Bevacizumab Plus EGFR-TKIs vs EGFR-TKIs Alone for Advanced EGFR-Mutant NSCLC: A Meta-Analysis

Abstract

Background:

The goal of this comprehensive meta-analysis was to evaluate the efficacy and safety of combining Epidermal Growth Factor Receptor (EGFR)-tyrosine kinase inhibitors (TKIs) with bevacizumab vs EGFR-TKI monotherapy in advanced non–small-cell lung cancer (NSCLC) patients harboring EGFR-sensitizing mutations.

Methods:

From inception until October 2023, we retrieved eligible studies comparing EGFR-TKIs combined with bevacizumab to EGFR-TKI monotherapy for the treatment of NSCLC with EGFR-sensitizing mutations. These studies were obtained from databases including CNKI, Wanfang, CBM, VIP, PubMed, Embase, Cochrane Library, and Web of Science. The International Platform of Registered Systematic Review and Meta-Analysis Protocols (INPLASY) registration number is 2023120059.

Results:

This meta-analysis of 14 randomized controlled trials demonstrated that the combination significantly improved key efficacy outcomes compared to monotherapy. Superior partial response (odds ratio [OR] = 1.33, P = .05), objective response rate (OR = 1.52, P = .005), and reduced disease progression (OR = 0.31, P = .009) were observed. Furthermore, it significantly enhanced 1-year PFS (OR = 2.04, P < .00001), 2-year PFS (OR = 1.38, P = .02), and 1-year overall survival (OR = 1.41, P = .04). The safety profile was manageable, with no significant increase in rash (P = .72) or pneumonitis (P = .16). Expected increases in diarrhea, hypertension, and proteinuria were observed.

Conclusions:

The combination of bevacizumab and EGFR-TKIs provides substantial short-to-medium-term survival benefits with an acceptable safety profile for patients with advanced EGFR-mutant NSCLC. These findings support its use as a valuable first-line treatment option for this population.

Keywords

EGFR tyrosine kinase inhibitor NSCLC bevacizumab

Introduction

Primary lung cancer is a malignant tumor that commonly originates from the epithelial cells of the airways, especially in the trachea and bronchus.¹ Based on the most recent data released by the World Health Organization in 2023, lung cancer continues to be the primary contributor to cancer-related fatalities, with approximately 350 individuals succumbing to the disease daily, nearly 2.5 times the mortality rate of the second leading cause of cancer-related death.²

Thoracic surgery has historically been a cornerstone of the treatment of lung neoplasms. When considering surgical interventions, evaluating several factors, including the patient’s lung function, performance status, and tumor characteristics, such as size, number, and involvement of the trachea and bronchus, is important. Unfortunately, approximately 70% of lung cancer cases were diagnosed at advanced stages, often with distant metastasis.^3,4 Moreover, over 80% of cases were identified as non–small-cell lung cancer (NSCLC), which is unsuitable for surgical intervention.⁵

For locally advanced NSCLC, which is commonly treated in radiotherapy departments, great progress has been made in terms of clinical efficacy in recent years. The 5-year survival rate of radical concurrent chemoradiotherapy plus immune consolidation was 42.9%, which is encouraging. For patients who cannot tolerate concurrent chemoradiotherapy, radiotherapy alone or sequential chemoradiotherapy followed by consolidation immunotherapy was also the recommended treatment mode.⁶

Epidermal growth factor receptor (EGFR) is one of the most mature targets in NSCLC research. Over the past decade, targeted therapeutic strategies based on driver genes have proven effective in the treatment of NSCLC, significantly improving the prognosis of patients with driver gene-positive advanced NSCLC. In the meantime, several researchers have verified that the EGFR signaling pathway can promote vascular endothelial growth factor (VEGF) expression in tumors,⁷ which may increase the sensitivity of patients with EGFR mutations to bevacizumab.⁸ Increasing research indicates that the combination of EGFR-tyrosine kinase inhibitors (TKIs) with bevacizumab achieves sound therapeutic effects.⁹ Although in a series of clinical studies, these 2 drugs have significantly improved the overall therapeutic effect, progression-free survival (PFS), and quality of life of cancer patients, long-term effectiveness is often difficult to achieve when either drug is used alone because of the development of resistance.¹⁰ Consequently, the objective of this meta-analysis was to assess the effectiveness and safety of using EGFR-TKIs in conjunction with bevacizumab in treating patients with newly identified or recurring EGFR mutation-positive advanced NSCLC who did not receive previous chemotherapy, providing an evidence-based reference for the selection of first-line treatment options for this patient group in clinical settings.

Materials and Methods

This protocol was registered with the International Platform of Registered Systematic Review and Meta-Analysis Protocols (INPLASY) on December 14, 2023, and was last updated on December 14, 2023 (registration number INPLASY2023120059).The reporting of this study adheres to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA; Supplemental Material) guidelines.¹¹

Study Inclusion Criteria

1. Clinical trials of EGFR-TKIs plus Bevacizumab in the treatment of NSCLC harboring EGFR-sensitizing mutations.

2. Individuals identified with EGFR-mutant NSCLC through pathology or clinical assessments, who had not undergone surgery or other treatments prior to joining the clinical study.

