
==== Front
Target Oncol
Target Oncol
Targeted Oncology
1776-2596
1776-260X
Springer International Publishing Cham

38990462
1084
10.1007/s11523-024-01084-7
Original Research Article
Risk Stratification According to Baseline and Early Change in Neutrophil-to-Lymphocyte Ratio in Advanced Non-Small Cell Lung Cancer Treated with Chemoimmunotherapy: A Multicenter Real-World Study
Matsumoto Kinnosuke 1
Yamamoto Yuji 1
Shiroyama Takayuki takayuki.s12@hotmail.co.jp

1
Kuge Tomoki 12
Mori Masahide 2
Tamiya Motohiro 3
Kinehara Yuhei 4
Tamiya Akihiro 5
Suzuki Hidekazu 6
Tobita Satoshi 7
Ueno Kiyonobu 7
Niki Toshie 8
Nagatomo Izumi 1
Takeda Yoshito 1
Kumanogoh Atsushi 1910111213
1 https://ror.org/035t8zc32 grid.136593.b 0000 0004 0373 3971 Department of Respiratory Medicine and Clinical Immunology, Graduate School of Medicine, Osaka University, 2-2 Yamadaoka, Suita City, Osaka 565-0871 Japan
2 https://ror.org/03ntccx93 grid.416698.4 Department of Thoracic Oncology, National Hospital Organization Osaka Toneyama Medical Center, Toyonaka, Japan
3 https://ror.org/010srfv22 grid.489169.b Department of Respiratory Medicine, Osaka International Cancer Institute, Osaka, Japan
4 Department of Respiratory Medicine and Clinical Immunology, Nippon Life Hospital, Osaka, Japan
5 grid.415611.6 0000 0004 4674 3774 Department of Internal Medicine, National Hospital Organization Kinki-Chuo Chest Medical Center, Sakai, Japan
6 Department of Thoracic Oncology, Osaka Habikino Medical Center, Habikino, Japan
7 https://ror.org/00vcb6036 grid.416985.7 0000 0004 0378 3952 Department of Respiratory Medicine, Osaka General Medical Center, Osaka, Japan
8 https://ror.org/00hm23551 grid.416305.5 0000 0004 0616 2377 Department of Respiratory Medicine, Nishinomiya Municipal Central Hospital, Nishinomiya, Japan
9 https://ror.org/035t8zc32 grid.136593.b 0000 0004 0373 3971 Department of Immunopathology, World Premier International (WPI), Immunology Frontier Research Center (iFReC), Osaka University, Suita, Japan
10 https://ror.org/035t8zc32 grid.136593.b 0000 0004 0373 3971 Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives (OTRI), Osaka University, Suita, Japan
11 https://ror.org/035t8zc32 grid.136593.b 0000 0004 0373 3971 Center for Infectious Diseases for Education and Research (CiDER), Osaka University, Suita, Osaka Japan
12 grid.136593.b 0000 0004 0373 3971 Japan Agency for Medical Research and Development-Core Research for Evolutional Science and Technology (AMED–CREST), Osaka University, Suita, Japan
13 https://ror.org/035t8zc32 grid.136593.b 0000 0004 0373 3971 Center for Advanced Modalities and DDS (CAMaD), Osaka University, Suita, Japan
11 7 2024
11 7 2024
2024
19 5 757767
1 7 2024
© The Author(s) 2024
2024
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Background

Chemoimmunotherapy is a standard treatment for advanced non-small-cell lung cancer (NSCLC). However, data on clinical predictive factors remain scarce.

Objective

We aim to identify clinical biomarkers in patients undergoing chemoimmunotherapy.

Methods

This multicenter, real-world cohort study included chemonaive patients who underwent chemoimmunotherapy between December 2018 and May 2022. Multivariate analysis was used to determine associations between survival outcomes and patient background, including baseline neutrophil-to-lymphocyte ratio (NLR) and its dynamic change (ΔNLR). To further investigate the clinical significance of NLR, patients were classified based on their peripheral immune status, defined by a combination of NLR and ΔNLR.

Results

The study included 280 patients with 30.1 months of median follow-up. Multivariate analysis revealed that older individuals, poor performance status, tumor proportion score < 1%, liver metastasis, baseline NLR ≥ 5, and ΔNLR ≥ 0 independently correlated significantly with shorter progression-free and overall survival (OS). Patients with high peripheral immune status (defined as NLR <5 and ΔNLR < 0) significantly improved long-term survival (2-year OS rate of 58.3%), whereas those with low peripheral immune status (defined as NLR ≥ 5 and ΔNLR ≥ 0) had extremely poor outcomes (2-year OS rate of 5.6%). Safety profiles did not differ significantly in terms of severe adverse events and treatment-related death rates despite the patients’ peripheral immune status (P = 0.46 and 0.63, respectively).

Conclusions

Our study provides real-world evidence regarding clinical prognostic factors for the efficacy of chemoimmunotherapy. The combined assessment of baseline NLR and ΔNLR could facilitate the identification of patients who are likely to achieve a durable response from chemoimmunotherapy.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11523-024-01084-7.

http://dx.doi.org/10.13039/501100001691 Japan Society for the Promotion of Science JP23K15187 Shiroyama Takayuki Open Access funding provided by Osaka University.Osaka UniversityOpen Access funding provided by Osaka University.

issue-copyright-statement© Springer Nature Switzerland AG 2024
==== Body
pmcKey Points

We hypothesized and demonstrated that chemoimmunotherapy could lead to a dynamic change in the neutrophil-to-lymphocyte ratio (NLR), which could be a novel prognostic factor for patients with advanced non-small cell lung cancer treated with chemoimmunotherapy.	
We classified patients into three groups of peripheral immune status based on their baseline NLR and its dynamic change (ΔNLR). Patients treated with chemoimmunotherapy showed 2-year overall survival rates of 58.3% and 5.6% for patients with high (NLR < 5 and ΔNLR < 0) and low (NLR ≥ 5 and ΔNLR ≥ 0) peripheral immune statuses, respectively.	
Thus, the combination of baseline NLR and ΔNLR may be a key risk stratification factor in patients with advanced non-small cell lung cancer treated with chemoimmunotherapy.	

Introduction

Non-small-cell lung cancer (NSCLC) is the leading cause of cancer-related mortality worldwide [1, 2]. Although molecular targeted therapies for patients with driver mutations are available, improving prognoses in many regions, many patients still lack access to such treatments [3]. For such patients, platinum-based chemotherapy plus immune checkpoint inhibitors (ICIs) are now a standard first-line treatment [4–9]. Some patients escape early death and have long-term survival benefits after chemoimmunotherapy.

Various predictive factors for survival are known in patients with NSCLC receiving ICI monotherapy [10]. ICI monotherapy is ineffective for patients with a poor Eastern Cooperative Oncology Group performance status (ECOG-PS) or those requiring oral corticosteroids, proton pump inhibitors (PPIs), or antibiotics before treatment [11]. In addition to clinical features, laboratory parameters, such as the neutrophil-to-lymphocyte ratio (NLR), C-reactive protein, and lactate dehydrogenase, and histological factors, such as programmed death ligand-1 (PD-L1), are predictive biomarkers. Meanwhile, few reports exist regarding predictive factors for patients with NSCLC receiving ICI plus chemotherapy compared with those for patients receiving ICI monotherapy [12–14], with these reports having a short follow-up period (median 11.7–18.0 months).

The NLR, defined as the absolute neutrophil count divided by the absolute lymphocyte count, is a promising predictive survival factor in various tumor types [15]. Moreover, the NLR is simple and easy to calculate and can be obtained from routine whole-blood calculations. However, levels of these blood cells are often dynamic rather than static, especially during therapeutic interventions; hence, evaluating NLR dynamic changes is also important.

