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Neutrophil-to-lymphocyte ratio-based prognostic score can predict outcomes in patients with advanced non-small cell lung cancer treated with immunotherapy plus chemotherapy

BMC Cancer volume 25, Article number: 697 (2025) Cite this article

Abstract

Backgroud

Immune checkpoint inhibitor (ICI) plus chemotherapy has become the standard of care for advanced non-small cell lung cancer (NSCLC). Nonetheless, reliable efficacy biomarkers of ICI plus chemotherapy are lacking. In this research, we sought to explore efficacy biomarkers and construct robust prognostic models in NSCLC patients treated with ICI plus chemotherapy.

Methods

We retrospectively analyzed 171 patients with advanced NSCLC treated with ICI plus chemotherapy. Clinical characteristics and peripheral blood inflammatory indexes were collected and prognostic models were constructed to explore efficacy and prognosis biomarkers of ICI plus chemotherapy.

Results

In the cohort that received first-line ICI plus chemotherapy, pre-treatment neutrophil-to-lymphocyte ratio (NLR) > 3.3 and fibrinogen (FIB) > 3.196 were associated with worse efficacy and were independent risk factors of progression-free survival (PFS). Compared to programmed cell death ligand 1 (PD-L1), the derived NLR-FIB (NF) score had significantly improved accuracy in predicting efficacy and prognosis. In advanced NSCLC patients with targetable oncogenic driver alterations receiving second- or post-line ICI plus chemotherapy, pre-treatment NLR > 3.53 was associated with worse efficacy and was an independent risk factor of PFS and OS; Tyrosine kinase inhibitor (TKI)-PFS > 12 months were independent risk factors of overall survival (OS). Secondary epidermal growth factor receptor (EGFR)-T790M mutation, platelet-to-lymphocyte ratio (PLR) > 196.81 and albumin (ALB) < 40.25 were associated with worse PFS. Based on NLR and TKI-PFS, an NLR-TKI-PFS (NTP) score was constructed with three OS risk prognosis categories: favorable, intermediate, and poor (corresponding to a median OS of 21, 12, and 5.3 months).

Conclusions

The noninvasive NF score, combining NLR > 3.3 and FIB > 3.196, was superior to PD-L1 estimated from tumor tissue in predicting the efficacy and prognosis of first-line ICI plus chemotherapy in advanced NSCLC patients. The noninvasive NTP score, combining NLR > 3.53 and TKI-PFS > 12 months, is a valuable tool for predicting OS and PFS in advanced NSCLC patients with targetable oncogenic driver alterations receiving second- or post-line ICI combination therapy.

Peer Review reports

Backgrounds

Lung cancer is a malignant tumor with among highest morbidity and mortality rates [1]. The development of immune checkpoint inhibitor (ICI) targeting the PD-1/PD-L1 interaction has changed the treatment prospects for cancer patients, and ICI plus chemotherapy has become the first-line standard of care for patients with advanced non-small cell lung cancer (NSCLC) without targetable driver gene alterations [2,3,4]. However, only 15–30% of patients achieve long-term survival [5, 6]. Therefore, to improve the efficacy of ICI plus chemotherapy and achieve the goal of precision treatment, the exploration of ICI plus chemotherapy biomarkers has received considerable attention.

PD-L1 stands out as one of the most well-established and extensively validated predictive biomarkers for ICI in NSCLC [7]. Patients with a PD-L1 tumor cell proportion score (TPS) ≥ 50% are most likely to benefit from ICI and can be treated with ICI monotherapy [8, 9]. Nevertheless, people with high PD-L1 expression account for only 27% of the total population, most NSCLC patients have low PD-L1 expression and their 5-year survival rate with ICI plus chemotherapy remains below 20% [5]. Besides, some PD-L1-negative patients may still benefit from ICI plus chemotherapy [10, 11]. Therefore, the use of PD-L1 as a marker for ICI plus chemotherapy is not ideal. Similarly, current studies yield inconsistent results regarding the predictive value of tumor mutational burden (TMB) for ICI [12,13,14]. Moreover, according to the tumor microenvironment (TME), the immune cell status can be used to categorize tumor immune infiltration patterns, thereby enabling prediction of the efficacy of ICI [15]. Nonetheless, challenges remain in effectively applying this to clinical practice.