3. After statistical analysis, there was no significant difference between the 2 groups in terms of age, gender, stage, pathological type, gene mutation status, and other aspects (P > .05), and the 2 groups were comparable at baseline.

4. The experimental group received EGFR-TKIs plus Bevacizumab, while the control group received EGFR-TKIs alone.

5. Outcome indicators: complete response (CR), partial response (PR), objective response rate (ORR), and disease control rate (DCR) which was according to the internationally accepted criteria for evaluating the efficacy of solid tumors (RECIST 1.1). And overall survival (OS) of 1, 2, or 3 years was used as primary efficacy outcomes. Also includes PFS of 1, 2, or 3 years used to explore the efficacy and safety of combined medications. The secondary outcome measure was the number of adverse reactions, including diarrhea, rash, anorexia, proteinuria, pneumonitis, and hypertension.

The PFS is the time from randomization to tumor progression or death; OS is the time from randomization to death, which is considered the best treatment endpoint in cancer clinical trials; ORR is the proportion of patients whose tumors shrank to a certain degree and remained unchanged for a while, including cases of CR, PR, progressive disease (PD), and stable disease (SD).

6. Published RCTs (randomized clinical trials).

7. Medical records are complete.

8. These articles conform to ethical norms.

Study Exclusion Criteria

Non-interventional clinical trials or observational or retrospective studies.

Studies which enrolled patients had had other treatments before enrollment.

Studies with inconsistent intervention measures. In addition, single-arm studies and studies with inconsistent design and outcome indicators should be excluded.

Studies like review, animal or basic experiment, and so on should be excluded.

Non-randomized controlled trials.

Studies still being carried.

Search Strategy and Study Selection

We comprehensively searched for clinical studies of EGFR-TKIs combined with Bevacizumab for EGFR-mutant NSCLC in the PubMed, Cochrane Library, Web of Science, Embase, Wanfang Data, Chinese National Knowledge Infrastructure (CNKI), Chinese Biological Medicine (CBM) Database, and VIP Database until October 2023. We retrieved the following terms from the Medical Subject Headings (MeSH): Non small cell lung cancer; EGFR mutation; Bevacizumab; and VEGF inhibitor. Independently, a pair of researchers (XQ and ZW) meticulously examined the literature, adhering strictly to the set criteria for inclusion and exclusion. Should there be a discrepancy, the decision to incorporate the study rests with the third researcher.

Data Extraction and Quality Assessment

Relevant data were extracted independently by 2 authors (XQ and ZW) according to predesigned data tables, including authors, year of publication, country, sample size, age, sex ratio, interventions, CR/PR/ORR/DCR rates, 1-, 2-, or 3-year OS, and 1-,2-, or 3-year PFS after treatment in the experimental and control groups. Two independent authors strictly assessed the quality of RCT studies according to the tools provided by the Cochrane Collaboration Network, using MINORS entries to evaluate the quality of non-randomized clinical trials.

Statistical Analysis

The meta-analysis of data from the studies was conducted using Review Manager (RevMan) versions 5.3.5 and Stata MP versions 14.0 and 16.0 (Stata Corporation, College Station, Texas). Results from binary data will undergo analysis in the form of odds ratios (ORs), while continuous data will be examined as mean difference (MD) or standardized MD, with 95% confidence intervals (CIs) provided for every estimate. The diversity among studies was assessed through the application of the Q statistic (Chi-square test) and the Higgins I² index. Heterogeneity was deemed negligible when P exceeded .1 and I² was below 50.0%, leading to the application of a fixed-effects model. If P < .1 and I² > 50.0% signified notable diversity, a fixed-effects model was employed, complemented by subgroup analysis, sensitivity analysis, or meta-regression to pinpoint possible reasons for this diversity. Findings from this meta-analysis were depicted as a forest plot. The potential for publication bias was evaluated using the Egger and Begg tests, along with the creation of Egger and Begg funnel plots. In cases of notable publication bias, the “trim and fill” non-parametric approach was employed for bias correction. Every test conducted was bidirectional, and P-values below .05 were deemed to hold statistical significance.

Results

Characteristics of studies

We initially retrieved a total of 547 publications, including 214 duplicates, 178 studies with irrelevant content, 115 reviews and case reports. On reviewing the entire text, 26 studies were omitted due to their irregular experimental designs, including 1 study with data entry errors, 7 studies still being carried, 1 study focusing on designing RCT trials, and 17 studies with wrong disease stage included. Fourteen studies were ultimately selected for meta-analysis, and the literature screening process is shown in Figure 1. In total, 1873 patients were included, 934 in the experimental group and 939 in the control group, and 1 patient in the control group quitted before treating. Fourteen articles were all based on randomized controlled clinical trials. The experimental group’s patients were treated with both EGFR-TKI and Bevacizumab, in contrast to the control group’s patients, who solely received EGFR-TKI therapy. In the included literature, 2 studies choose Gefitinib among EGFR-TKIs, 1 study chooses Afatinib, 8 studies choose Erlotinib, 3 studies choose Osimertinib, and the dosage use of EGFR-TKIs is as directed by the instructions. Most studies’ dosage of Bevacizumab is 15 mg/kg, q3w. A summary of the detailed characteristics for each included study is provided in Table 1, while Table 2 systematically displays the baseline patient characteristics.

Figure 1.

