks of herbs (Force-directed layout in core): While the circular layout allows to see the relationship between herbs at a glance, it has the limitation of making it difficult to identify clusters. To overcome this, the force-directed layout introduces the concept of electromagnetic force based on co-occurrence. It suggests that the core hubs are in the center. The primary clusters are Astragali Radix and Atractylodis Macrocephalae Rhizoma.

Table 7.

Centrality Analysis of 10 Core Herbs.

No.	Herb name	Average shortest path length	Closeness centrality	Degree centrality	Betweenness centrality
1	Astragali Radix	1	1	85	1.08
2	Atractylodis Macrocephalae Rhizoma	1.01	0.91	83	1.65
3	Poria	1.05	0.94	76	1.011
4	Ophiopogonis Radix	1.13	0.88	78	1.012
5	Glycyrrhizae Radix et Rhizoma	1.63	0.61	65	0.66
6	Pseudostellariae Radix	1.13	0.88	66	0.68
7	Codonopsis Radix	1.17	0.85	58	0.480
8	Glehniae Radix	1.23	0.81	62	0.483
9	Citri Reticulatae Pericarpium	1.44	0.69	59	0.403
10	Pinelliae Rhizoma	1.55	0.64	65	0.537

Discussion

This meta-analysis systematically reviewed and analyzed 81 studies involving 5955 participants to evaluate the efficacy and safety of combining THM with chemotherapy in treating lung cancer. A comprehensive assessment of the included studies was conducted using the RoB tool, which facilitated the evaluation of potential biases in these trials. The analysis revealed that the trials demonstrated an unclear risk of bias, primarily due to deficiencies in methodological reporting. Specifically, many trials did not provide sufficient details on allocation concealment, and blinding of participants was challenging due to the nature of the intervention with THM. Additionally, detection bias was unclear in many studies, and reporting bias was difficult to assess due to the lack of protocol registration. Despite including a large number of studies, the overall methodological quality varied. To mitigate this, we applied strict eligibility criteria and emphasized clarity in outcome definitions. These observations highlight the need to prioritize methodological rigor over quantity in future research.

The RoB assessments highlight the necessity for more rigorously designed RCTs in this field to bolster the evidence base. To ensure clarity and consistency in evaluating treatment outcomes, studies focusing on various syndrome types, including Qi or Yin deficiency, were included. Additionally, studies incorporating the concept of Fuzheng, even without explicitly mentioning Qi or Yin deficiency, were also included. Studies that did not align with these criteria were excluded. Furthermore, studies using interventions such as radiotherapy or injectable treatments, as well as those involving combined treatments of herbal medicine and acupuncture, were excluded.

Primary outcomes demonstrated a positive link between THM and tumor response, with both ORR and DCR showing statistically significant improvements. Secondary outcomes revealed that patients receiving both THM and chemotherapy mostly showed improved QoL scores. However, the FACT-L scores and QLQ-C30 subscales, including CF, SF, Pain, Diarrhea, and Financial Difficulties, did not show significant improvement, which may be attributed to the subjective nature of these patient-reported tools and a small number of studies included. In contrast, improvements in quality of life were observed through third-party evaluations such as KPS, which confirmed an improvement in patients’ quality of life. Although the FACT-L and QLQ-C30 did not show significant improvements in some subscales, their established reliability and effectiveness as quality-of-life indicators remain valuable, as demonstrated in previous studies.^7,61

Additionally, the combination of THM and chemotherapy resulted in fewer adverse drug reactions and reduced tumor marker levels compared to chemotherapy alone. However, adverse drug reactions such as neutropenia, liver injury, and diarrhea, which are closely associated with certain chemotherapy agents, may be more difficult to alleviate through adjunctive therapies like THM due to the inherent mechanisms of these drugs. The relatively small sample size for studies focusing on these specific side effects may have also limited the ability to demonstrate statistically significant improvements. Nevertheless, positive outcomes observed in other cancer studies,⁹⁵ alongside favorable results in other indicators within our study, suggest that the integration of THM with chemotherapy may offer effective management of chemotherapy-related adverse reactions.

Most included studies did not report adverse events attributable solely to THM, limiting our ability to evaluate its independent safety profile. Nevertheless, the combination therapy demonstrated improved long-term outcomes, including 1 to 3-year survival rates, prolonged PFS, and extended MST. Although subgroup analysis by herbal category was not feasible due to heterogeneous compositions and inconsistent reporting across studies, subgroup analyses based on chemotherapy type (eg, NP, GP, TP) were conducted for ORR, DCR, KPS score, and KPS improvement. This review focused exclusively on NSCLC, and studies involving SCLC were excluded based on our predefined eligibility criteria, as the rapid progression of SCLC limits the feasibility of integrating herbal therapies.