Current immunological predictive markers have been explored from various perspectives such as at cellular level [16], DNA level [17, 18], protein level [19,20,21,22], and patients’ intrinsic factors (e.g., inflammation and nutritional indicators) [23]. Compared with tissue sample-based assays, patients’ intrinsic factors have the advantages of being cost-effective, noninvasive, and easily accessible. Therefore, in this study, we primarily focused on exploring patients’ intrinsic factors to find more robust markers that can predict the response to ICI plus chemotherapy than PD-L1 expression level.

Chronic inflammation and immune evasion are the main features of cancer occurrence and development [24]. Previous research has elucidated the molecular mechanisms of inflammation-related carcinogenesis and found several candidate biomarkers [18, 21]. Moreover, some peripheral blood inflammatory markers have been found to be related to the prognosis of ICI monotherapy in NSCLC, such as the neutrophil-to-lymphocyte ratio (NLR) and derived NLR (dNLR) [25,26,27,28,29]. However, their prognostic value in patients who receive ICI plus chemotherapy is still unknown. For example, based on the dNLR and lactate dehydrogenase (LDH), Mezquita et al. developed a lung immune prognostic index (LIPI) status for patients with advanced NSCLC treated with first-line ICI and showed that good LIPI status was associated with better clinical outcomes [29]. However, Wang et al. demonstrated that LIPI status could be a prognostic marker of the treatment response to ICI monotherapy but not to ICI plus chemotherapy [30]. Furthermore, studies that amalgamate multiple peripheral blood inflammatory markers in first-line ICI plus chemotherapy and offer cross-sectional comparisons with PD-L1 remain relatively scarce. Consequently, one objective of this study was to explore cost-effective, noninvasive, and easily accessible markers in combination with PD-L1 or to discover superior biomarkers, elucidating their value in predicting the efficacy and prognosis of first-line ICI plus chemotherapy.

In addition to first-line ICI plus chemotherapy for patients without targetable oncogenic driver alterations, we also addressed second-line immunotherapy for patients with targetable oncogenic driver alterations after developing resistance to targeted therapy. Epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) have shown outstanding efficacy in the treatment of patients with EGFR-mutated NSCLC [31, 32]; however, nearly all patients eventually develop drug resistance. Among patients with resistance to first- or second-generation EGFR-TKIs, 50% have T790M resistance mutations, which is sensitive to third-generation EGFR-TKI therapy [33]. However, for patients with unknown resistance mechanisms who do not have T790M mutations or who have failed third-generation EGFR-TKI therapy, rescue treatment remains a challenging issue in clinical practice [34]. Chemotherapy has been the standard of care for those patients with unknown resistance mechanisms after TKI treatment [35]. However, its effectiveness is limited, with median progression-free survival (mPFS) of only 4–5 months [36]. In addition, although ICI demonstrated greater effectiveness than chemotherapy in second-line treatment [37,38,39], second-line ICI monotherapy was not superior to standard chemotherapy regimens for patients harboring driver gene mutations, with an objective response rate (ORR) of only about 10–20% and a mPFS of only 2–3 months [40]. Our previous research also explained the poor efficacy of ICI monotherapy as a result of the immunosuppressive microenvironment from the perspective of the TME [41]. Preclinical studies have shown that chemotherapy can activate immune responses through various mechanisms and has a synergistic effect when used in combination with ICI [42]. Second-line ICI plus chemotherapy have yielded promising outcomes. A clinical study demonstrated a mPFS of up to 7 months in EGFR-TKI-resistant patients without T790M mutation treated with ICI plus chemotherapy [43]. Consistently, favorable findings in clinical trials such as IMPOWER 150 and ORIENT-31 also demonstrated higher efficacy with the addition of ICI to bevacizumab and chemotherapy than with the standard of care [44,45,46]. As a result, the combination immunotherapy obtained approval from the National Medical Products Administration for its indications, making it currently the highest-evidence treatment option in evidence-based medicine. Nonetheless, the results of the IMPOWER 151 study presented at the 2023 World Conference on Lung Cancer (WCLC) Annual Meeting did not find a clinical benefit of the four-drug regimen comprising bevacizumab plus chemotherapy containing a PD-L1 monoclonal antibody over bevacizumab in combination with chemotherapy. Taking these findings together, controversy remains regarding second-line treatment for patients with unexplained resistance mechanisms to EGFR-TKIs. Although ICI plus chemotherapy is a promising treatment strategy, clinical research data indicate limited benefits in the unscreened general population. Future development should move in a biomarker-driven direction to identify potential populations that would benefit from ICI combination therapy, thereby avoiding unnecessary medical expenses.