Recent studies on ICI monotherapy have suggested the special role of early changes in the NLR in predicting the efficacy of immunotherapy for patients with advanced NSCLC [15]. The changes in the NLR before and after immunotherapy can also be easily measured in routine whole-blood tests, as with the baseline NLR. To date, multiple studies have demonstrated that cytotoxic chemotherapy activates and expands lymphocytes via damage-associated molecular patterns in response to tumor cell death while simultaneously decreasing systemic neutrophils [16]. Therefore, we hypothesized that dynamic NLR changes could be a novel prognostic factor of survival for patients with advanced NSCLC treated with chemoimmunotherapy.

Material and Methods

Patient Selection

Consecutive patients with histologically confirmed advanced or recurrent-stage NSCLC were registered through electronic databases of eight institutes in Japan. Patients treated with a first-line combination of pembrolizumab or nivolumab plus ipilimumab with platinum-based chemotherapy were included, while those with positive or untested EGFR gene mutations and ALK rearrangements were excluded according to the Keynote 189 and CheckMate 9LA protocols [4, 6]. Patients whose treatment was initiated between December 2018 and May 2022 were included, and the data collection cutoff date was 30 November 2023.

Study Design

This multicenter retrospective cohort study collected clinical data from medical records, including age, sex, ECOG-PS, smoking status, histology, driver gene mutations, PD-L1 tumor proportion scores (TPSs), clinical stage, prior thoracic radiotherapy, use of steroids, PPIs, and antibiotics before treatment, brain metastasis, liver metastasis, platinum-based chemotherapy, ICIs, baseline NLR, changes in the NLR before and after treatment (ΔNLR), treatment outcomes, and adverse events (AEs). The PD-L1 TPS in tumor cells was calculated using an anti-PD-L1 antibody (clone 22C3; Dako North America, Inc., CA). Information on medications before treatment included the use of steroids (≥ 10 mg/day of prednisone equivalent) within the 30 days before chemoimmunotherapy initiation, antibiotics within 30 days before treatment initiation, and PPIs at treatment initiation [17–21]. The baseline NLR was defined as the ratio between the numbers of neutrophils and lymphocytes from the peripheral blood count at chemoimmunotherapy initiation. ΔNLR was defined as the difference between the NLR at the start of the second cycle and that at baseline; a high NLR was set as ≥ 5 according to the existing six literature [22], and the ΔNLR cutoff value was zero based on the ease of clinical use and existing literature: ΔNLR ≥ 0 indicates an increase from baseline, and ΔNLR < 0 indicates a decrease [23]. To further evaluate the prognostic relevance of a combination of baseline NLR and ΔNLR, patients were stratified based on the baseline NLR (< 5/≥ 5) and ΔNLR (< 0/≥ 0) into three peripheral immune statuses: high (NLR < 5 and ΔNLR < 0), intermediate (NLR < 5 and ΔNLR ≥ 0 or NLR ≥ 5 and ΔNLR < 0), and low (NLR ≥ 5 and ΔNLR ≥ 0).

Clinical responses were defined according to the Response Evaluation Criteria in Solid Tumors version 1.1 [24]. Progression-free survival (PFS) was defined as the period from the start date of chemoimmunotherapy to the date of disease progression or death from any cause. Overall survival (OS) was determined from the start date of chemoimmunotherapy to the date of death or last follow-up. The safety level was evaluated using the Common Terminology Criteria for Adverse Events version 5.0 based on AE incidence, treatment discontinuation, and treatment-related death (TRD) [25]. Severe AEs (SAEs) were defined as AEs ≥ grade 3.

Statistical Analyses

Dichotomous variables were compared using the chi-squared or Fisher’s exact test when the smallest expected value was < 5. P values were adjusted using the Bonferroni correction to account for overlap. A list-wise deletion approach was used to handle missing data. Only patients with complete data for all variables of interest were included in the final analysis. Survival was assessed using the Kaplan–Meier method, with the log-rank test for comparison. A landmark time analysis was applied to estimate survival based on changes in NLR. PFS and OS were defined as the period from a 3-week landmark time, including only patients with disease control or those who were alive at 21 days after initiating chemoimmunotherapy for PFS (n = 263) or OS (n = 267), respectively. The median follow-up duration was calculated using only patients who remained alive. To determine the associations between patient characteristics and survival, univariate and multivariate Cox proportional hazards regressions were performed with the variables age, sex, ECOG-PS, smoking status, histology, PD-L1 TPS, cStage, prior thoracic radiotherapy, steroids, PPIs, antibiotics, brain metastasis, liver metastasis, baseline NLR, ΔNLR, platinum-based chemotherapy, and ICIs [10, 11, 17–23, 26]. Variance inflation factor (VIF) values were calculated to measure the degree of multicollinearity among the explanatory variables. A VIF of > 5 was regarded as a high correlation of the variables [27]. Differences were considered significant at two-sided P values < 0.05. Statistical analyses were performed using R software (version 4.3.0).

Results

Patient Characteristics

This retrospective study enrolled 321 patients who received chemoimmunotherapy, resulting in 280 patients being included (Supplementary Fig. 1). The patient characteristics are summarized in Table 1. The median patient age was 69.0 years [interquartile range (IQR), 62–73 years]; some older patients (≥ 75 years) were included (18.2%). Most patients were men (79.6%) and smokers (90.0%) and had an ECOG-PS of 0–1 (87.9%). The PD-L1 TPS (high, low, and negative) was balanced. Driver mutations, excluding EGFR and ALK genomic aberrations, were detected in 32 patients (Supplementary Table 1). Some patients had undergone thoracic radiotherapy (10.0%); had taken steroids (6.4%), PPIs (24.6%), or antibiotics (15.4%); and had brain (18.9%) or liver (10.4%) metastases. In most patients, the concomitant ICI was pembrolizumab (92.1%), whereas nivolumab plus ipilimumab was used in some patients. Significant differences were observed in characteristics for ECOG-PS and prior thoracic radiotherapy in both baseline NLR and ΔNLR and for PD-L1 TPS, cStage, history of antibiotics use, and liver metastasis in either baseline NLR or ΔNLR.Table 1 Patient characteristics (n = 280)

