
==== Front
Heliyon
Heliyon
Heliyon
2405-8440
Elsevier

S2405-8440(24)13323-3
10.1016/j.heliyon.2024.e37292
e37292
Research Article
Fei Jin Sheng formula and its effectiveness in treating advanced non-small cell lung cancer: An observational study
Yan Zhen ab
Gao Wen-Cang c
Wang Xiao-Xiao d
Xu Hong-Quan e
Li Qian e
Chen Jian-Xiang e
Pang De-Xiang c
Xie Tian xbs@hznu.edu.cn
aef⁎
a First Clinical Medical Institute, Nanjing University of Chinese Medicine, Nanjing, Jiangsu, 210023, China
b Department of Traditional Chinese Medicine, Integrated Chinese and Western Medicine, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang, 310000, China
c Department of Oncology, The Second Affiliated Hospital of Zhejiang Chinese Medicine University, Hangzhou, Zhejiang, 310005, China
d Department of GCP, Jiangsu Provincial Hospital of Chinese Medicine, Nanjing University of Chinese Medicine, Nanjing, Jiangsu, 210029, China
e School of Pharmacy, Hangzhou Normal University, Hangzhou, Zhejiang, 311121, China
f Key Laboratory of Elemene Class Anti-Cancer Chinese Medicines, Engineering Laboratory of Development and Application of Traditional Chinese Medicines, Collaborative Innovation Center of Traditional Chinese Medicines of Zhejiang Province, Hangzhou Normal University, Hangzhou, Zhejiang, 311121, China
⁎ Corresponding author. First Clinical Medical Institute, Nanjing University of Chinese Medicine, No.138 of Xianlin Dadao, Xixia District, Nanjing, 210023, China. xbs@hznu.edu.cn
31 8 2024
30 9 2024
31 8 2024
10 18 e3729218 2 2024
28 8 2024
30 8 2024
© 2024 The Authors
2024
https://creativecommons.org/licenses/by-nc/4.0/ This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Objective

This study involved evaluating the efficacy of the Feijinsheng formula in the therapeutic management of patients with advanced non-small cell lung cancer (NSCLC).

Methods

We extracted the medical records of patients with advanced NSCLC undergoing treatment in the oncology department at the Second Affiliated Hospital of Zhejiang Chinese Medicine University from the medical record system. After applying inclusion and exclusion criteria, clinical data of 150 patients were collected. The patients were stratified into two groups based on their usage of the Feijinsheng formula, comprising 69 cases in the Exposed group and 81 cases in the Control group. A comparative analysis of the survival time difference between the two groups was conducted.

Results

The data between the two groups exhibited similarity (p > 0.05). Following treatment, the Exposed group demonstrated a notably prolonged overall survival time compared to the Control group (p < 0.05). While the Exposed group displayed a higher objective remission rate than the Control group, this disparity did not reach statistical significance (p > 0.05).

Conclusion

The Feijinsheng formula extended the duration of survival of patients with advanced NSCLC.

Keywords

Feijinsheng formula
Non-small cell lung cancer
Objective remission rate
Overall survival
Retrospective clinical research
Traditional Chinese medicine
==== Body
pmc1 Introduction

Lung cancer stands as the foremost contributor to cancer-related fatalities globally [1], comprising nearly 20 % of all cancer-related fatalities [1,2]. The global incidence of new lung cancer cases was estimated at 2.5 million in 2022, reflecting a rapid increase in recent years [1]. Lung cancer represents a complex and multifaceted disease, categorized into non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC) [3], constituting approximately 84 % and 13 % of lung cancer cases, respectively [4]. Merely 25%–30 % of individuals diagnosed with NSCLC are identified at early stages [5], with the majority diagnosed during advanced stages [6]. Despite the availability of numerous treatments for NSCLC, the majority of therapeutic approaches exhibit limitations, particularly in cases of advanced disease where patients derive limited benefits [[7], [8], [9], [10], [11]]. Consequently, the prognosis for NSCLC remains unfavorable. Hence, there is an urgent demand for the exploration and development of novel anti-NSCLC therapies.