To date, predictive biomarkers for the outcomes of second-line ICI plus chemotherapy have not been identified [47]. The predictive value of the currently recognized immunotherapy biomarker PD-L1 is debatable in second-line immunology [48, 49]. Zhou et al. conducted an analysis of peripheral blood immune cells using full-spectrum flow cytometry and demonstrated that the expression type and level of immune checkpoint proteins on immune cells are related to the outcomes of subsequent ICI plus chemotherapy in patients with EGFR-TKI-resistant NSCLC [50]. Nevertheless, the value of more cost-effective and easily accessible peripheral blood parameters, such as NLR, in predicting the prognosis of TKI-resistant patients with NSCLC who are receiving ICI plus chemotherapy remains unclear. Consequently, another objective of this study was to explore potential prognostic biomarkers for NSCLC patients with targetable oncogenic driver alterations from the perspective of peripheral blood indexes to offer valuable insights for guiding treatment decisions regarding second- or post-line ICI combination therapy following the development of resistance to TKIs.

Methods

Study design and participants

We conducted a retrospective analysis involving 131 patients with advanced NSCLC who attended Nanfang Hospital between January 2019 and October 2022 to receive first-line ICI plus chemotherapy. We also enrolled 40 advanced NSCLC patients with targetable oncogenic driver alterations who exhibited unexplained resistance to TKI treatment to receive second- or post-line ICI combination therapy. Among the patient cohort, individuals with comorbid hematologic or autoimmune diseases, co-infections, a history of hormone usage within 2 weeks prior to treatment initiation, or those lacking consistent follow-up were excluded from the study. The study was approved by the Ethics Committee of Nanfang Hospital.

Data collection

Data on patients’ clinical characteristics and laboratory tests were anonymized and extracted from the electronic medical record system. The unit measures for the laboratory variables are as follows: FIB: g/L; LDH: U/L; D-Dimer: ug/mL; CRP: mg/L; ALB: g/L; HGB: g/L. All peripheral blood indicators were collected 1 week before immunotherapy. Moreover, the PD-L1 expression (tumor proportion score (TPS)) was evaluated by PD-L1 IHC 22C3 pharmDx assay (Agilent Technologies China, Beijing, China). Therapeutic efficacy assessment adopts the Response Evaluation Criteria in Solid Tumors 1.1 (RECIST 1.1), which includes categories of complete remission (CR), partial remission (PR), stable disease (SD), and progressive disease (PD). Recent efficacy assessment is based on the ORR and disease control rate (DCR). The ORR is defined as the sum of the number of CR and PR cases divided by the total number of cases. DCR is defined as the sum of CR, PR, and SD cases divided by the total number of cases. Prognosis assessment is based on PFS and overall survival (OS). PFS is defined as the time from the start of treatment to the first determination of tumor progression or the follow-up endpoint. OS is defined as the time from the start of treatment to death for any reason or the follow-up endpoint.