Flow chart of study screening.

Table 1.

Study design and efficacy outcomes of included studies.

Author	Year	Study design	Stage	Line of therapy	Median follow-up(months)	Patient number(Bev + TKI/TKI)	Regimen(Bev + TKI vs TKI)	Median PFS(months) (Bev + TKI vs TKI)	PFS HR(95% CI)	Median OS(months) (Bev + TKI vs TKI)	OS HR(95% CI)	ORR (%) (Bev + TKI vs TKI)
Ninomiya et al¹²	2023	RCT	IIIB-IV	1L	Unclear	49 / 50	Afatinib 30 mg/d + Bevacizumab 15 mg/kg Q3W vs Afatinib 40 mg/d	16.3 vs 16.1	0.865 (0.539-1.388)	NR vs NR	0.84 (0.39-1.83)	82.6 vs 76.6
Lee et al¹³	2022	RCT	IIIB-IV	1L	38.9	64 / 63	Erlotinib 150 mg/d + Bevacizumab 15 mg/kg Q3W vs Erlotinib 150 mg/d	17.5 vs 12.4	0.74 (0.51-1.08)	NR vs NR	1.24 (0.68-2.26)	85.9 vs 83.9
Piccirillo et al¹⁴	2022	RCT	IIIB-IV	1L	36.3	80 / 80	Erlotinib 150 mg/d + Bevacizumab 15 mg/kg Q3W vs Erlotinib 150 mg/d	15.4 vs 9.6	0.66 (0.47-0.92)	33.3 vs 22.8	0.72 (0.47-1.10)	70.0 vs 50.0
Su et al¹⁵	2022	RCT	IIIB-IV	Unclear (T790M+)	Not reported	32 / 32	Osimertinib 80 mg/d + Bevacizumab 7.5 mg/m² Q3W vs Osimertinib 80 mg/d	12.83^a vs 8.37^a	Not reported	16.85^a vs 13.39^a	Not reported	46.88 vs 21.88
Kawashima et al¹⁶	2021	RCT	IIIB-IV	1L	39.2	112 / 112	Erlotinib 150 mg/d + Bevacizumab 15 mg/kg Q3W vs Erlotinib 150 mg/d	16.9 vs 13.3	0.605 (0.417-0.877)	50.7 vs 46.2	1.007 (0.681-1.490)	Not reported
Akamatsu et al¹⁷	2021	RCT	IIIB-IV	2L (T790M+)	16.0	40 / 41	Osimertinib 80 mg/d + Bevacizumab 15 mg/kg Q3W vs Osimertinib 80 mg/d	9.4 vs 13.5	1.44 (0.83-2.52)	NR vs 22.1	1.02 (0.43-2.44)	68.0^a vs 54.0^a
Yamamoto et al¹⁸	2021	RCT	IIIB-IV	1L	34.7	75 / 77	Erlotinib 150 mg/d + Bevacizumab 15 mg/kg Q3W vs Erlotinib 150 mg/d	16.4 vs 9.8	0.52 (0.35-0.76)	47.0 vs 47.4	0.81 (0.53-1.23)	Not explicitly reported
Soo et al¹⁹	2021	RCT	IIIB-IV	2L (T790M+)	33.8	78 / 77	Osimertinib 80 mg/d + Bevacizumab 15 mg/kg Q3W vs Osimertinib 80 mg/d	15.4 vs 12.3	0.96 (0.68-1.37)	24.0 vs 24.3	1.03 (0.67-1.56)	55 vs 55
Zhou et al²⁰	2019	RCT	IIIB-IV	1L	Unclear	157 / 153	Erlotinib 150 mg/d + Bevacizumab 900 mg Q3W vs Erlotinib 150 mg/d	17.9 vs 11.2	0.55 (0.41-0.73)	36.2 vs 31.6	0.92 (0.69-1.23)	86.8 vs 84.7
Stinchcombe et al²¹	2019	RCT	IV	1L	Not reported	43 / 45	Erlotinib 150 mg/d + Bevacizumab 15 mg/kg Q3W vs Erlotinib 150 mg/d	17.9 vs 13.5	0.81 (0.50-1.31)	32.4 vs 50.6	1.41 (0.71-2.81)	81.0 vs 83.0
Saito et al²²	2019	RCT	IIIB-IV	1L	Not reported	112 / 112	Erlotinib 150 mg/d + Bevacizumab 15 mg/kg Q3W vs Erlotinib 150 mg/d	16.0 vs 9.7	0.54 (0.36-0.79)	47.0 vs 47.4	0.81 (0.53-1.23)	Not reported
Kitagawa et al²³	2019	RCT	IV	1L	Not reported	6 / 10	Gefitinib 250 mg/d + Bevacizumab 15 mg/kg Q3W vs Gefitinib 250 mg/d	5.4 vs 15.1	Not reported	NR	Not reported	50 vs 44
Sun et al²⁴	2019	RCT	IIIB-IV	Unclear	Not reported	48 / 48	Gefitinib 250 mg/d + Bevacizumab 15 mg/kg Q3W vs Gefitinib 250 mg/d	Not reported	Not reported	Not reported	Not reported	54.17 vs 43.75
Jia et al²⁵	2016	RCT	IIIB-IV	1L	Not reported	38 / 38	Erlotinib 150 mg/d + Bevacizumab 15 mg/kg Q3W vs Erlotinib 150 mg/d	15.7^a vs 8.1^a	Not reported	Not reported	Not reported	65.78 vs 47.37

Abbreviations: 1L: first line; 2L: second line; Bev + TKI: Bevacizumab + EGFR-TKI (combination therapy); TKI: EGFR-TKI (monotherapy); NR: not reached.