In China, traditional Chinese medicine (TCM) stands as a valuable treasure, possessing distinct characteristics and advantages in managing intricate diseases, backed by millennia of clinical experience [12]. Recognized for its extensive historical application, TCM is acknowledged for providing distinctive methodologies in addressing complex diseases [12]. Empiricla investigations have demonstrated the anti-NSCLC efficacy of TCM. In a study by Xu et al. [13,14], Ze-Qi-Tang, a traditional Chinese herbal formula employed for respiratory system ailments, was found to impede the proliferation of NSCLC cells, presenting itself as a viable alternative treatment for NSCLC with evident anti-lung cancer effects [15]. Recent research has delved into exploring various TCM-derived compounds for their potential impacts on lung cancer [15]. For example, Lou et al. reported that ginkgetin, derived from Ginkgo biloba leaves, enhances cisplatin-induced anti-lung cancer effects by inducing ferroptosis [16].

Drawing on millennia of clinical application and the contemporary advancements in TCM research, seasoned TCM practitioners have formulated the Feijinsheng formula (FJS) for managing NSCLC [17,18]. Substantiated by a clinical study, FJS demonstrated a significant anti-NSCLC effect. In their research, Zhou et al. revealed that the integration of FJS with chemotherapy markedly reduced the pathological burden, elevated Karnofsky scores, and ameliorated the clinical symptoms of patients [19,20]. However, there remains a lack of objective assessment regarding the impact of FJS on extending the prognosis of individuals with advanced NSCLC.

In this investigation, we carried out a retrospective cohort study assessing the effectiveness of FJS in treating advanced NSCLC, focusing on the primary clinical endpoint of overall survival (OS). Secondary outcomes included the objective response rate (ORR). We aim to contribute additional evidence supporting the use of FJS in the treatment of advanced NSCLC, facilitating its more optimal application in patients with this condition, in the future.

2 Methods

2.1 Study population and initial screening

This retrospective cohort study was conducted exclusively at the Second Affiliated Hospital of Zhejiang Chinese Medicine University, focusing on inpatients at the oncology department, during the period spanning January 2014 to December 2021. Inclusion criteria encompassed patients pathologically or cytologically diagnosed with NSCLC, specifically adenocarcinoma or squamous carcinoma. Evaluation, following RECIST (version 1.1) guidelines for solid tumors, involved criteria such as complete response (CR), partial response (PR), stable disease (SD), and progressive disease (PD). Participants were required to exhibit at least one measurable lesion on imaging, manifest clarity on imaging after two treatment cycles, and not present serious liver or kidney failure, cardiovascular or cerebrovascular diseases. Additionally, comprehensive medical records were a prerequisite for inclusion. Exclusion criteria involved a survival time of less than 3 months, individuals with mental health disorders, pregnant or lactating women, and patients with more than two concurrent cancers. Approval for this study was granted by the ethics review committee of the Second Hospital of Zhejiang Chinese Medicine University ([2022]101–01).

We obtained baseline data from electronic medical records, encompassing information such as sex, age, smoking and drinking history, pathological type, transmission network management (TNM), physical status (PS), and laboratory tests (Table 1).Table 1 Clinical characteristics of patients in two groups.