Statistical analysis

The NLR was calculated by dividing the absolute counts of neutrophils and lymphocytes measured in peripheral blood; the same applied to platelet-to-lymphocyte ratio (PLR). Analysis was conducted using the receiver operating characteristic (ROC) curve and area under the ROC curve (AUC), and the Youden Index was calculated based on the ROC curve. The maximum Youden Index are established as the optimal threshold values of NLR, PLR, fibrinogen (FIB), LDH, D-Dimer, C-reactive protein (CRP), albumin (ALB), and the CD4+/CD8 + T lymphocyte ratio, thereby dividing various peripheral blood indicators into two groups: high and low. The threshold for hemoglobin (HGB) in this study was set at 120 g/L according to the criteria for anemia.

We used chi-square tests or Fisher’s exact probability method to compare the demographic characteristics of patients with count data or to compare the differences in treatment effectiveness between patient groups. Kaplan-Meier survival analysis was performed in the two patient groups, and differences between the groups were assessed using the log-rank test. Variables with P < 0.1 were included in the multivariate regression analysis. Multivariate regression analysis was conducted using the Cox proportional hazards model. Differences in continuous variables with a normal distribution among multiple groups were analyzed using one-way analysis of variance, and differences in continuous variables with a non-normal distribution among multiple groups were analyzed using nonparametric tests.

All data were analyzed using SPSS 25.0 software (New York, USA) and GraphPad Prism (version 9.0, USA). All P-values were based on two-sided hypotheses, with statistical significance set at P < 0.05.

Results

Patient characteristics in first-line ICI plus chemotherapy

In this study, we enrolled 131 patients with advanced NSCLC who did not have targetable oncogenic driver alterations and who received first-line combination immunotherapy. The median age of the study population was 59 years. Most patients were men (105/131, 80.2%), had a history of smoking (96/131, 73.3%), and had positive PD-L1 expression (74/98, 75.5%) (Table 1).

Table 1 Patient characteristics in first-line ICI plus chemotherapy
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According to the ROC curves (Supplementary material 1), the optimal cutoff values for NLR, FIB, LDH, D-Dimer, CRP, ALB, and the CD4+/CD8 + T lymphocyte ratio were 3.30, 3.92, 198.00, 0.53, 7.74, 43.95 and 1.73 respectively. In the high NLR group, the number of patients in stage IV was significantly higher than that in the low NLR group (P = 0.001). However, there were no significant differences between different pre-treatment NLR levels and clinical characteristics such as sex, age, smoking status, pathological tissue type, baseline liver metastasis, baseline brain metastasis, and PD-L1 expression (Table 1).

Analysis of factors affecting efficacy of first-line ICI plus chemotherapy

The results showed that squamous carcinoma was correlated with a better ORR than adenocarcinoma (P = 0.041) (Fig. 1A). In contrast, age, sex, liver metastasis, smoking status, PD-L1 expression, NLR, HGB, LDH, FIB, D-dimer, ALB, CRP, and the CD4/CD8 + T lymphocyte ratio were not associated with the ORR of first-line ICI plus chemotherapy (Table 2). As for the DCR, a low NLR (P = 0.011) and low FIB (P = 0.024) were correlated with a better DCR than a high NLR and high FIB (Fig. 1B, 1 C). In contrast, age, sex, histology, liver metastasis, smoking status, PD-L1 expression, HGB, CRP, ALB, LDH, D-Dimer, and the CD4/CD8 + T lymphocyte ratio were not associated with the DCR of first-line ICI plus chemotherapy (Table 2).