Parameter	Overall, n (%)	Baseline NLR, n (%)	ΔNLR, n (%)	
NLR < 5	NLR ≥ 5	P	ΔNLR < 0	ΔNLR ≥ 0	P	
Patients	280	186	94		192	82		
Median age (IQR), years	69 (62–73)	69 (62–73)	68.5 (63–73)	0.917	69 (62–74)	69 (63–73)	0.503	
Age, years				1.000			0.460	
 < 75	229 (81.8)	152 (81.7)	77 (81.9)		155 (80.7)	37 (19.3)		
 ≥ 75	51 (18.2)	34 (18.3)	17 (18.1)		68 (82.9)	14 (17.1)		
Sex				0.271			0.383	
 Male	223 (79.6)	152 (81.7)	71 (75.5)		150 (78.1)	42 (21.9)		
 Female	57 (20.4)	34 (18.3)	23 (24.5)		69 (84.1)	13 (15.9)		
ECOG-PS				<0.001			<0.001	
 0–1	246 (87.9)	174 (93.5)	72 (76.6)		179 (93.2)	64 (78.0)		
 2–3	34 (12.1)	12 (6.5)	22 (23.4)		13 (6.8)	18 (22.0)		
Smoking status				0.143			0.074	
 Former/current	252 (90.0)	171 (91.9)	81 (86.2)		171 (89.0)	77 (93.9)		
 Never	28 (10.0)	15 (8.1)	13 (13.8)		21 (10.9)	5 (6.1)		
Histology				0.585			0.123	
 Nonsquamous cell carcinoma	194 (69.3)	131 (70.4)	63 (67.0)		126 (65.6)	64 (78.0)		
 Squamous cell carcinoma	86 (30.7)	55 (29.6)	31 (33.0)		66 (34.4)	18 (22.0)		
PD-L1 TPS, %				0.003			0.325	
 ≥ 50	79 (28.2)	51 (27.4)	28 (29.8)		60 (31.3)	19 (23.2)		
 1–49	92 (32.9)	73 (39.2)	19 (20.2)		62 (32.3)	26 (31.7)		
 < 1	82 (29.3)	50 (26.9)	32 (34.0)		52 (27.1)	28 (34.1)		
 Unknown	27 (9.6)	12 (6.5)	15 (16.0)		18 (9.4)	9 (11.0)		
cStage				0.020			0.741	
 IV	222 (79.3)	140 (75.3)	82 (87.2)		153 (79.7)	65 (79.3)		
 Others	58 (20.7)	46 (24.7)	12 (12.8)		39 (20.3)	17 (20.7)		
Prior thoracic radiotherapy	28 (10.0)	14 (7.5)	14 (14.9)	0.060	23 (12.0)	3 (3.7)	0.017	
Medication history								
 Steroids	18 (6.4)	8 (4.3)	10 (10.6)	0.067	12 (6.3)	5 (6.1)	0.585	
 Proton pump inhibitors	69 (24.6)	45 (24.2)	24 (25.5)	0.883	46 (24.0)	21 (25.6)	0.846	
 Antibiotics	43 (15.4)	21 (11.3)	22 (23.4)	0.013	33 (17.2)	9 (11.0)	0.424	
Brain metastasis	53 (18.9)	33 (17.7)	20 (21.3)	0.279	34 (17.7)	16 (19.5)	0.353	
Liver metastasis	29 (10.4)	16 (8.6)	13 (13.8)	0.213	14 (7.3)	14 (17.1)	0.045	
Treatment regimen				0.275			0.238	
 Carboplatin + nab-paclitaxel	73 (26.1)	45 (24.2)	28 (29.8)		58 (30.2)	13 (15.9)		
 Carboplatin + pemetrexed	159 (56.8)	105 (56.5)	54 (57.4)		101 (52.6)	55 (67.1)		
 Carboplatin + paclitaxel	20 (7.1)	17 (9.1)	3 (3.2)		13 (6.8)	7 (8.5)		
 Cisplatin + pemetrexed	28 (10.0)	19 (10.2)	9 (9.6)		20 (10.4)	7 (8.5)		
Immune checkpoint inhibitor				0.157			0.382	
 Pembrolizumab	258 (92.1)	168 (90.3)	90 (95.7)		179 (93.2)	73 (89.0)		
 Nivolumab + ipilimumab	22 (7.9)	18 (9.7)	4 (4.3)		13 (6.8)	9 (11.0)		
ECOG-PS, Eastern Cooperative Oncology Group Performance Status; IQR, interquartile range; NLR, neutrophil-to-lymphocyte ratio; PD-L1 TPS, programmed cell death ligand-1 tumor proportion score; ΔNLR, post-one cycle NLR minus baseline NLR

Treatment Effectiveness in All Patients

The median follow-up period was 30.1 (IQR 19.1–43.3) months, with 217 PFS (77.5%) and 169 OS (60.4%) events. The median PFS and OS were 8.0 [95% confidence interval (CI) 6.6–9.3] and 18.5 (95% CI 14.6–22.3) months, respectively (Supplementary Fig. 2).

Multivariate analysis identified age ≥ 75 years [hazard ratio (HR) of 1.54, 95% CI 1.06–2.22, P = 0.022], ECOG-PS of 2–3 (HR of 2.09, 95% CI 1.29–3.39, P = 0.003), PD-L1 TPS < 1% (HR of 1.38, 95% CI 1.01–1.88, P = 0.045), liver metastasis (HR of 1.83, 95% CI 1.14–2.92, P = 0.012), NLR ≥ 5 (HR of 1.64, 95% CI 1.18–2.30, P = 0.003), and ΔNLR ≥ 0 (HR of 1.77, 95% CI 1.26–2.49, P < 0.001) as significant independent predictors of PFS (Fig. 1). Moreover, age ≥ 75 years (HR of 1.90, 95% CI 1.27–2.84, P = 0.002), ECOG-PS of 2–3 (HR of 3.19, 95% CI 1.91–5.32, P < 0.001), PD-L1 TPS < 1% (HR of 1.45, 95% CI 1.01–2.07, P = 0.043), liver metastasis (HR of 2.18, 95% CI 1.34–3.53, P = 0.002), NLR ≥ 5 (HR of 2.16, 95% CI 1.48–3.13, P < 0.001), ΔNLR ≥ 0 (HR of 2.21, 95% CI 1.50–3.28, P < 0.001), and platinum regimen of cisplatin (HR of 0.45, 95% CI 0.22–0.90, P = 0.024) were significant independent OS predictors (Fig. 2). There was no problematic level of multicollinearity among the variables in the PFS and OS multivariate analysis (Supplementary Table 2). Thus, the following six variables showed significant differences between the two classified groups in both PFS and OS: ECOG-PS, PD-L1 TPS, use of antibiotics, liver metastasis, baseline NLR, and ΔNLR (Supplementary Fig. 3).Fig. 1 Univariate and multivariate analyses of progression-free survival in all patients. CI, confidence interval; ECOG-PS, Eastern Cooperative Oncology Group Performance Status; HR, hazard ratio; NLR, neutrophil-to-lymphocyte ratio; PD-L1 TPS, programmed cell death ligand-1 tumor proportion score; PPI, proton pump inhibitor; TRT, thoracic radiotherapy

Fig. 2 Univariate and multivariate analyses of overall survival in all patients. CI, confidence interval; ECOG-PS, Eastern Cooperative Oncology Group Performance Status; HR, hazard ratio; NLR, Neutrophil-to-lymphocyte ratio; PD-L1 TPS, programmed cell death ligand-1 tumor proportion score; PPI, proton pump inhibitor; TRT, thoracic radiotherapy

Treatment Effectiveness Relative to NLR and ΔNLR

The median PFS and OS for patients with NLR < 5 were 9.9 (95% CI 8.1–12.5) months and 26.6 (95% CI 19.1–36.2) months, respectively, and those for patients with NLR ≥ 5 were 6.5 (95% CI 4.7–8.1) months and 11.6 (95% CI 9.9–16.8) months, respectively (both P < 0.001) (Fig. 3A, B). The objective response rate (ORR) (66.7% versus 54.8%, P = 0.066) and disease control rate (DCR) (91.4% versus 77.4%, P = 0.002) were significantly higher in the low NLR group than in the high NLR group (Supplementary Table 3). Similarly, for patients with ΔNLR < 0, the median PFS and OS were 9.8 (95% CI 7.6–12.1) months and 22.3 (95% CI 18.5–36.2) months, respectively, whereas for patients with ΔNLR ≥ 0 were 6.0 (95% CI 3.9–8.9) months and 13.2 (95% CI 8.7–17.2) months, respectively (P = 0.002 and P < 0.001) (Fig. 3C, D). The ORR (70.3% versus 46.3%, P < 0.001) and DCR (94.3% versus 72.0%, P < 0.001) were significantly higher in the ΔNLR < 0 group than in the ΔNLR ≥ 0 group (Supplementary Table 3).Fig. 3 Kaplan–Meier survival curves with 3-week landmark analysis of patients with advanced NSCLC receiving chemoimmunotherapy grouped by the NLR and ΔNLR. (A) PFS of patients stratified by the baseline NLR. (B) OS of patients stratified by the baseline NLR. (C) PFS of patients stratified by ΔNLR (difference between the NLR at the start of the second cycle and baseline). (D) OS of patients stratified by ΔNLR. (E) PFS of patients stratified by peripheral immune status: high (NLR < 5 and ΔNLR < 0), intermediate (NLR <5 and ΔNLR ≥ 0, or NLR ≥ 5, and ΔNLR < 0), and low (NLR ≥ 5 and ΔNLR ≥ 0). (F) OS of patients stratified by peripheral immune status. CI, confidence interval; NLR, neutrophil-to-lymphocyte ratio; NSCLC, non-small-cell lung cancer; OS, overall survival; PFS, progression-free survival