Table 1Characteristics	Levels	FJS group (n = 61)	Control group (n = 89)	Statistics	P	
Sex [Case (%)]	Male	40 (65.6 %)	55 (61.8 %)	χ2 = 0.222	0.637	
	Female	21 (34.4 %)	34 (38.2 %)			
Age (Year)	Mean ± SD	67.95 ± 11.37	67.17 ± 10.72	t = 0.428	0.669	
Age group	<60	14 (23 %)	20 (22.5 %)	χ2 = 4.160	0.245	
	60–69	17 (27.9 %)	37 (41.6 %)			
	70–79	20 (32.8 %)	18 (20.2 %)			
	≥80	10 (16.4 %)	14 (15.7 %)			
Smoking history	no	31 (50.8 %)	48 (53.9 %)	χ2 = 0.141	0.708	
	yes	30 (49.2 %)	41 (46.1 %)			
Drinking history	no	44 (72.1 %)	65 (73 %)	χ2 = 0.015	0.903	
	yes	17 (27.9 %)	24 (27 %)			
TNM	III	8 (13.1 %)	12 (13.5 %)	χ2 = 0.004	0.948	
	IV	53 (86.9 %)	77 (86.5 %)			
Pathological pattern	squamous	17 (27.9 %)	19 (21.3 %)	χ2 = 0.844	0.358	
	adenocarcinoma	44 (72.1 %)	70 (78.7 %)			
EGFR mutations	no	37 (60.7 %)	50 (56.2 %)	χ2 = 0.298	0.585	
	yes	24 (39.3 %)	39 (43.8 %)			
PS	Mean ± SD	2.34 ± 0.81	2.34 ± 0.98	t = 0.047	0.962	
WBC	Median (IQR)	7.3 (5.4, 9.0)	7.10 (4.8,9.0)	U = 2624	0.731	
HB	Mean ± SD	116.95 ± 19.11	108.30 ± 25.12	t = 2.274	0.018	
PLT	Median (IQR)	239.0 (179.0, 311.0)	203.0 (152.0, 262.0)	U = 2188	0.044	
ALT	Median (IQR)	16.0 (11.0, 25.0)	17.00 (11.0, 25.0)	U = 2617	0.710	
AST	Median (IQR)	22.0 (18.0, 29.0)	24.00 (18.0, 29.0)	U = 2657	0.827	
ALB	Mean ± SD	33.46 ± 5.06	32.54 ± 5.20	t = 1.067	0.288	
TG	Median (IQR)	0.95 (0.74, 1.38)	1.06 (0.82, 1.44)	U = 2422	0.264	
TCHO	Mean ± SD	4.29 ± 1.00	4.46 ± 1.550	t = −0.766	0.409	
CEA	Median (IQR)	11.8 (4.0, 50.2)	15.0 (5.10, 117.1)	U = 2417	0.256	
CEA group	normal	19 (31.1 %)	22 (24.7 %)	χ2 = 0.753	0.386	
	abnormal	42 (68.9 %)	67 (75.3 %)			
CA19-9	Median (IQR)	13.20 (5.6, 57.2)	16.10 (5.3, 133.0)	U = 2588	0.551	
CA19-9 group	normal	43 (70.5 %)	55 (61.8 %)	χ2 = 1.210	0.272	
	abnormal	18 (29.5 %)	34 (38.2 %)			
Cyfra21-1	Median (IQR)	5.37 (2.55, 23.91)	6.35 (3.03, 21.10)	U = 2570	0.582	
Cyfra21-1 group	normal	14 (23 %)	16 (18 %)	χ2 = 0.559	0.454	
	abnormal	47 (77 %)	73 (82 %)			
SCC	Median (IQR)	1.10 (0.60, 2.20)	1.20 (0.60, 2.20)	U = 2651	0.808	
SCC group	normal	39 (63.9 %)	51 (57.3 %)	χ2 = 0.663	0.415	
	abnormal	22 (36.1 %)	38 (42.7 %)			
Chemotherapy	no	25 (41 %)	35 (39.3 %)	χ2 = 0.041	0.839	
	yes	36 (59 %)	54 (60.7 %)			
Radiotherapy	no	44 (72.1 %)	53 (59.6 %)	χ2 = 2.510	0.113	
	yes	17 (27.9 %)	36 (40.4 %)			
Targeted therapy	no	26 (42.6 %)	44 (49.4 %)	χ2 = 0.675	0.411	
	yes	35 (57.4 %)	45 (50.6 %)			
Immunotherapy	no	56 (91.8 %)	76 (85.4 %)	χ2 = 1.410	0.235	
	yes	5 (8.2 %)	13 (14.6 %)			
Notes: TNM: tumor-node-metastasis; PS: performance status; NRS: numeric rating scales; WBC: white blood cell; HB: haemoglobin; PLT: platelet count; ALT: alanine transaminase; AST: glutamic oxalic transaminase; ALB: albumin; TG: triglyceride; TCHO: total cholesterol; CEA: carcinoembryonic antigen; CA19-9: carbohydrate antigen 19–9; Cyfra21-1: cytokeratin 19 fragment 21-1; SCC: squamous cell carcinoma associated antigen.

2.2 Study endpoints and follow-up

The primary outcome measure was OS, delineated as the duration from the identification of any pertinent deaths or exclusions (until 2022-06-30) to the diagnosis of mid-late NSCLC. Secondary outcome parameters included the ORR, computed using the formula: (number of CR + number of PR)/total number of individuals.