Based on these positive results, our study may provide new insights into the global challenge of treating lung cancer, which is complicated by various risk factors and has a significant impact on patients quality of life. Lung cancer is the leading cause of cancer-related deaths globally, outpacing other types of cancer in mortality rates. The treatment regimen for NSCLC, which accounts for about 85% of lung cancer cases, typically includes surgery, radiation, and chemotherapy.¹ However, many patients present with advanced-stage disease, making surgical intervention infeasible. Chemotherapy remains the primary treatment for these patients, often complemented by targeted therapies and immunotherapies. Despite significant therapeutic advancements, the side effects of chemotherapy, such as myelosuppression gastrointestinal disturbances, and decreased quality of life, continue to pose major challenges.⁴

Recently, interest has increased in integrating THM with conventional chemotherapy. THM, consisting of various herbal formulations long used in TAM for health support and disease treatment, aims to enhance chemotherapy’s effectiveness, reduce side effects, and improve patients’ overall quality of life.^7,8 One of the key therapeutic methods in THM is the FBQYT approach, which is centered on tonifying Qi and nourishing Yin. In line with this approach, the RCTs analyzed for ORR and DCR research frequently used herbs like Astragalus membranaceus, Poria cocos, Atractylodes macrocephala, Ophiopogon japonicus, and Glycyrrhiza uralensis. Zhang et al’s study⁹⁶ demonstrated that such decoctions alleviate symptoms such as cough and phlegm, enhance immune function, and improve quality of life while reducing side effects. When combined with palliative chemotherapy and EGFR-TKIs (erlotinib, gefitinib, osimertinib), the FBQYT method decoction has shown potential to enhance treatment efficacy by inhibiting cancer cell proliferation and inducing apoptosis. Similarly, studies by Liu et al⁹⁷ on BuZhongYiQi decoction and Cui et al⁹⁸ on ShaShenMaiDong decoction, which also include these herbs, found they inhibit cancer growth and aid in overcoming drug resistance. This effect is attributed to Astragalus’s ability to boost immune function by increasing cAMP levels, enhancing leukocyte and macrophage activity, stabilizing red blood cells, and promoting DNA synthesis in regenerating liver cells. Atractylodes and Glycyrrhiza promote T cell growth and maturation, improving immune response. Poria cocos reverses TNF-β-induced EMT and reduces E-cadherin downregulation and Vimentin upregulation, Downregulates GPX4 and SLC7A11, Ferroptosis inhibitor (Fer-1) reverses the effects.⁹⁹ Glehnia root contains sterols with anti-tumor, anti-inflammatory, and immune-regulating properties, while Ophiopogon root contains isoflavones that inhibit lung cancer cell growth.¹⁰⁰ Furthermore, chemotherapeutic agents such as docetaxel and cisplatin were found to enhance these effects by promoting apoptosis and suppressing the tumor microenvironment. Thus, the combination of the FBQYT method of traditional herbal medicines with chemotherapy appears to enhance therapeutic efficacy while reducing common side effects of cancer therapies. The therapeutic efficacy of FBQYT-based integrative therapy may be partially explained by its underlying biological mechanisms. Many of the included herbs, such as Astragalus membranaceus and Glycyrrhiza uralensis, are known to enhance immune function by promoting lymphocyte activity, cytokine regulation, and macrophage activation. These immunomodulatory effects may contribute to improved tumor control and resilience during chemotherapy. Additionally, herbs like Poria cocos and Atractylodes macrocephala have demonstrated properties in reducing inflammation, mitigating oxidative stress, and reversing EMT, which may help in reducing chemotherapy-induced toxicity and inhibiting tumor metastasis. Some ingredients also influence ferroptosis-related pathways, suggesting a possible mechanism in enhancing cell death of resistant tumor cells. Collectively, these mechanisms support the observed clinical benefits and provide biological plausibility for integrating THM with chemotherapy.

In this study, we confirmed the frequent use of herbs such as Astragali Radix, Atractylodis Macrocephalae Rhizoma, Ophiopogonis Radix, Poria, and Glycyrrhiza uralensis. Notably, 37.8% of herbs used more than 10 times were classified as tonifying qi or nourishing yin herbs in traditional Chinese medicine. These findings align with previous research that also reported the frequent use of these herbs.¹⁰¹ Although the inclusion criteria required explicit reference to Fuzheng principles including strategies such as tonifying qi or nourishing yin rather than herb composition alone, it is noteworthy that the central herbs identified via network analysis overlapped significantly with commonly cited Fuzheng components. This alignment reinforces the validity of the classification while also suggesting a degree of convergence in clinical practice.