Patients were classified into peripheral immune groups as follows: high (n = 122), intermediate (n = 133), and low (n = 19) (Supplementary Table 4), with a median PFS of 11.8 (95% CI 9.1–14.3) months, 7.4 (95% CI 6.2–9.8) months, and 1.9 (95% CI: 1.2–6.8) months and a median OS of 31.8 (95% CI 21.7 to not reached) months, 15.1 (95% CI 13.2–20.2) months, and 3.3 (95% CI 2.1–7.9) months, respectively (both P < 0.001). The 2-year PFS rates were 35.3%, 21.6%, and 0%, respectively, and the 2-year OS rates were 58.3%, 37.0%, and 5.6%, respectively (Fig. 3E, F). The ORR (72.1% versus 61.7% versus 15.8%, P < 0.001) and DCR (95.9% versus 87.2% versus 36.8%, P < 0.001) were significantly higher in the high and intermediate peripheral immune groups than in the low immune group (Supplementary Table 3).

Safety Profiles

Table 2 shows that 95 (34.7%) patients experienced grade ≥ 3 SAEs and 59 (21.5%) discontinued treatment due to SAEs. Ten (3.8%) patients died owing to the following treatment-related AEs: pneumonitis (five patients), febrile neutropenia (three), cardiovascular disorder (one), and bacterial infection (one). Furthermore, the safety profiles did not differ significantly with respect to SAEs, treatment discontinuation, and TRD rates among the peripheral immune statuses (P = 0.463, 0.706, and 0.633, respectively).Table 2 Treatment-related severe adverse events (grade ≥ 3) according to peripheral immune statusa

	All patients
(n = 274)	High
(n = 122)	Intermediate
(n = 133)	Low
(n = 19)	P value	
Number of patients with SAEs, (%)	95 (34.7)	38 (31.1)	51 (38.3)	6 (31.6)	0.463	
 Pneumonitis	32 (11.7)	14 (11.5)	16 (12.0)	2 (10.5)	0.978	
 Skin toxicity	12 (4.4)	7 (5.7)	4 (3.0)	1 (5.3)	0.557	
 Colitis	6 (2.2)	1 (0.8)	5 (3.8)	0 (0)	0.220	
 Hepatobiliary toxicity	11 (4.0)	3 (2.5)	6 (4.5)	2 (10.5)	0.230	
 Renal toxicity	5 (1.8)	2 (1.6)	3 (2.3)	0 (0)	0.773	
 Adrenal pituitary disorder	9 (3.3)	5 (4.1)	4 (3.0)	0 (0)	0.628	
 Neuromuscular disorder	4 (1.5)	4 (3.3)	0 (0)	0 (0)	0.080	
 Type 1 diabetes mellitus	2 (0.7)	0 (0)	2 (1.5)	0 (0)	0.344	
 Cardiovascular disorder	4 (1.5)	3 (2.5)	1 (0.8)	0 (0)	0.451	
 Febrile neutropenia	16 (5.8)	3 (2.5)	12 (9.0)	1 (5.3)	0.082	
 Bacterial infection	2 (0.7)	1 (0.8)	1 (0.8)	0 (0)	0.926	
 Others (details unknown)	6 (2.2)	2 (1.6)	4 (3.0)	0 (0)		
SAEs leading to discontinuation, n (%)	59 (21.5)	25 (20.5)	31 (23.3)	3 (15.8)	0.706	
Treatment-related death, n (%)	10 (3.6)	3 (2.5)	6 (4.5)	1 (5.3)	0.633	
aPeripheral immune status shows high (NLR < 5 and ΔNLR < 0), intermediate (NLR < 5 and ΔNLR ≥ 0 or NLR ≥ 5 and ΔNLR < 0), and low (NLR ≥ 5 and ΔNLR ≥ 0). NLR, neutrophil-to-lymphocyte ratio; SAE, severe adverse event; ΔNLR, post-one cycle NLR minus baseline NLR

Discussion

We evaluated the efficacy and safety of chemoimmunotherapy in treatment-naive patients with advanced NSCLC in a real-world setting over a 2-year follow-up period. Combination therapy provided long-term survival for patients with high peripheral immune status (NLR < 5 and ΔNLR < 0) but had extremely poor effectiveness for patients with low peripheral immune status (NLR ≥ 5 and ΔNLR ≥ 0). The safety profiles showed no significant differences in SAEs, treatment discontinuation, and TRD rates despite peripheral immune status. To our knowledge, this is the first study to elucidate clinical outcomes in patients receiving chemoimmunotherapy using the baseline NLR and ΔNLR. Our results can enable early prediction of survival in patients undergoing chemoimmunotherapy.

The survival outcomes in this study are similar to those in clinical trials such as Keynote407 and CheckMate9LA [5, 6]. Moreover, previous real-world reports on chemoimmunotherapy have demonstrated similar survival results [12–14]. Consistent with the reported predictive factors for survival in patients with NSCLC treated with chemoimmunotherapy, ECOG-PS, and PD-L1 TPS were identified in this study [12]. We newly identified pretreatment antibiotics, liver metastasis, baseline NLR, and ΔNLR as independent predictive factors for PFS and OS with chemoimmunotherapy, consistent with those reported in previous studies for patients receiving ICI monotherapy [20, 28, 29]. The SAE rate was lower than that reported in previous clinical trials owing to limitations in retrospective clinical data collection from medical records. Therefore, careful attention should be paid to SAE interpretations, discontinuation, and TRD incidences.

Regarding ICI monotherapy, some previous reports have focused on the impact of baseline NLR on prognosis. Tumor cells secrete various chemokines and growth factors, inducing neutrophils to enter the tumors and promote vascular formation. Moreover, neutrophils differentiate into myeloid-derived suppressor cells, thereby preventing T cell activation within the tumor [30, 31]. An immunohistochemical peripheral NLR validation demonstrated that the correlation between the peripheral NLR and clinical outcomes was consistent with the correlation between the intratumoral lymphocyte ratio and the clinical outcomes [32–34]. Therefore, a high NLR at baseline implies an increase in the neutrophil count or a decrease in the lymphocyte count within the tumor. Given these findings, the baseline NLR could be a beneficial biomarker in patients treated with chemoimmunotherapy, as reported for ICI monotherapy.