Table 2 Relationship between clinical characteristics and peripheral blood indexes and the outcome of first-line ICI plus chemotherapy
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Univariate analysis revealed that only NLR and FIB were associated with DCR, in the pursuit of seek a more effective and comprehensive indicator, we further combined these two variables to establish the NLR-FIB score (hereafter referred to as NF score). A score of 1 was assigned for each risk factor when NLR > 3.3 or FIB > 3.915. These scores categorized patients according to three groups: [1] Group 0 with low NLR and low FIB [2], Group 1 with high NLR or high FIB [3], Group 2 with high NLR and high FIB. Fisher’s exact test demonstrated that the DCR was 100% in Group 0, 97.9% in Group 1, and 81.6% in Group 2 (P < 0.05) (Fig. 1D). ROC curves were plotted for predicting the DCR (Fig. 1E). The AUC values for the NLR, FIB, NF score, PD-L1, and NFP score (which incorporates both the NF score and PD-L1) were 0.778, 0.781, 0.798, 0.528, and 0.731, respectively, with corresponding P-values of 0.015, 0.014, 0.007, 0.804, and 0.009. These findings suggest that the value of the NF score for accessing the efficacy of first-line ICI combination therapy was superior to that of single indexes and even PD-L1 (TPS ≥ 1%).

Multivariate cox regression analysis of factors related to PFS in response to first-line ICI plus chemotherapy

Kaplan-Meier survival curves showed that stage IV, NLR, FIB, HGB, LDH, CRP, D-Dimer, and the CD4/CD8 + T lymphocyte ratio were correlated with PFS (Fig. 2A H, Table 2). In multivariate Cox regression analysis, NLR (hazard ratio [HR] 3.834; 95% confidence interval [CI] 2.228–48.294, P < 0.001) and FIB (HR 2.043; 95% CI 1.755–3.552, P = 0.011) were independent prognostic factors for PFS (Table 3).

Table 3 Multivariate analysis of factors affecting PFS in first-line ICI plus chemotherapy
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After screening by multivariate Cox regression, only NLR and FIB were independent prognostic factors for PFS. Therefore, the NF score was applied again and compared its prognostic value with that of PD-L1 expression. Based on the NF score, the median PFS for patients in the 0-score group was not reached; for patients in the 1-score group, the median PFS was 13.5 months; and for patients in the 2-score group, the median PFS was 6.5 months (P < 0.05) (Fig. 2I). The ROC curves were plotted for predicting PFS (Fig. 2J). The AUC values for NLR, FIB, NF score, PD-L1, and NFP score were 0.72, 0.698, 0.747, 0.54, and 0.664, respectively, with corresponding P-values of 0.001, 0.003, < 0.001, 0.548, and 0.013. These findings suggest that the prognostic value of the NF score was also better than that of single indexes and even PD-L1 (TPS ≥ 1%).

Dynamic changes in NLR and FIB during first-line ICI plus chemotherapy

In this study, NLR and FIB data were collected at three time points: baseline, RD (Response Disease, including Partial Response (PR) and Stable Disease (SD)), and PD. Among these, 89 patients had paired NLR data available at all three time points. NLR significantly decreased at the RD time point compared to the baseline (P = 0.001). Conversely, NLR increased again at the PD time point (P < 0.001), suggesting a substantial reduction in NLR levels during the treatment response phase followed by an elevation during immunotherapy resistance. Regarding FIB, 55 patients had paired data available at all three time points, and the results showed a similar trend to NLR; however, the differences did not reach statistical significance (Fig. 3).

Fig. 1
figure 1

Treatment response of first-line ICI plus chemotherapy according to (A) Histology; (B) NLR level; (C) FIB level; (D) NF score. (E) ROC curves of the NLR, FIB, PD-L1, NF score and NFP score to predict DCR

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Fig. 2
figure 2

Kaplan–Meier curves for progression-free survival (PFS) of first-line ICI plus chemotherapy according to (A) Clinical stage; (B) NLR level; (C) FIB level; (D) HGB level; (E) CRP level; (F) LDH level; (G) D-Dimer level; (H) CD4/CD8 + T lymphocyte ratio; (I) NF score. (J) ROC curves of the NLR, FIB, PD-L1, NF score and NFP score to predict PFS

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Fig. 3
figure 3

Dynamic changes in NLR level (A) and FIB level (B) before (pre) and after (post) first-line ICI plus chemotherapy for patients with paired blood samples