We collected survival data through telephone follow-up. In cases where no primary endpoint event had transpired by the specified follow-up cut-off date (2022-06-30), that cut-off date was employed. Participants whose family members were uncooperative or unreachable during the telephone follow-up were designated as lost to follow up and noted as deletions. A thorough analysis was carried out to ascertain whether variables such as sex, age, smoking and drinking history, pathological type, TNM stage, PS, laboratory tests, treatment methods, and other factors in the Exposed group served as prognostic indicators for advanced NSCLC.

2.3 Feijinsheng formula composition

FJS used in this study, consists of the following medical plants:

Herba Euphorbiae Helioscopiae - Ze Qi (30g); Herba Salviae Chinensis - Shi Jian Chuan (30g); Radix Peucedani - Qian Hu (10g); Rhizoma Pinelliae - Jiang Ban Xia (9g); Radix Scutellariae - Huang Qin (10g); Radix et Rhizoma Ginseng - Ren Shen Pian (9g); Radix et Rhizoma Glycyrrhizae Praeparata cum Melle - Gan Cao (6g); Ramulus Cinnamomi - Gui Zhi (9g); Nidus Vespae - Chao Feng Fang (15g); Taxus chinensis var - Hong Dou Shan (8g); Rhizoma Arisaematis praeparatum - Zhi Nan Xing (6g). This composition was administered to patients as part of their treatment regimen. Medication regimen: Decoction of FJS, 150 ml, should be taken warm twice a day, in the morning and evening. Each course lasts for 14 days, and it should be taken continuously for at least 2 courses. The herbal formulation used in this traditional Chinese medicine compound is safe in terms of both the herbs and their dosages.

2.4 Statistical analysis

Statistical analyses were executed utilizing SPSS version 26.0 and R version 4.0.2, with the significance level (α) for statistical tests established at 0.05.

Continuous variables meeting the criteria of normality are presented as mean ± standard deviation, and intergroup comparisons were conducted using an independent sample t-test. In instances where continuous variables did not meet the normality assumption, the representation included median and quartile [Median (IQR)], and intergroup comparisons were performed using the Wilcoxon rank-sum test. Classification variables are expressed as the number of cases and relative frequencies, with intergroup comparisons carried out using the chi-squared test.

We employed Kaplan‒Meier curves and log-rank tests to illustrate the survival rates of both the Exposed group and the Control group, analyzing discrepancies in cumulative mortality between the two groups. Utilizing patient characteristics, laboratory test results, and treatment methods as independent variables, univariate analysis was conducted through the Cox proportional hazard regression model. In this analysis, FJS served as the primary study variable, with variables demonstrating p < 0.05 in the univariate analysis utilized as covariables. These variables were incorporated into the multivariate Cox proportional hazard regression model and the impact of FJS on patient survival was investigated through the stepwise regression method. The predictive capability of the multifactor model for 1-year, 3-year, and 5-year mortality risks was assessed using receiver operating characteristic curves (ROC) and the area under the ROC (AUC). The multifactor model is depicted graphically as a nomogram representing 1-year, 3-year, and 5-year mortality risks (Fig. 1).Fig. 1 Nomogram of multivariate cox regression model.

Fig. 1

Furthermore, preliminary screening of factors influencing the ORR was conducted through univariate analysis. Variables exhibiting p < 0.05 in the analysis were subsequently incorporated into the multivariate logistic regression to further investigate the influencing factors of ORR. Observe whether FJS has an effect on the objective response rate. Further analyze whether FJS exerts its anti-tumor effects by inhibiting the ORR.

3 Results

3.1 Baseline clinical characteristics of the study cohort

Among the 150 participants included in this study, 61 individuals (40.67 %) received FJS. In the Exposed group, the median age was 69.0 (63.0, 76.0), while in the Control group, it was 67.0 (60.0, 75.0). The Exposed group exhibited smoking and drinking rates of 49.2 % and 27.9 %, respectively. Predominantly, the pathological type was adenocarcinoma (72.1 %), with 24 patients (39.3 %) harboring EGFR mutations. Additional characteristics are detailed in Table 1. Upon comparing the patient characteristics between the Exposed and Control groups, it was observed that levels of hemoglobin (HB) (p = 0.018) and platelet count (PLT) (p = 0.044) were higher in the Exposed group compared to the Control group.

3.2 Clinical outcome

The Exposed group had a median follow-up duration of 24.40 months (13.70, 36.20), while the Control group had a median follow-up duration of 20.10 months (8.90, 28.70) (p = 0.014). Cumulative mortality in the Exposed group (78.7 %) was lower than in the Control group (92.1 %) (p = 0.017). The objective response rates for the two groups were 21.3 % and 15.7 %, respectively (p = 0.239) (Table 2).Table 2 Outcome indicator of the FJS group and control group.