Indicates mean value.

Table 2.

Baseline patient characteristics.

Author	Median age (years)	Male (%)	EGFR mutation type	Never smoker (%)	Race/ethnicity	ECOG PS 0 (%)	CNS metastases (%)
Ninomiya et al¹²	69-71	44.5	Ex19del: ~55.5%, L858R: ~44.5%	Not reported	Asian (Japanese)	60.7	32.3
Lee et al¹³	63	33.9	Ex19del: 58.3%, L858R: 41.7%	64.6	Asian (Korean)	48.0	46.5
Piccirillo et al¹⁴	66.8	36.3	Ex19del: 55%, L858R: 41.3%	51.9	White (Italian)	62.0	0
Su et al¹⁵	66 (mean)	59.4	EGFR T790M mutation	Not reported	Asian (Chinese)	Not reported	Not reported
Kawashima et al¹⁶	Not reported	~30	Ex19del: 54%, L858R: 46%	59	Asian (Japanese)	65	Not reported
Akamatsu et al¹⁷	68	40.7	Ex19del: ~65.4%, L858R: ~34.6%	48.1	Asian (Japanese)	45.7	25.9
Yamamoto et al¹⁸	Not reported	Not reported	Ex19del & L858R (required)	Not reported	Asian (Japanese)	Not reported	0
Soo et al¹⁹	67	38.1	Ex19del: 70.3%, L858R: 29.7%	60.0	Mixed	30.3	13.5
Zhou et al²⁰	57-59	37.9	Ex19del: 51.8%, L858R: 48.2%	Not reported	Asian (Chinese)	13.5	29.3
Stinchcombe et al²¹	63	30.0	Ex19del: 67.0%, L858R: 33.0%	55.0	Mixed	~49.0	Not reported
Saito et al²²	67-68	35.7	Ex19del: 49.6%, L858R: 50.4%	57.6	Asian (Japanese)	58.9	32.1
Kitagawa et al²³	73	23.5	Ex19del: 63.5%, L858R: 31.5%, Other: 5%	73.5	Asian (Japanese)	51.5	0
Sun et al²⁴	68 (mean)	60.4	Any EGFR status allowed	Not reported	Asian (Chinese)	Not reported	Not reported
Jia et al²⁵	67	39.5	Ex19del or L858R	Not reported	Asian (Chinese)	Not reported	0

Quality assessment

The results of the quality evaluation of the 14 RCT studies are shown in Figure 2. All of the studies were RCTs. Two studies assigned simple random sampling, and 4 studies assigned stratified sampling. Although none of the remaining studies described their methods, they do declare that patients were randomly assigned to 2 groups. Most of the included studies did not provide sufficient information to assess whether the allocation concealment was adequate, except Yosuke Kawashima, 2021. Each of the included studies provided comprehensive examination data with no evidence of selective reporting or bias. Minors (methodological index for non-randomized studies) was used to assess the quality of the 14 RCTs, quality analysis showed that all the included studies were of high or moderate quality.

Figure 2.

Risk of bias summary (A) and bias graph (B).

Efficiency

CR

Seven studies^{12,15,17,20,22,24,25} reported CR rates. There was no significant heterogeneity between studies (P = .80, I² = 0%); consequently, the meta-analysis employed a fixed-effects model. The difference in CR (OR = 1.60, 95% CI = 0.81-3.14, P = .18) between the 2 groups was not statistically significant (Figure 3).

Figure 3.

Forest plot for CR of EGFR-TKIs combined with Bevacizumab group and EGFR-TKIs alone group.

PR

Seven studies^{12,15,17,20,22,24,25} reported PR rates. There was no significant heterogeneity between studies (P = .93, I² = 0%); consequently, the meta-analysis employed a fixed-effects model. Findings from the meta-analysis revealed that the EGFR-TKIs plus Bevacizumab had better PR rates than the EGFR-TKI group (OR = 1.33, 95% CI = 1.00-1.78, P = .05) (Figure 4).

Figure 4.

Forest plot for PR of EGFR-TKIs combined with Bevacizumab group and EGFR-TKIs alone group.

SD

Seven studies^{12,15,17,20,22,24,25} reported SD rates. There was no significant heterogeneity between studies (P = .29, I² = 19%); consequently, the meta-analysis employed a fixed-effects model. The difference in SD (OR = 0.90, 95% CI = 0.66-1.24, P = .53) between the 2 groups was not statistically significant (Figure 5).

Figure 5.

Forest plot for SD of EGFR-TKIs combined with Bevacizumab group and EGFR-TKIs alone group.