Combining cytotoxic chemotherapy with immunotherapy may enhance antitumor immunity [16]. These are potent endogenous immune adjuvants to the host’s innate immune system, induced through various chemotherapies. Patients who maintained a low NLR during chemotherapy had the most favorable prognosis, whereas those with an increased NLR had the shortest survival [35]. An association between ΔNLR and response to cisplatin-based chemotherapy was found in patients with esophageal and biliary cancers [36, 37], suggesting that ΔNLR may be used as a predictive factor for survival in patients with cancer undergoing chemotherapy, corroborating the basic findings described above. Moreover, the meta-analysis demonstrated that the trends in the NLR were associated with the prognoses of patients receiving ICI monotherapy; notably, a high post-ICI treatment NLR was associated with poorer survival than a high baseline NLR [15], suggesting that ΔNLR can also be an optimal prognostic factor in patients undergoing chemoimmunotherapy. Additionally, the early separation and maintenance of survival curves among the groups based on the composite assessment of the baseline NLR and ΔNLR were most notable in our study. Patients with a high baseline NLR with further increase after the first treatment course experienced markedly poor outcomes. Therefore, combining the NLR and ΔNLR may help identify the subgroup of patients with an unfavorable treatment response.

The incidence of immune-related AEs (irAEs) was suggested to predict enhanced ICI effectiveness [38]. Our study demonstrated that the effectiveness significantly differed among the peripheral immune status (high, intermediate, and low) groups, whereas the SAEs and TRD rates did not significantly differ according to peripheral immune status. In a meta-analysis evaluating the association between the NLR and irAEs, a lower NLR at baseline was significantly associated with higher irAE rates. However, almost all the reports assessed included any-grade irAEs, which may have differed from our results [39]. Thus, the low peripheral immune group (NLR ≥ 5 and ΔNLR ≥ 0) may not benefit from chemoimmunotherapy since its toxicity is comparable with that in the other groups despite its poor effectiveness.

Despite its large multicenter cohort and novel findings, this study had some limitations, including the retrospective nature and the possibility of selection bias. In our cohort, driver gene mutations were not included as an adjustment factor because comprehensive panel testing was not widely available, and detection may have been masked. Moreover, almost all the patients belonged to a single ethnic group (Japanese), which limits the generalizability of these results to other populations. Finally, this study did not compare the efficacy and safety of patients receiving pembrolizumab alone as a control cohort; therefore, further comparative studies are needed.

Conclusions

Chemoimmunotherapy provided long-term survival for patients with high peripheral immune status and had extremely poor effectiveness for patients with low peripheral immune status. The safety profiles showed no significant differences in the SAEs, treatment discontinuation, and TRD rates despite the peripheral immune status. Our study demonstrates that combining baseline NLR and ΔNLR can serve as a prognostic factor for survival benefits in patients with advanced NSCLC treated with chemoimmunotherapy. Further prospective investigations are warranted to confirm these results.

Supplementary Information

Below is the link to the electronic supplementary material.Supplementary file1 (PDF 691 kb)

Acknowledgements

We thank all patients and staff who participated in this study.

Declarations

Funding

Open Access funding provided by Osaka University. This work was supported in part by the grant from JSPS KAKENHI (JP23K15187 to T.S.).

Conflict of interest

M.M. reports receiving grants from Ono Pharmaceutical, Merck Sharp and Dohme, Delt-Fly Pharma, and Chugai Pharmaceutical and honoraria for lectures from AstraZeneca, Chugai Pharmaceutical, Nippon Boehringer Ingelheim, Eli Lilly Japan, Novartis, Pfizer, Merck Sharp and Dohme, Bristol-Myers Squibb, Ono Pharmaceutical, Taiho Pharmaceutical, Takeda Pharmaceutical, Nippon Kayaku, Kyowa Kirin, Daiichi-Sankyo, Otsuka Pharmaceutical, and Shionogi Pharmaceutical outside of the submitted work. M.T. reports receiving grants from Ono Pharmaceutical, Japan, Bristol–Myers Squibb, and Boehringer Ingelheim; and honoraria for lectures from Taiho Pharmaceutical, Japan, Eli Lilly, Asahi Kasei Pharmaceutical, Merck Sharp and Dohme, Boehringer Ingelheim, AstraZeneca, Chugai Pharmaceutical, Ono Pharmaceutical, and Bristol-Myers Squibb outside of the submitted work. A.T. reports receiving grants from AstraZeneca, BeiGene, and Daiichi-Sankyo and honoraria for lectures from AstraZeneca, Boehringer Ingelheim, Eli Lilly, Pfizer, Amgen, Kyowa Kirin, Merck BioFarma, Novartis, Ono Pharmaceutical, Chugai Pharmaceutical, Bristol–Myers Squibb, Taiho Pharmaceutical, Merck Sharp and Dohme, Takeda Pharmaceutical, Nihon-Kayaku, and Thermo Fischer Scientific outside of the submitted work. The other authors declare no conflicts of interest. K.M., Y.Y., T.S., T.K., Y.K., H.S., S.T., K.U., T.N., I.N., Y.T., and A.K. declare that they have no conflicts of interest that might be relevant to the contents of this manuscript.

Ethics approval

This cohort study was conducted in accordance with the Declaration of Helsinki and the World Health Organization’s Guidelines for Good Clinical Practice. This study was also approved by the ethical review board of each participating institute.

Consent to participate

An opt-out method was used so that patients and families could refuse to participate in the study.

Consent for publication

Not applicable.

Availability of data and material

Data are available on request from the authors.

Code availability

Not applicable.

Author contributions

K.M.: conceptualization, data curation, formal analysis, investigation, methodology, resources, visualization, writing—original draft, writing—review and editing. Y.Y.: conceptualization, data curation, formal analysis, investigation, methodology, visualization, writing—original draft, writing—review and editing. T.S.: conceptualization, data curation, formal analysis, investigation, methodology, project administration, resources, supervision, visualization, writing—original draft, writing—review and editing. T.K.: conceptualization, data curation, investigation, methodology, resources, visualization, writing—original draft, writing—review and editing. M.M., M.T., Y.K., A.T., H.S., S.T., K.U., and T.N.: investigation, resources, writing—review and editing. I.N.: conceptualization, data curation, formal analysis, investigation, methodology, project administration, supervision, visualization, writing—original draft, writing—review and editing. Y.T. and A.K.: project administration, supervision, writing—review and editing. All authors have read and approved the final version of the manuscript.

Kinnosuke Matsumoto and Yuji Yamamoto contributed equally to this manuscript.
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References