Table 2Outcome indicators	FJS group (n = 61)	Control group (n = 89)	Statistics	P	
Survival time	24.40 (13.70, 36.20)	20.10 (8.90, 28.70)	U = 2074	0.014	
Survival state			χ2 = 5.660	0.017	
Survival	13 (21.3 %)	7 (7.9 %)			
Mortality	48 (78.7 %)	82 (92.1 %)			
ORR			χ2 = 0.764	0.382	
 No	48 (78.7 %)	75 (84.3 %)			
 Yes	13 (21.3 %)	14 (15.7 %)			
Note: ORR: objective remission rate.

The Kaplan‒Meier curve (Fig. 2) and log-rank test results showed that the cumulative death rate in the Exposed group was lower than that in the Control group (p = 0.012).Fig. 2 K–M curves of patients in the FJS group and control group.

Fig. 2

3.3 Overall survival

In the univariate Cox regression analysis, the Control group exhibited a 0.58-fold higher risk of mortality in contrast to the Exposed group (HR = 1.58, 95 % CI: 1.100–2.250, p = 0.013). Furthermore, performance status (PS), white blood cell (WBC) count, hemoglobin (HB), albumin (ALB), carcinoembryonic antigen (CEA), carbohydrate antigen 19–9 (CA19-9), cytokeratin 19 fragment 21-1 (Cyfra21-1), squamous cell carcinoma-associated antigen (SCC), and the administration of chemotherapy were all linked to a statistically significant risk of mortality (p < 0.05) (Table 3).Table 3 Univariate cox regression model of the risk of mortality.

Table 3Variable	Coefficient	HR	95%CI	P	
Lower limit	Upper limit	
Sex	
 Male	Reference	1.000	–	–	–	
 Female	−0.324	0.723	0.505	1.040	0.078	
Age	0.016	1.020	0.999	1.030	0.059	
Age group	
 <60	Reference	1.000	–	–	–	
 60-69	−0.220	0.802	0.506	1.270	0.350	
 70-79	−0.055	0.946	0.576	1.560	0.828	
 ≥80	0.414	1.510	0.876	2.610	0.137	
Smoking history	
 No	Reference	1.000	–	–	–	
 Yes	0.276	1.320	0.932	1.860	0.118	
Drinking history	
 No	Reference	1.000	–	–	–	
 Yes	0.057	1.060	0.717	1.560	0.775	
TNM	
 III	Reference	1.000	–	–	–	
 IV	0.12	1.130	0.656	1.940	0.663	
Pathological pattern	
 Squamous	Reference	1.000	–	–	–	
 Adenocarcinoma	−0.063	0.939	0.619	1.420	0.767	
EGFR mutations	
 No	Reference	1.000	–	–	–	
 Yes	−0.261	0.770	0.543	1.090	0.144	
PS	0.276	1.320	1.090	1.600	0.005	
WBC	0.025	1.030	1.000	1.050	0.027	
HB	−0.009	0.991	0.983	0.999	0.035	
PLT	0.0006	1.006	0.999	1	0.476	
ALT	−0.001	0.999	0.992	1.010	0.778	
AST	−0.001	0.999	0.992	1.010	0.718	
ALB	−0.051	0.951	0.920	0.982	0.002	
TG	0.022	1.020	0.779	1.34	0.873	
TCHO	−0.086	0.918	0.790	1.07	0.265	
CEA	0.0006	1.0006	1.000	1.001	0.003	
CEA group	
 Normal	Reference	1.000	–	–	–	
 Abnormal	0.356	1.430	0.958	2.130	0.080	
CA19-9	0.0001	1.0001	1.000	1	0.008	
CA19-9 group	
 Normal	Reference	1.000	–	–	–	
 Abnormal	0.272	1.310	0.918	1.880	0.137	
Cyfra21-1	0.012	1.010	1.010	1.020	<0.001	
Cyfra21-1 group	
 Normal	Reference	1.000	–	–	–	
 Abnormal	0.846	2.330	1.430	3.790	<0.001	
SCC	0.030	1.030	1.010	1.050	0.002	
SCC group	
 Normal	Reference	1.000	–	–	–	
 Abnormal	0.121	1.130	0.795	1.600	0.499	
Chemotherapy	
 No	Reference	1.000	–	–	–	
 Yes	−0.464	0.629	0.440	0.900	0.011	
Radiotherapy	
 No	Reference	1.000	–	–	–	
 Yes	−0.033	0.967	0.675	1.39	0.856	
Targeted therapy	
 No	Reference	1.000	–	–	–	
 Yes	−0.207	0.813	0.574	1.15	0.244	
Immunotherapy	
 No	Reference	1.000	–	–	–	
 Yes	−0.471	0.624	0.344	1.13	0.121	
FJS	
 Yes	Reference	1.000	–	–	–	
 No	0.455	1.58	1.100	2.250	0.013	