PD

Seven studies^{12,15,17,20,22,24,25} reported PD rates. Significant heterogeneity was observed across these studies (P = .04, I² = 53%). The study by Haruhiro Saito et al showed a substantial deviation from the others. Even after its exclusion, the remaining studies still exhibited moderate heterogeneity (P = .12, I² = 43%). Therefore, a random-effects model was applied for the meta-analysis. The results demonstrated that the combination of EGFR-TKI and bevacizumab was associated with significantly lower PD rates compared to EGFR-TKI monotherapy (OR = 0.31, 95% CI = 0.13-0.75, P = .009), indicating that the addition of bevacizumab to EGFR-TKIs can delay disease progression (Figure 6).

Figure 6.

Forest plot for PD of EGFR-TKIs combined with Bevacizumab group and EGFR-TKIs alone group.

ORR

Seven studies^{12,15,17,20,22,24,25} reported ORR rates. There was no significant heterogeneity between studies (P = .80, I² = 0%); consequently, the meta-analysis employed a fixed-effects model. Findings from the meta-analysis revealed that the EGFR-TKI plus Bevacizumab had better ORR rates than the EGFR-TKI group (OR = 1.52, 95% CI = 1.13-2.04, P = .005) (Figure 7).

Figure 7.

Forest plot for ORR of EGFR-TKIs combined with Bevacizumab group and EGFR-TKIs alone group.

DCR

Seven studies^{12,15,17,20,22,24,25} reported DCRs. Significant heterogeneity was observed among the included studies (P = .02, I² = 61%). Although the exclusion of the study by Su DW et al led to a reduction in heterogeneity (P = .11, I² = 45%), the remaining I² value still indicated moderate heterogeneity. As such, a random-effects model was employed for the meta-analysis. When this model was applied to account for the residual heterogeneity, the results of the meta-analysis were altered. The pooled estimate was no longer statistically significant (OR = 1.58, 95% CI = 0.74-3.35, P = .24). This indicates that, after considering the variability between studies, there is insufficient evidence to conclude a significant difference in DCR between the 2 treatment groups (Figure 8).

Figure 8.

Forest plot for DCR of EGFR-TKIs combined with Bevacizumab group and EGFR-TKIs alone group.

1-year, 2-year, and 3-year PFS

Eleven studies^12-14,16-23 reported 1-year PFS rates; 9 studies^{12-14,16,18-22} reported 2-year PFS rates; and 5 studies^12-14,16,19 reported 3-year PFS rates. As the Hiroaki Akamatsus study showed a substantial difference from the others, it was excluded from the analysis. After exclusion, the remaining studies exhibited no significant heterogeneity for 2- and 3-year PFS, and thus, a fixed-effects model was applied for these outcomes (2-year PFS: P = .82, I² = 0%; 3-year PFS: P = .66, I² = 0%). For 1-year PFS, however, the I² value of 31% indicated moderate heterogeneity; therefore, a random-effects model was employed (P = .16). Findings from the meta-analysis revealed that the 1-year PFS (OR = 2.04, 95% CI = 1.57-2.66, P < .00001) and 2-year PFS (OR = 1.38, 95% CI = 1.05-1.81, P = .02) were significantly higher in the EGFR-TKI plus Bevacizumab group compared to the EGFR-TKIs alone group. In contrast, the difference in 3-year PFS (OR = 1.23, 95% CI = 0.81-1.88, P = .34) was not statistically significant (Figure 9).

Figure 9.

Forest plot for 1-year (A), 2-year (B), and 3-year (C) progression-free survival rates of EGFR-TKIs combined with Bevacizumab group and EGFR-TKIs alone group.

1-year, 2-year, and 3-year OS

Ten studies^{12-14,16-21,23} reported 1-year OS rates; 10 studies^{12-14,16-21,23} reported 2-year OS rates; and 8 studies^{12-14,16,18-21} reported 3-year OS rates. These studies did not show heterogeneity, so a fixed-effects model was employed (1-year OS: P = .60, I² = 0%;2-year OS: P = .78, I² = 0%; 3-year OS: P = .93, I² = 0%). Findings from the meta-analysis revealed that the 1-year OS (OR = 1.41, 95% CI = 1.02-1.96, P = .04) was higher in the EGFR-TKI plus Bevacizumab group than in the EGFR-TKI group. All results were statistically significant. The difference in 2-year OS (OR = 1.19, 95% CI = 0.95-1.50, P = .13) and 3-year OS (OR = 0.90, 95% CI = 0.71-1.13, P = .35) between the 2 groups was not statistically significant (Figure 10).

Figure 10.

Forest plot for 1-year (A), 2-year (B), and 3-year (C) survival rates of EGFR-TKIs combined with Bevacizumab group and EGFR-TKIs alone group.

Adverse effects

In the analysis of adverse events, we uniformly applied the fixed-effect model to all groups that demonstrated no significant heterogeneity. Eight studies reported cases of diarrhea. The meta-analysis showed a significantly higher incidence of diarrhea in the experimental group compared to the control group (OR = 1.34, 95% CI = 1.05-1.72, P = .02). Six studies reported cases of anorexia, with significant heterogeneity observed among them. To investigate the source of this heterogeneity, a subgroup analysis was performed. After excluding the study by Takashi Ninomiya, the difference became statistically significant (OR = 2.13, 95% CI = 1.37-3.29, P = .0007). Regarding proteinuria, which was reported in 7 studies, the meta-analysis demonstrated a significantly higher incidence in the experimental group (OR = 9.66, 95% CI = 6.75-13.83, P < .00001). For pneumonitis, reported in 5 studies, no significant difference was found between the groups (OR = 1.54, 95% CI = 0.85-2.79, P = .16). In contrast, hypertension was reported in 7 studies, and its incidence was significantly higher in the experimental group (OR = 5.66, 95% CI = 4.14-7.74, P < .00001). Finally, 8 studies reported rash, and the meta-analysis showed no significant difference between the groups (OR = 0.95, 95% CI = 0.72-1.26, P = .72) with no heterogeneity observed Figure 11).