1. Siegel RL Miller KD Wagle NS Jemal A Cancer statistics, 2023 CA Cancer J Clin 2023 73 17 48 10.3322/caac.21763 36633525
Siegel RL, Miller KD, Wagle NS, Jemal A. Cancer statistics, 2023. CA Cancer J Clin. 2023;73:17–48. 10.3322/caac.21763.36633525 10.3322/caac.21763
2. Molina JR Yang P Cassivi SD Schild SE Adjei AA Non-small cell lung cancer: epidemiology, risk factors, treatment, and survivorship Mayo Clin Proc 2008 83 584 594 10.4065/83.5.584 18452692
Molina JR, Yang P, Cassivi SD, Schild SE, Adjei AA. Non-small cell lung cancer: epidemiology, risk factors, treatment, and survivorship. Mayo Clin Proc. 2008;83:584–94. 10.4065/83.5.584.18452692 10.4065/83.5.584
3. Kunimasa K Matsumoto S Kawamura T Inoue T Tamiya M Kanzaki R Clinical application of the AMOY 9-in-1 panel to lung cancer patients Lung Cancer 2023 179 107190 10.1016/j.lungcan.2023.107190 37058787
Kunimasa K, Matsumoto S, Kawamura T, Inoue T, Tamiya M, Kanzaki R, et al. Clinical application of the AMOY 9-in-1 panel to lung cancer patients. Lung Cancer. 2023;179:107190. 10.1016/j.lungcan.2023.107190.37058787 10.1016/j.lungcan.2023.107190
4. Gandhi L Rodríguez-Abreu D Gadgeel S Esteban E Felip E De Angelis F Domine M Pembrolizumab plus chemotherapy in metastatic non-small-cell lung cancer N Engl J Med 2018 378 2078 2092 10.1056/NEJMoa1801005 29658856
Gandhi L, Rodríguez-Abreu D, Gadgeel S, Esteban E, Felip E, De Angelis F, Domine M, et al. Pembrolizumab plus chemotherapy in metastatic non-small-cell lung cancer. N Engl J Med. 2018;378:2078–92. 10.1056/NEJMoa1801005.29658856 10.1056/NEJMoa1801005
5. Paz-Ares L Luft A Vicente D Tafreshi A Gümüş M Mazières J Pembrolizumab plus chemotherapy for squamous non-small-cell lung cancer N Engl J Med 2018 379 2040 2051 10.1056/NEJMoa1810865 30280635
Paz-Ares L, Luft A, Vicente D, Tafreshi A, Gümüş M, Mazières J, et al. Pembrolizumab plus chemotherapy for squamous non-small-cell lung cancer. N Engl J Med. 2018;379:2040–51. 10.1056/NEJMoa1810865.30280635 10.1056/NEJMoa1810865
6. Paz-Ares L Ciuleanu TE Cobo M Schenker M Zurawski B Menezes J First-line nivolumab plus ipilimumab combined with two cycles of chemotherapy in patients with non-small-cell lung cancer (CheckMate 9LA): an international, randomised, open-label, phase 3 trial Lancet Oncol 2021 22 198 211 10.1016/S1470-2045(20)30641-0 33476593
Paz-Ares L, Ciuleanu TE, Cobo M, Schenker M, Zurawski B, Menezes J, et al. First-line nivolumab plus ipilimumab combined with two cycles of chemotherapy in patients with non-small-cell lung cancer (CheckMate 9LA): an international, randomised, open-label, phase 3 trial. Lancet Oncol. 2021;22:198–211. 10.1016/S1470-2045(20)30641-0.33476593 10.1016/S1470-2045(20)30641-0
7. Socinski MA Jotte RM Cappuzzo F Orlandi F Stroyakovskiy D Nogami N Atezolizumab for first-line treatment of metastatic nonsquamous NSCLC N Engl J Med 2018 378 2288 2301 10.1056/NEJMoa1716948 29863955
Socinski MA, Jotte RM, Cappuzzo F, Orlandi F, Stroyakovskiy D, Nogami N, et al. Atezolizumab for first-line treatment of metastatic nonsquamous NSCLC. N Engl J Med. 2018;378:2288–301. 10.1056/NEJMoa1716948.29863955 10.1056/NEJMoa1716948
8. West H McCleod M Hussein M Morabito A Rittmeyer A Conter HJ Atezolizumab in combination with carboplatin plus nab-paclitaxel chemotherapy compared with chemotherapy alone as first-line treatment for metastatic non-squamous non-small-cell lung cancer (IMpower130): a multicentre, randomised, open-label, phase 3 trial Lancet Oncol 2019 20 924 937 10.1016/S1470-2045(19)30167-6 31122901
West H, McCleod M, Hussein M, Morabito A, Rittmeyer A, Conter HJ, et al. Atezolizumab in combination with carboplatin plus nab-paclitaxel chemotherapy compared with chemotherapy alone as first-line treatment for metastatic non-squamous non-small-cell lung cancer (IMpower130): a multicentre, randomised, open-label, phase 3 trial. Lancet Oncol. 2019;20:924–37. 10.1016/S1470-2045(19)30167-6.31122901 10.1016/S1470-2045(19)30167-6
9. Johnson ML Cho BC Luft A Alatorre-Alexander J Geater SL Laktionov K Durvalumab with or without tremelimumab in combination with chemotherapy as first-line therapy for metastatic non-small-cell lung cancer: the phase III POSEIDON study J Clin Oncol 2023 41 1213 1227 10.1200/JCO.22.00975 36327426
Johnson ML, Cho BC, Luft A, Alatorre-Alexander J, Geater SL, Laktionov K, et al. Durvalumab with or without tremelimumab in combination with chemotherapy as first-line therapy for metastatic non-small-cell lung cancer: the phase III POSEIDON study. J Clin Oncol. 2023;41:1213–27. 10.1200/JCO.22.00975.36327426 10.1200/JCO.22.00975
10. Brueckl WM Ficker JH Zeitler G Clinically relevant prognostic and predictive markers for immune-checkpoint-inhibitor (ICI) therapy in non-small cell lung cancer (NSCLC) BMC Cancer 2020 20 1185 10.1186/s12885-020-07690-8 33272262
Brueckl WM, Ficker JH, Zeitler G. Clinically relevant prognostic and predictive markers for immune-checkpoint-inhibitor (ICI) therapy in non-small cell lung cancer (NSCLC). BMC Cancer. 2020;20:1185. 10.1186/s12885-020-07690-8.33272262 10.1186/s12885-020-07690-8
11. Kawachi H Yamada T Tamiya M Negi Y Goto Y Nakao A Concomitant proton pump inhibitor use with pembrolizumab monotherapy vs immune checkpoint inhibitor plus chemotherapy in patients with Non−Small cell lung cancer JAMA Netw Open 2023 6 2322915 10.1001/jamanetworkopen.2023.22915
Kawachi H, Yamada T, Tamiya M, Negi Y, Goto Y, Nakao A, et al. Concomitant proton pump inhibitor use with pembrolizumab monotherapy vs immune checkpoint inhibitor plus chemotherapy in patients with Non−Small cell lung cancer. JAMA Netw Open. 2023;6:2322915. 10.1001/jamanetworkopen.2023.22915.10.1001/jamanetworkopen.2023.22915
12. Fujimoto D Miura S Yoshimura K Wakuda K Oya Y Haratani K A real-world study on the effectiveness and safety of pembrolizumab plus chemotherapy for nonsquamous NSCLC JTO Clin Res Rep. 2021 3 100265 10.1016/j.jtocrr.2021.100265 35146460
Fujimoto D, Miura S, Yoshimura K, Wakuda K, Oya Y, Haratani K, et al. A real-world study on the effectiveness and safety of pembrolizumab plus chemotherapy for nonsquamous NSCLC. JTO Clin Res Rep. 2021;3:100265. 10.1016/j.jtocrr.2021.100265.35146460 10.1016/j.jtocrr.2021.100265
13. Banna GL Cantale O Muthuramalingam S Cave J Comins C Cortellini A Efficacy outcomes and prognostic factors from real-world patients with advanced non-small-cell lung cancer treated with first-line chemoimmunotherapy: the Spinnaker retrospective study Int Immunopharmacol 2022 110 108985 10.1016/j.intimp.2022.108985 35777264