In the multivariate Cox regression model, the variables that exhibited statistical significance in the univariate Cox regression model were adjusted. The stepwise regression analysis revealed that patients in the Control group had a mortality risk 1.496 times higher than that of the Exposed group (HR = 1.496, 95 % CI: 1.041–2.149, p = 0.029) (Table 4).Table 4 Effect of the FJS on the risk of mortality of patients.

Table 4Variable	Coefficient	HR (95%CI)	z	P	
FJS	
 Yes	Reference	1.000	–	–	
 No	0.403	1.496 (1.041–2.149)	2.179	0.029	
WBC	0.022	1.023 (0.995–1.052)	1.574	0.116	
CEA	0.0005	1.0005 (1.0001–1.0010)	2.265	0.024	
Cyfra21-1	
 Normal	Reference	1.000	–	–	
 Abnormal	0.826	2.284 (1.386–3.763)	3.240	0.001	
SCC	0.021	1.021 (1.0002–1.042)	1.983	0.047	
Chemotherapy	
 No	Reference	1.000	–	–	
 Yes	−0.567	0.567 (0.392–0.820)	−3.012	0.003	

We incorporated FJS, WBC, CEA, Cyfra21-1, SCC, and chemotherapy into the multivariate Cox regression model. ROC analysis revealed that the AUCs for 1-year, 3-year, and 5-year mortality risks were 78.75 (69.13, 88.37), 72.53 (63.11, 81.96), and 80.79 (69.98, 92.61), respectively, indicating significant predictive capability (Fig. 3).Fig. 3 ROC analysis of multivariate cox regression model.

Fig. 3

To enhance the practicality and operational ease of the model, we depicted the multifactor Cox regression model graphically as a column chart (Fig. 1). The column graph facilitates the prediction of 1-, 3-, and 5-year mortality risks for patients with tumor.

3.4 Objective remission rate

In the analysis of the ORR, based on univariate analysis, we identified sex, Cyfra21-1 abnormality, and SCC abnormality as influencing factors, with no discernible impact of FJS on ORR. Furthermore, multivariate regression analysis did not reveal any influencing factors for the objective remission rate (Table 5).Table 5 Influencing factors of objective mitigation rate.