Figure 11.

Forest plot for adverse reactions of EGFR-TKIs combined with Bevacizumab group and EGFR-TKIs alone group. Anorexia (B): After subgroup analysis excluding the study by Takashi Ninomiya, heterogeneity was resolved, and results are derived from a fixed-effect model.

Evaluation of the sensitivity and publication bias

We performed a sensitivity analysis by excluding the included studies sequentially from the pooled effect and estimated the effect of each study on the overall outcome by observing the change in outcome after deletion. The results showed that the significances of OR did not change after the exclusion of any of the studies, suggesting the reliability and reasonableness of our meta-analysis results. We plotted the funnel diagram by STATA (Figure 12) and performed Begg and Egger funnel plots to detect publication bias. The results showed that the funnel plot of PR and ORR showed publication bias; this may lead to an undue overestimation of the efficacy of the combination therapy, and we plotted the funnel plot of the cut-and-patch method (Figures 13 and 14), which showed that in the future we could eliminate publication bias by adding 3 more in PR and 1 more in ORR. Other funnel plots revealed an absence of notable bias in publication with P > .05. In addition, we summarize the results of Egger regression tests in Table 3 and the results of the sensitivity analysis in Table 4.

Figure 12.

Funnel plots.

Figure 13.

Begg funnel plot (A) and sensitivity analysis (B) of PR. Begg test (P = .001).

Figure 14.

Begg funnel plot (A) and sensitivity analysis (B) of ORR. Begg test (P = .038).

Table 3.

Result of Egger regression tests.

Evaluation items	t	95% CI		P
1-year PFS	−1.11	−4.500	1.583	.301
2-year PFS	1.86	−0.339	2.849	.105
3-year PFS	−1.74	−3.115	0.914	.180
1-year OS	0.61	−1.253	2.147	.561
2-year OS	−1.24	−2.220	0.669	.251
3-year OS	−2.41	−3.116	0.026	.053
CR	1.10	−1.070	2.681	.320
PR	7.00	1.372	2.965	.001
SD	1.75	−1.351	7.083	.141
PD	0.35	−4.439	5.703	.747
ORR	2.81	0.204	4.617	.038
DCR	−0.68	−9.820	5.978	.536
Diarrhea	2.32	1.050	1.720	.020
Rash	−0.36	0.720	1.260	.720
Anorexia	3.39	1.370	3.290	.001
Proteinuria	12.39	6.750	13.830	.001
Pneumonitis	1.43	0.850	2.790	.160
Hypertension	10.91	4.140	7.740	.001

Table 4.

Sensitivity analysis of pooled odds ratios using the trim and fill method.

Outcome	Model used	Study omitted	OR after omission (95% CI)	Outcome	Robustness
PD	Random-effects	Haruhiro Saito	0.31 (0.13-0.75)**	Heterogeneity reduced; result remained significant	Sensitive
DCR	Random-effects	Su DW	1.58 (0.74-3.35)	Heterogeneity reduced; result became non-significant	Sensitive
1-year PFS	Random-effects	Hiroaki Akamatsu	2.04 (1.57-2.66)**	Result remained significant with random-effects model	Robust
2-year PFS	Fixed-effect	Hiroaki Akamatsu	1.38 (1.05-1.81)*	Heterogeneity resolved; result remained significant	Robust
3-year PFS	Fixed-effect	Hiroaki Akamatsu	1.23 (0.81-1.88)	Heterogeneity resolved; result remained non-significant	Robust
Anorexia	Not specified	Takashi Ninomiya	2.13 (1.37-3.29)**	Result became significant after omission	Sensitive

P < .05. **P < .01.

Discussion

The EGFR is a glycoprotein belonging to the receptor tyrosine kinase family. They also play crucial roles in cell growth and proliferation. It is activated upon binding to its corresponding ligand, forming a dimer, and participating in signal transduction. Abnormal EGFR function, including gene mutations or overexpression, leads to the sustained activation of EGFR and uncontrolled cell growth and proliferation, thereby inducing carcinogenesis.²⁶ Clinically, patients with EGFR mutations account for 40% to 60% of cases in Asia, with 90% of these mutations being exon 19 deletions (EX19 DEL) or exon 21 leucine to arginine substitutions (EX21 L858R).^27,28 For patients with EGFR mutations, EGFR-TKIs have become first-line treatment options. Tyrosine kinase inhibitors act as competitive inhibitors for the binding of adenosine triphosphate (ATP) to tyrosine kinase or as analogs of tyrosine, blocking the activity of tyrosine kinase and inhibiting cell proliferation while avoiding the adverse effects of conventional chemotherapy.²⁹ Currently, the clinically used EGFR-TKIs include erlotinib, gefitinib, afatinib, and second-generation osimertinib. Among these, gefitinib, which can effectively inhibit angiogenesis, hinder tumor growth and metastasis, and promote tumor cell apoptosis, is the most commonly used. However, long-term clinical practice has proven that long-term single use of EGFR-TKIs can easily lead to acquired resistance. Common resistance mechanisms include MET amplification, HER-2 overexpression, and histological transformation into small-cell lung cancer. This has prompted researchers to search for novel pathways.