Banna GL, Cantale O, Muthuramalingam S, Cave J, Comins C, Cortellini A, et al. Efficacy outcomes and prognostic factors from real-world patients with advanced non-small-cell lung cancer treated with first-line chemoimmunotherapy: the Spinnaker retrospective study. Int Immunopharmacol. 2022;110:108985. 10.1016/j.intimp.2022.108985.35777264 10.1016/j.intimp.2022.108985
14. Morimoto K Uchino J Yokoi T Kijima T Goto Y Nakao A Impact of cancer cachexia on the therapeutic outcome of combined chemoimmunotherapy in patients with non-small cell lung cancer: a retrospective study OncoImmunology. 2021 10 1950411 10.1080/2162402X.2021.1950411 34290909
Morimoto K, Uchino J, Yokoi T, Kijima T, Goto Y, Nakao A, et al. Impact of cancer cachexia on the therapeutic outcome of combined chemoimmunotherapy in patients with non-small cell lung cancer: a retrospective study. OncoImmunology. 2021;10:1950411. 10.1080/2162402X.2021.1950411.34290909 10.1080/2162402X.2021.1950411
15. Guo Y Xiang D Wan J Yang L Zheng C Focus on the dynamics of neutrophil-to-lymphocyte ratio in cancer patients treated with immune checkpoint inhibitors: a meta-analysis and systematic review Cancers (Basel). 2022 14 5297 10.3390/cancers14215297 36358716
Guo Y, Xiang D, Wan J, Yang L, Zheng C. Focus on the dynamics of neutrophil-to-lymphocyte ratio in cancer patients treated with immune checkpoint inhibitors: a meta-analysis and systematic review. Cancers (Basel). 2022;14:5297. 10.3390/cancers14215297.36358716 10.3390/cancers14215297
16. Sordo-Bahamonde C Lorenzo-Herrero S Gonzalez-Rodriguez AP Martínez-Pérez A Rodrigo JP García-Pedrero JM Chemo-immunotherapy: a new trend in cancer treatment Cancers (Basel). 2023 15 2912 10.3390/cancers15112912 37296876
Sordo-Bahamonde C, Lorenzo-Herrero S, Gonzalez-Rodriguez AP, Martínez-Pérez A, Rodrigo JP, García-Pedrero JM, et al. Chemo-immunotherapy: a new trend in cancer treatment. Cancers (Basel). 2023;15:2912. 10.3390/cancers15112912.37296876 10.3390/cancers15112912
17. Arbour KC Mezquita L Long N Rizvi H Auclin E Ni A Impact of baseline steroids on efficacy of programmed cell death-1 and programmed death-ligand 1 blockade in patients with non-small-cell lung cancer J Clin Oncol 2018 36 2872 2878 10.1200/JCO.2018.79.0006 30125216
Arbour KC, Mezquita L, Long N, Rizvi H, Auclin E, Ni A, et al. Impact of baseline steroids on efficacy of programmed cell death-1 and programmed death-ligand 1 blockade in patients with non-small-cell lung cancer. J Clin Oncol. 2018;36:2872–8. 10.1200/JCO.2018.79.0006.30125216 10.1200/JCO.2018.79.0006
18. Petrelli F Signorelli D Ghidini M Ghidini A Pizzutilo EG Ruggieri L Cabiddu M Association of steroids use with survival in patients treated with immune checkpoint inhibitors: a systematic review and meta-analysis Cancers (Basel). 2020 12 546 10.3390/cancers12030546 32120803
Petrelli F, Signorelli D, Ghidini M, Ghidini A, Pizzutilo EG, Ruggieri L, Cabiddu M, et al. Association of steroids use with survival in patients treated with immune checkpoint inhibitors: a systematic review and meta-analysis. Cancers (Basel). 2020;12:546. 10.3390/cancers12030546.32120803 10.3390/cancers12030546
19. Ricciuti B Dahlberg SE Adeni A Sholl LM Nishino M Awad MM Immune checkpoint inhibitor outcomes for patients with non-small-cell lung cancer receiving baseline orticosteroids for palliative versus nonpalliative indications J Clin Oncol 2019 37 1927 1934 10.1200/JCO.19.00189 31206316
Ricciuti B, Dahlberg SE, Adeni A, Sholl LM, Nishino M, Awad MM. Immune checkpoint inhibitor outcomes for patients with non-small-cell lung cancer receiving baseline orticosteroids for palliative versus nonpalliative indications. J Clin Oncol. 2019;37:1927–34. 10.1200/JCO.19.00189.31206316 10.1200/JCO.19.00189
20. Pinato DJ Howlett S Ottaviani D Urus H Patel A Mineo T Association of prior antibiotic treatment with survival and response to immune checkpoint inhibitor therapy in patients with cancer JAMA Oncol 2019 5 1774 1778 10.1001/jamaoncol.2019.2785 31513236
Pinato DJ, Howlett S, Ottaviani D, Urus H, Patel A, Mineo T, et al. Association of prior antibiotic treatment with survival and response to immune checkpoint inhibitor therapy in patients with cancer. JAMA Oncol. 2019;5:1774–8. 10.1001/jamaoncol.2019.2785.31513236 10.1001/jamaoncol.2019.2785
21. Homicsko K Richtig G Tuchmann F Tsourti Z Hanahan D Coukos G Proton pump inhibitors negatively impact survival of PD-1 inhibitor based therapies in metastatic melanoma patients Ann Oncol 2018 29 X40 10.1093/annonc/mdy511.001
Homicsko K, Richtig G, Tuchmann F, Tsourti Z, Hanahan D, Coukos G, et al. Proton pump inhibitors negatively impact survival of PD-1 inhibitor based therapies in metastatic melanoma patients. Ann Oncol. 2018;29:X40. 10.1093/annonc/mdy511.001.10.1093/annonc/mdy511.001
22. Cao D Xu H Xu X Guo T Ge W A reliable and feasible way to predict the benefits of Nivolumab in patients with non-small cell lung cancer: a pooled analysis of 14 retrospective studies OncoImmunology. 2018 7 e1507262 10.1080/2162402X.2018.1507262 30377569
Cao D, Xu H, Xu X, Guo T, Ge W. A reliable and feasible way to predict the benefits of Nivolumab in patients with non-small cell lung cancer: a pooled analysis of 14 retrospective studies. OncoImmunology. 2018;7:e1507262. 10.1080/2162402X.2018.1507262.30377569 10.1080/2162402X.2018.1507262
23. Chen S Li R Zhang Z Huang Z Cui P Jia W Prognostic value of baseline and change in neutrophil-to-lymphocyte ratio for survival in advanced non-small cell lung cancer patients with poor performance status receiving PD-1 inhibitors Transl Lung Cancer Res. 2021 10 1397 1407 10.21037/tlcr-21-43 33889518
Chen S, Li R, Zhang Z, Huang Z, Cui P, Jia W, et al. Prognostic value of baseline and change in neutrophil-to-lymphocyte ratio for survival in advanced non-small cell lung cancer patients with poor performance status receiving PD-1 inhibitors. Transl Lung Cancer Res. 2021;10:1397–407. 10.21037/tlcr-21-43.33889518 10.21037/tlcr-21-43
24. Eisenhauer EA Therasse P Bogaerts J Schwartz LH Sargent D Ford R New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1) Eur J Cancer 2009 45 228 247 10.1016/j.ejca.2008.10.026 19097774
Eisenhauer EA, Therasse P, Bogaerts J, Schwartz LH, Sargent D, Ford R, et al. New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). Eur J Cancer. 2009;45:228–47. 10.1016/j.ejca.2008.10.026.19097774 10.1016/j.ejca.2008.10.026
25. Common Terminology Criteria for Adverse Events (CTCAE). v.5.0. United States Department of Health and Human Services National Institutes of Health—National Cancer Institute. 2017. https://www.meddra.org/. Accessed 31 May 2023.