Table 5Variable	Univariate analysis	Multivariate analysis	
OR (95%CI)	P	OR (95%CI)	P	
Sex	
 Male	1.000	–			
 Female	3.133(1.33–7.377)	0.0090	2.14(0.837–5.475)	0.1121	
Age	0.972(0.936–1.011)	0.1577			
Age group	
 <60	1.000	–			
 60-69	0.555(0.195–1.58)	0.2704			
 70-79	0.421(0.125–1.412)	0.1611			
 ≥80	0.555(0.149–2.072)	0.3815			
Smoking history	
 No	1.000	–			
 Yes	0.598(0.254–1.409)	0.2396			
Drinking history	
 No	1.000	–			
 Yes	1.745(0.724–4.212)	0.2150			
TNM	
 III	1.000	–			
 IV	1.283(0.348–4.731)	0.7082			
Pathological pattern					
 Squamous	1.000	–			
 Adenocarcinoma	1.483(0.517–4.249)	0.4635			
EGFR mutations	
 No	1.000	–			
 Yes	1.355(0.587–3.129)	0.4757			
PS	0.801(0.513–1.251)	0.3298			
WBC	1.016(0.959–1.078)	0.5825			
HB	1.001(0.983–1.019)	0.8986			
PLT	1.001(0.997–1.005)	0.5704			
ALT	1.012(0.998–1.027)	0.0991			
AST	1.019(0.999–1.039)	0.0575			
ALB	1.02(0.94–1.108)	0.6249			
TG	1.212(0.673–2.182)	0.5227			
TCHO	1.221(0.919–1.621)	0.1679			
CEA	1(0.999–1.001)	0.5860			
CEA group	
 Normal	1.000	–			
 Abnormal	1.82(0.64–5.181)	0.2614			
CA199	1(1–1)	0.5643			
CA199 group	
 Normal	1.000	–			
 Abnormal	1.66(0.711–3.875)	0.2413			
Cyfra21-1	0.992(0.974–1.009)	0.3586			
Cyfra21-1 group	
 Normal	1.000	–	1.000	–	
 Abnormal	0.33(0.132–0.825)	0.0177	0.429(0.163–1.128)	0.0862	
SCC	0.963(0.877–1.057)	0.4288			
SCC group	
 Normal	1.000	–	1.000	–	
 Abnormal	0.365(0.138–0.968)	0.0427	0.51(0.179–1.451)	0.2071	
Chemotherapy	
 No	1.000	–			
 Yes	1.74(0.707–4.279)	0.2281			
Radiotherapy	
 No	1.000	–			
 Yes	0.73(0.296–1.802)	0.4946			
Targeted therapy	
 No	1.000	–			
 Yes	1.968(0.82–4.719)	0.1294			
Immunotherapy	
 No	1.000	–			
 Yes	1.923(0.622–5.944)	0.2560			
FJS	
 Yes	1.000	–			
 No	0.689(0.298–1.592)	0.3837			

4 Discussion

As commonly acknowledged, TCM stands as a distinctive modality in cancer treatment in China, serving as both an adjuvant and alternative approach for NSCLC. Clinical investigations have demonstrated that the integration of TCM with chemotherapy or targeted therapy in the management of NSCLC contributes to the mitigation of side effects, enhancement of patient treatment tolerance, and extension of survival time [[21], [22], [23], [24]].

Diverging from prior research, this study entailed an evaluation of the effectiveness of FJS in the treatment of patients with advanced NSCLC through a retrospective cohort study. The findings demonstrated that the survival time of patients in FJS group was extended compared to the control group. Despite no notable difference in the ORR between the two groups, suggesting that FJS does not impact patient survival by reducing tumor size, TCM emerges as a pivotal player in advanced tumor treatment, serving as a “healer” with distinct advantages. TCM stands as a crucial approach for prolonging survival and enhancing the quality of life for patients facing advanced tumors. Ongoing research continues to explore TCM's role in extending survival and improving patient well-being, aligning with the conclusions drawn from this study.

Our findings also affirm the efficacy of the “coexistence of humans and tumors” treatment model for advanced tumors with TCM. The notion of “survival with tumor” is a pivotal concept in the management of advanced malignant tumors, embodying the holistic principle of the unity of nature and human [25,26]. Pioneered by TCM master Zhou [27,28], the academic concept of “survival with tumor” was initially introduced in his “Experimental Collection of Cancer Therapeutics.” From the perspective of TCM, tumors are perceived as manifestations of essence deficiency and symptom excess. For instance, the approach to treating advanced NSCLC previously showcased a limited interpretation of “survival with tumor.” [29].

The clinical treatment objective of “survival with tumor” in TCM is consistent with the assessment criteria for solid tumor efficacy outlined by the World Health Organization, even in cases where clinical CR does not meet the standard of tumor-free status. For instance, Professor Guo Lihua demonstrated the treatment of lung adenocarcinoma patients solely with TCM over a 4-year clinical period, achieving SD [30,31]. The “Fu Zheng Jie Du Qu Yu” therapy for advanced NSCLC, as elucidated by Professor Jiang [32], exhibits precise therapeutic efficacy in clinical practice, effectively prolonging patient survival. This approach enables individuals with advanced NSCLC to lead extended and more comfortable lives alongside the presence of the tumor. The primary mechanisms involve tumor stabilization and symptom improvement, aligning with the objective of “survival with tumor” and consequently extending patient survival duration.