Despite the evident benefits of combining THM with palliative chemotherapy for lung cancer, there remain knowledge gaps in THM’s specifics, such as discerning essential components and probing potential interactions between herbal medicines and standard treatments. This study, focusing on FBQYT traditional herbal medicines, provides a clearer evaluation of their effects. Previous studies and recent meta-analyses have primarily focused on immune functions within a specific timeframe, lacking a more comprehensive evaluation. In contrast, this study conducted an extensive meta-analysis and provided a thorough evaluation, covering a broader range of clinical outcomes. This comprehensive approach can be particularly helpful to practitioners who treat lung cancer patients with palliative chemotherapy, offering them more effective and targeted herbal treatment options. Integrating THM into palliative chemotherapy regimens for lung cancer offers a promising strategy to enhance treatment outcomes and improve patient quality of life.

Limitations

This study has several limitations. Firstly, although we performed subgroup analyses based on chemotherapy type (eg, NP, GP, TP, DP) for ORR, DCR, KPS score, and KPS improvement, subgroup analyses based on cancer subtype or herbal treatment category were not feasible due to the limited number of trials per group and inconsistent reporting. Although the frequency of THM categories was analyzed, their heterogeneous compositions precluded meaningful subgroup comparisons. Moreover, variations in THM formulations and treatment durations across studies may have affected the outcomes but were not amenable to detailed analysis due to limited reporting. Blinding was inherently infeasible since THM was administered solely to the intervention group, potentially introducing placebo effects, especially in subjective outcomes like quality of life. Most included studies did not distinguish between THM-related and chemotherapy-related adverse events, limiting our ability to assess the safety of THM independently. Overall survival (OS) was reported in only 1 study, precluding its inclusion in the meta-analysis due to inconsistent availability. The funnel plot indicated potential publication bias, and many studies had small sample sizes, limiting the generalizability of the findings. Future studies should adopt more standardized reporting, larger sample sizes, and clearer outcome definitions to validate the clinical value of FBQYT-based integrative therapy.

Conclusions

This systematic review and meta-analysis indicates that the combination of palliative chemotherapy and the FBQYT method of THM yields promising therapeutic benefits in lung cancer. The integrative therapy significantly improves tumor response, quality of life, and survival outcomes, while also reducing the incidence of common chemotherapy-related adverse effects, including myelosuppression, leukopenia, thrombocytopenia, anemia, renal injury, nausea and vomiting, gastrointestinal symptoms, and neurotoxicity. Based on current evidence, this approach appears most suitable for stage III or IV NSCLC patients, particularly those with Qi and Yin deficiency. Herbal therapies are typically administered concurrently with chemotherapy over a period of 4 to 12 weeks. However, due to the moderate-to-unclear risk of bias in many of the included studies, further well-designed randomized controlled trials with standardized interventions, placebo controls, and rigorous methodological quality are warranted to validate these findings and support their clinical application.

Supplemental Material

sj-docx-1-ict-10.1177_15347354251373045 – Supplemental material for Efficacy of Herbal Medicine Therapy Combined With Palliative Chemotherapy in Unresectable Advanced NSCLC: A Systematic Review and Meta-Analysis

Supplemental material, sj-docx-1-ict-10.1177_15347354251373045 for Efficacy of Herbal Medicine Therapy Combined With Palliative Chemotherapy in Unresectable Advanced NSCLC: A Systematic Review and Meta-Analysis by Keon-Jun Lee, Jong-Ha Kwon, Dong-Hyeon Kim, Mi-Sun Park, Ye-Jin Jin, Ji-Hwan Kim, Hwa-Seung Yoo and So-Jung Park in Integrative Cancer Therapies

Footnotes

Acknowledgements

The authors thank all researchers and supporters involved in this study.

ORCID iDs

Keon-Jun Lee

Dong-Hyeon Kim

So-Jung Park

Ethical Considerations

No ethical approval was required as this study did not involve human participants or laboratory animals

Author Contributions

KJL and JHK contributed to study conception and design, and drafted the original manuscript. JHK, DHK, and MSP performed data collection, extraction, and assessment. KJL, JHK, HSY, and JHKim were involved in manuscript writing and critical revision. KJL, JHK, and DHK contributed to writing review and editing. JHK, HSY, and SJP were responsible for methodology and critical revision. SJP supervised the project, managed administration, and acquired funding. All authors reviewed and approved the final version of the manuscript.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: 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-2023-KH139460)

Declaration of Conflicting Interests

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

Data Availability Statement

All data and materials included in this study are included in this published article and supplementary material.

Supplemental Material

Supplemental material for this article is available online.

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