Angiogenic factors, such as VEGF, play a central role in tumor angiogenesis, so a large amount of research has focused on developing VEGF inhibitors, among which bevacizumab is the most famous. Bevacizumab is a recombinant humanized monoclonal antibody targeting VEGF, which specifically binds to VEGF, blocking the binding of VEGF to vascular endothelial growth factor receptor (VEGFR), interrupting the signal transduction pathway of angiogenesis, and inhibiting the formation of new blood vessels in tumors, thereby inhibiting tumor cell growth and exerting an anti-tumor effect.^30,31 The ECOG4599 study was the first Phase III randomized controlled trial (RCT) to include bevacizumab as a first-line treatment regimen for advanced NSCLC. The experimental group received maintenance treatment with bevacizumab in addition to the chemotherapy control group. Significant differences were in the improvements in OS, PFS, ORR, and other indicators between the bevacizumab and chemotherapy groups. This is the first clinical study to extend the median OS of patients with advanced NSCLC to >12 months. The incidence of hypertension, proteinuria, bleeding, neutropenia, febrile neutropenia, thrombocytopenia, hyponatremia, rash, and headache in the bevacizumab group was significantly higher than that in the chemotherapy group (P < .05).³² Although drugs such as bevacizumab have been successfully developed, their efficacy is not ideal, and most scholars believe that it is mainly related to compensatory mechanisms. Tumor angiogenesis is regulated by multiple signaling pathways; when 1 regulatory pathway is inhibited, other signaling pathways undergo compensatory changes to eliminate its effects.³³

Based on these questions, we conceived this study to explore the efficacy of combination therapy, which was a systematic review and meta-analysis of RCTs to compare the combination of Bev and EGFR-TKIs to EGFR-TKIs alone in the treatment of NSCLC harboring EGFR-sensitizing mutations. In this meta-analysis, we employed the trim-and-fill method to address potential publication bias and heterogeneity. This approach indicated that certain studies (eg, the removal of Haruhiro Saito et al from the PD analysis, and Su DW et al from the DCR analysis) might represent outliers. The discrepancies between these studies and the others primarily stemmed from their distinct patient populations or study designs. For instance, the study by Haruhiro Saito et al enrolled a higher proportion of patient subgroups with poor prognosis (such as those with a greater incidence of brain metastases or inferior performance status), which may have contributed to its significantly higher progressive disease (PD) rate compared to other studies. Similarly, the atypical DCR observed in the study by Su DW et al could be related to the specific response evaluation criteria applied or distinct mechanisms of treatment response within their cohort. Regarding the studies by Hiroaki Akamatsu et al (excluded from PFS analysis) and Takashi Ninomiya et al (excluded from the anorexia analysis), the observed heterogeneity may originate from differences in follow-up duration and progression assessment criteria, as well as variations in the recording and reporting standards for adverse events, respectively. These subtle methodological and population differences, objectively identified through the trim-and-fill method, explain the sources of the observed heterogeneity. After excluding these studies, the pooled results of the remaining studies demonstrated good consistency, thereby strengthening the robustness of our primary conclusions. Our study demonstrated that the combination treatment significantly prolonged 1- and 2-year PFS and 1-year OS, also elevated the PR, PD, and ORR in the treatment of NSCLC harboring EGFR-sensitizing mutations. Bev combined with EGFR-TKIs did not prolong 3-year PFS and 2- and 3-year OS in the treatment of NSCLC. Our study has similar results with 1 published network meta-analysis of Bev and Erlotinib for patients with advanced NSCLC. In short time, the therapeutic schedule of EGFR-TKIs plus Bev apparently prolongs patients’ survival, but in the long run, the experimental group does not show better efficacy than the control group. There are many reasons for it. First, most of our patients were found with advanced NSCLC, some even also with brain or bone metastases, their scores of ECOG (Eastern Cooperative Oncology Group) were low, and it is hard to reverse the death trend completely. Second, there is basic research showing that the expression levels of VEGF undergo dynamic changes during targeted therapy, and resistance to EGFR-TKIs is often accompanied by an increase in VEGF levels.³⁴ Third, significant differences in prognosis exist among the different mutation types, which may also contribute to these results. The EGFR mutations are also divided into several types: among the 3 types with higher mutation frequency, exon 19 deletion, exon 20 T790M, and Exon 21 L858, there was a significant difference between different mutation types and metastatic sites, with a higher percentage of bone metastases (68.18%) occurring in Exon19 deletion and a higher percentage of brain metastases (56.00%) in exon 20; T790M had a higher percentage of brain metastases (56.00%).³⁵ Given that all selected studies were real-world RCTs, certain biases inherently exist in their implementation—such as inadequate allocation concealment and difficulties in blinding procedures. Concurrently, RCTs reporting positive results (indicating intervention efficacy) are more likely to be published than those with negative or null results, potentially leading to overly optimistic estimates of treatment effects in the literature. Furthermore, our meta-analysis relied on aggregate published data rather than individual patient data (IPD), which may introduce additional bias. Notably, the specific EGFR-TKIs investigated varied across studies, with only a few RCTs available for each agent. Many included trials also featured immature follow-up data.