Collectively, FJS, classified under TCM, exhibits low toxicity, cost-effectiveness, and the ability to extend the survival duration in patients with advanced NSCLC. Being a TCM formulation, ongoing investigations are underway to assess its safety, affordability, and potential impact on the survival outcomes for individuals with advanced NSCLC. This exploration may broaden the array of treatment alternatives available for those facing advanced NSCLC. While this study offers initial insights into the role of TCM formulations in enhancing the survival prospects of advanced NSCLC patients, its retrospective nature imposes certain limitations. Primarily, retrospective studies rely on existing medical records, introducing the possibility of incomplete data and record biases, which could impact result accuracy. Ensuring uniformity in the treatment received across all patients is also challenging in retrospective analyses. The study lacks a comparison with standardized Western medical treatments, an essential aspect for substantiating the efficacy of the TCM formulation FJS. Furthermore, as a single-center study, the sample size may be restricted, and the process of patient selection could introduce regional and demographic biases, consequently limiting the generalizability of the findings. Additionally, while the primary outcome measures displayed positive trends, the secondary outcome indicator—ORR—did not achieve statistical significance, suggesting that the impact of the TCM formulation on disease amelioration may have limitations. This observation implies that the medication may have minimal direct effects on tumor reduction and could potentially exert its influence on enhancing the quality of life of patients through other biological mechanisms.

5 Conclusions

Despite its constraints, this study provides substantial insights into the utilization of TCM within the field of oncology. The results align with the Chinese medicine principle of “survival with tumor,” emphasizing not only disease remission but also the augmentation of life quality and survival duration. This convergence with contemporary cancer treatment trends underscores the significance of holistic well-being and integrative care for patients.

In upcoming research endeavors, we intend to initiate multicentric, prospective clinical trials to provide a more precise evaluation of the effectiveness of FJS in the treatment of advanced NSCLC. This approach will enable an assessment of the efficacy and safety of FJS across a broader and more diverse patient population. Furthermore, our objectives include delving into the potential mechanisms through which FJS influences tumor biology, paving the way for innovative therapeutic strategies for NSCLC. Future studies will also prioritize the assessment of quality-of-life indicators and the optimization of patient well-being through personalized treatment approaches, maintaining an equitable and objective perspective throughout the research. Nevertheless, this study is constrained by limitations stemming from time and staffing, including relatively modest sample sizes and the inclusion of patients from a single center. Subsequent prospective cohort studies encompassing multiple centers and larger sample sizes are imperative to comprehensively assess the efficacy of the FJS in the treatment of advanced NSCLC and to furnish supplementary data for randomized controlled trials. Despite the notable clinical efficacy demonstrated by FJS, its mechanism of action against lung cancer remains unclear, representing a shared challenge within the TCM approach to treating malignant tumors.

Ethics approval and consent to participate

This study was conducted with approval from the Ethics Committee of The Second Affiliated Hospital of Zhejiang Chinese Medical University (Approval Number: 2022research101-01). This study was conducted in accordance with the declaration of Helsinki. Written informed consent was obtained from all participants.

Consent for publication

Not applicable.

Funding

No external funding received to conduct this study.

Availability of data and materials

The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.

CRediT authorship contribution statement

Zhen Yan: Writing – original draft, Software, Formal analysis, Data curation. Wen-Cang Gao: Writing – review & editing, Validation, Formal analysis. Xiao-Xiao Wang: Writing – original draft, Software, Formal analysis. Hong-Quan Xu: Investigation, Formal analysis, Data curation. Qian Li: Writing – original draft, Software, Formal analysis. Jian-Xiang Chen: Writing – review & editing, Project administration, Conceptualization. De-Xiang Pang: Writing – review & editing, Visualization, Formal analysis. Tian Xie: Writing – review & editing, Resources, Conceptualization.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Abbreviations:

TNM tumor-node-metastasis

PS performance status

NRS numeric rating scales

WBC white blood cell

NE% Percentage of neutrophils

NEUT Neutrophil absolute

HB haemoglobin

PLT platelet count

ALT alanine transaminase

AST glutamic oxalic transaminase

ALB albumin

TBIL total bilirubin

TG triglyceride

TCHO total cholesterol

CEA carcinoembryonic antigen

AFP alpha fetoprotein

CA19-9 carbohydrate antigen 19-9

Cyfra21-1 cytokeratin 19 fragment 21-1

SCC squamous cell carcinoma associated antigen

Acknowledgements

We would like to thank the doctors at The Second Affiliated Hospital of Zhejiang Chinese Medical University for their work in this study. We also would like to thank the patients for participating in this study.
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