26. Shaverdian N Lisberg AE Bornazyan K Veruttipong D Goldman JW Formenti SC Previous radiotherapy and the clinical activity and toxicity of pembrolizumab in the treatment of non-small-cell lung cancer: a secondary analysis of the KEYNOTE-001 phase 1 trial Lancet Oncol 2017 18 895 903 10.1016/S1470-2045(17)30380-7 28551359
Shaverdian N, Lisberg AE, Bornazyan K, Veruttipong D, Goldman JW, Formenti SC, et al. Previous radiotherapy and the clinical activity and toxicity of pembrolizumab in the treatment of non-small-cell lung cancer: a secondary analysis of the KEYNOTE-001 phase 1 trial. Lancet Oncol. 2017;18:895–903. 10.1016/S1470-2045(17)30380-7.28551359 10.1016/S1470-2045(17)30380-7
27. Kim JH Multicollinearity and misleading statistical results Korean J Anesthesiol 2019 72 558 569 10.4097/kja.19087 31304696
Kim JH. Multicollinearity and misleading statistical results. Korean J Anesthesiol. 2019;72:558–69. 10.4097/kja.19087.31304696 10.4097/kja.19087
28. Chen Q Zhang Z Li X Feng S Liu S Analysis of prognostic factors affecting immune checkpoint inhibitor therapy in tumor patients exposed to antibiotics Front Oncol 2023 13 1204248 10.3389/fonc.2023.1204248 37483503
Chen Q, Zhang Z, Li X, Feng S, Liu S. Analysis of prognostic factors affecting immune checkpoint inhibitor therapy in tumor patients exposed to antibiotics. Front Oncol. 2023;13:1204248. 10.3389/fonc.2023.1204248.37483503 10.3389/fonc.2023.1204248
29. Xia H Zhang W Zhang Y Shang X Liu Y Wang X Liver metastases and the efficacy of immune checkpoint inhibitors in advanced lung cancer: a systematic review and meta-analysis Front Oncol 2022 12 978069 10.3389/fonc.2022.978069 36330494
Xia H, Zhang W, Zhang Y, Shang X, Liu Y, Wang X. Liver metastases and the efficacy of immune checkpoint inhibitors in advanced lung cancer: a systematic review and meta-analysis. Front Oncol. 2022;12:978069. 10.3389/fonc.2022.978069.36330494 10.3389/fonc.2022.978069
30. Kalafati L Mitroulis I Verginis P Chavakis T Kourtzelis I Neutrophils as orchestrators in tumor development and metastasis formation Front Oncol 2020 10 581457 10.3389/fonc.2020.581457 33363012
Kalafati L, Mitroulis I, Verginis P, Chavakis T, Kourtzelis I. Neutrophils as orchestrators in tumor development and metastasis formation. Front Oncol. 2020;10:581457. 10.3389/fonc.2020.581457.33363012 10.3389/fonc.2020.581457
31. Oberg HH Wesch D Kalyan S Kabelitz D Regulatory interactions between neutrophils, tumor cells and t cells Front Immunol 2019 10 1690 10.3389/fimmu.2019.01690 31379875
Oberg HH, Wesch D, Kalyan S, Kabelitz D. Regulatory interactions between neutrophils, tumor cells and t cells. Front Immunol. 2019;10:1690. 10.3389/fimmu.2019.01690.31379875 10.3389/fimmu.2019.01690
32. Takakura K Ito Z Suka M Kanai T Matsumoto Y Odahara S Comprehensive assessment of the prognosis of pancreatic cancer: peripheral blood neutrophil-lymphocyte ratio and immunohistochemical analyses of the tumour site Scand J Gastroenterol 2016 51 610 617 10.3109/00365521.2015.1121515 26679084
Takakura K, Ito Z, Suka M, Kanai T, Matsumoto Y, Odahara S, et al. Comprehensive assessment of the prognosis of pancreatic cancer: peripheral blood neutrophil-lymphocyte ratio and immunohistochemical analyses of the tumour site. Scand J Gastroenterol. 2016;51:610–7. 10.3109/00365521.2015.1121515.26679084 10.3109/00365521.2015.1121515
33. Ohki S Shibata M Gonda K Machida T Shimura T Nakamura I Circulating myeloid-derived suppressor cells are increased and correlate to immune suppression, inflammation and hypoproteinemia in patients with cancer Oncol Rep 2012 28 453 458 10.3892/or.2012.1812 22614133
Ohki S, Shibata M, Gonda K, Machida T, Shimura T, Nakamura I, et al. Circulating myeloid-derived suppressor cells are increased and correlate to immune suppression, inflammation and hypoproteinemia in patients with cancer. Oncol Rep. 2012;28:453–8. 10.3892/or.2012.1812.22614133 10.3892/or.2012.1812
34. Restifo NP Dudley ME Rosenberg SA Adoptive immunotherapy for cancer: harnessing the T cell response Nat Rev Immunol 2012 12 269 281 10.1038/nri3191 22437939
Restifo NP, Dudley ME, Rosenberg SA. Adoptive immunotherapy for cancer: harnessing the T cell response. Nat Rev Immunol. 2012;12:269–81. 10.1038/nri3191.22437939 10.1038/nri3191
35. Liu D Jin J Zhang L Li L Song J Li W The neutrophil to lymphocyte ratio may predict benefit from chemotherapy in lung cancer Cell Physiol Biochem 2018 46 1595 1605 10.1159/000489207 29694985
Liu D, Jin J, Zhang L, Li L, Song J, Li W. The neutrophil to lymphocyte ratio may predict benefit from chemotherapy in lung cancer. Cell Physiol Biochem. 2018;46:1595–605. 10.1159/000489207.29694985 10.1159/000489207
36. Sato H Tsubosa Y Kawano T Correlation between the pretherapeutic neutrophil to lymphocyte ratio and the pathologic response to neoadjuvant chemotherapy in patients with advanced esophageal cancer World J Surg 2012 36 617 622 10.1007/s00268-011-1411-1 22223293
Sato H, Tsubosa Y, Kawano T. Correlation between the pretherapeutic neutrophil to lymphocyte ratio and the pathologic response to neoadjuvant chemotherapy in patients with advanced esophageal cancer. World J Surg. 2012;36:617–22. 10.1007/s00268-011-1411-1.22223293 10.1007/s00268-011-1411-1
37. Grenader T Nash S Plotkin Y Furuse J Mizuno N Okusaka T Derived neutrophil lymphocyte ratio may predict benefit from cisplatin in the advanced biliary cancer: the ABC-02 and BT-22 studies Ann Oncol 2015 26 1910 1916 10.1093/annonc/mdv253 26037798
Grenader T, Nash S, Plotkin Y, Furuse J, Mizuno N, Okusaka T, et al. Derived neutrophil lymphocyte ratio may predict benefit from cisplatin in the advanced biliary cancer: the ABC-02 and BT-22 studies. Ann Oncol. 2015;26:1910–6. 10.1093/annonc/mdv253.26037798 10.1093/annonc/mdv253
38. Wang D Chen C Gu Y Lu W Zhan P Liu H Immune-related adverse events predict the efficacy of immune checkpoint inhibitors in lung cancer patients: a meta-analysis Front Oncol 2021 11 631949 10.3389/fonc.2021.631949 33732650
Wang D, Chen C, Gu Y, Lu W, Zhan P, Liu H, et al. Immune-related adverse events predict the efficacy of immune checkpoint inhibitors in lung cancer patients: a meta-analysis. Front Oncol. 2021;11:631949. 10.3389/fonc.2021.631949.33732650 10.3389/fonc.2021.631949
39. Zhang W Tan Y Li Y Liu J Neutrophil to lymphocyte ratio as a predictor for immune-related adverse events in cancer patients treated with immune checkpoint inhibitors: a systematic review and meta-analysis Front Immunol 2023 14 1234142 10.3389/fimmu.2023.123414 37622124
Zhang W, Tan Y, Li Y, Liu J. Neutrophil to lymphocyte ratio as a predictor for immune-related adverse events in cancer patients treated with immune checkpoint inhibitors: a systematic review and meta-analysis. Front Immunol. 2023;14:1234142. 10.3389/fimmu.2023.123414.37622124 10.3389/fimmu.2023.123414