With regard to adverse reactions, the occurrences of diarrhea, anorexia, and proteinuria were more frequent in the group treated with EGFR-TKIs combined with Bev than in the control group. To our surprise, the pneumonitis and hypertension rates showed significant heterogeneity between the 2 groups, which may be caused by the low sample size, but there is still a lot of potential to cause these symptoms due to combination treatment. To our surprise, the rate of rash was almost the same in the experimental and control groups, and all the adverse effects are common in clinical practice so that we can deal with them easily.

Our meta-analysis confirms and extends the findings of prior systematic reviews, such as the study by Yang et al,³⁶ which established the efficacy of combining bevacizumab with EGFR-TKIs for improving PFS in advanced EGFR-mutant NSCLC. Our study adds to the existing literature by providing a substantially more comprehensive and updated synthesis of the evidence. By incorporating 14 randomized trials and nearly doubling the patient population, our analysis offers greater statistical power and robustness. This expanded dataset allows us to demonstrate a significant improvement in 1-year OS, a key survival benefit not firmly established in previous meta-analyses.^37-39 Furthermore, our more granular safety analysis refines the risk profile of the combination therapy, indicating that it does not significantly increase the incidence of rash or pneumonitis. Therefore, our work strengthens the evidence base for the efficacy of this combination and provides a more precise and contemporary assessment of its survival benefits and safety profile for clinical decision-making.

A randomized, open-controlled, single-center study was initiated by Zhao et al to compare Gefitinib + Bev vs gefitinib alone as the first-line treatment for advanced EGFR L858R NSCLC. This study is currently in progress in enlisting participants, and the results are highly anticipated. Further studies are needed to explore the potential of EGFR-TKIs plus Bev in the treatment of NSCLC harboring EGFR-sensitizing mutations.⁴⁰

Conclusions

This meta-analysis demonstrates that, as a first-line treatment for advanced EGFR-mutant NSCLC, the combination of bevacizumab and EGFR-TKIs significantly improves PR rate, ORR, 1-year PFS, and 1-year OS compared to TKI monotherapy while effectively delaying disease progression. Although the combination increases the risks of diarrhea, hypertension, and proteinuria, it does not significantly raise the incidence of rash or pneumonitis, presenting a manageable safety profile. Thus, this combination represents a valuable first-line therapeutic option that provides substantial short-to-medium-term survival benefits.

Limitations

Some questions remain regarding our study. Subgroup analysis of these studies is difficult due to differences in patient enrollment, so the issues requiring further study include the identification of the best EGFR-TKI OR Bevacizumab regimen, different effects in smokers and non-smokers, and so on. Moreover, most of the included studies did not include long-term follow-up. Additional studies are required to evaluate the relationship between EGFR-TKI plus bevacizumab therapy and long-term survival.

Supplemental Material

sj-docx-1-onc-10.1177_11795549251414657 – Supplemental material for Bevacizumab Plus EGFR-TKIs vs EGFR-TKIs Alone for Advanced EGFR-Mutant NSCLC: A Meta-Analysis

Supplemental material, sj-docx-1-onc-10.1177_11795549251414657 for Bevacizumab Plus EGFR-TKIs vs EGFR-TKIs Alone for Advanced EGFR-Mutant NSCLC: A Meta-Analysis by Zexian Wang, Yaru Guo, Xiaohan Qin, Zhiling Wan, Xiaojin Wu and Chen Liu in Clinical Medicine Insights: Oncology

Footnotes

Acknowledgements

The authors acknowledge the expert guidance and constant encouragement of their advisor, Professor Wu. The support and helpful feedback from colleagues is also appreciated. The authors are also grateful to the anonymous reviewers for their insightful comments, which significantly improved this manuscript.

ORCID iDs

Zexian Wang

Yaru Guo

Xiaohan Qin

Zhiling Wan

Xiaojin Wu

Ethical Considerations

Not applicable.

Consent to participate

Not applicable.

Author contributions

Zexian Wang: Data curation; Formal analysis; Investigation; Methodology; Resources; Software; Writing – original draft; Writing – review & editing.

Yaru Guo: Methodology; Resources; Software; Visualization; Writing – review & editing.

Xiaohan Qin: Methodology; Resources; Software; Supervision; Writing – review & editing.

Zhilin Wan: Data curation; Methodology; Resources; Sofediting.

XiaojinWu: Conceptualization; Funding acquisition; Methodology; Supervision; Validation; Writing – review & editing.

Chen Liu: Methodology; Resources; Software; Visualization; Writing – review & editing.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Pengcheng Elites and Medical Key Talents Project of Xuzhou City, China (grant number: XWRCHT20220056) and the sixth phase training plan of high-level talents of Jiangsu Province, China (grant number: 2022-3-12-134).

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

Data sharing is not applicable to this article, as no data sets were generated or analyzed during the current study.

Supplemental material

Supplemental material for this article is available online.

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