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Patient characteristics in second- or post-line ICI combination therapy

We enrolled 40 advanced NSCLC patients with targetable oncogenic driver alterations who received second- or post-line combination immunotherapy after developing resistance to targeted drugs. The median age of the study population was 60 years. Most patients were female (23/40, 57.5%), nonsmokers (27/40, 67.5%), had positive PD-L1 expression (12/20, 60%), and EGFR mutations (36/40, 90%). Thirteen patients (38.2%) developed EGFR-T790M mutations after developing resistance to EGFR-TKIs. Seventeen patients (42.5%) received second-line ICI combination therapy, and 23 patients (57.5%) received post-line ICI combination therapy (Table 4).

Table 4 Clinical characteristics of patients in second- or post-line ICI plus chemotherapy
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According to the ROC curves (Supplementary material 2), the optimal cutoff values for NLR, PLR, CRP, and ALB were 3.525, 196.805, 16.115, and 40.25, respectively. There was no significant correlation between different pre-treatment NLR levels and clinical characteristics such as sex, age, smoking history, number of treatment lines, baseline liver metastases, PD-L1 expression, TKI-PFS, and secondary EGFR-T790M mutation (Table 4).

Analysis of factors affecting efficacy of second- or post-line ICI combination therapy

The results showed that low NLR levels were associated with higher ORR (P = 0.046) and tended to be associated with higher DCR (Table 5). In contrast, age, sex, baseline liver metastases, smoking history, number of lines of therapy, secondary T790M mutation, PD-L1 ≥ 1%, TKI-PFS, HGB, PLR, ALB, and CRP levels were not associated with ORR and DCR (Table 5).

Table 5 Relationship between clinical characteristics and peripheral blood indexes and the outcome of second- or post-line ICI plus chemotherapy
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Multivariate cox regression analyses of factors related to OS and PFS in response to second- or post-line ICI combination therapy

Kaplan-Meier survival curves showed that TKI-PFS and NLR were correlated with OS (P = 0.008, P < 0.001, respectively) (Fig. 4A and B). Age, sex, number of lines of treatment, history of smoking, liver metastasis, secondary EGFR-T790M mutation, PD-L1 expression, HGB, CRP, ALB, and PLR levels were not significantly correlated with OS (Table 5). In multivariate Cox regression analysis, NLR (HR 11.918; 95% CI 2.941–48.294, P = 0.001) and TKI-PFS (HR 5.398; 95% CI 1.518–19.2, P = 0.009) were independent prognostic factors for OS (Table 6).

Fig. 4
figure 4

Kaplan–Meier curves for Overall survival (OS) of second- or post-line ICI combination therapy according to (A) TKI-PFS; (B) NLR level. Kaplan–Meier curves for PFS according to (C) Secondary T790M mutation; (D) NLR level; (E) PLR level; (F) ALB level. (G) Kaplan–Meier curves for OS according to NTP score. (H) Kaplan–Meier curves for PFS according to NTP score. (I) ROC curves of the NLR, TKI-PFS and NTP score to predict OS

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Table 6 Multivariate analysis of factors affecting OS and PFS in second- or post-line ICI plus chemotherapy
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In terms of PFS, secondary EGFR-T790M mutation, NLR, PLR, and ALB were associated with PFS (P = 0.029, < 0.001, 0.026, and 0.012, respectively) (Fig. 4C and F; Table 5). In multivariate Cox regression analysis, only NLR (HR 6.95; 95% CI 2.068–23.355, P = 0.002) was an independent prognostic factor for PFS (Table 6).

After screening by multivariate Cox regression, only NLR and TKI-PFS were independent prognostic factors for OS, in the pursuit of seek a more effective and comprehensive indicator, we further combined these two variables to establish the NLR-TKI-PFS score (hereafter referred to as NTP score), where risk factors such as high NLR or long TKI-PFS were each assigned a score of (1) Fourteen (35%) patients had an NTP score of 0, 16 (40%) had an NTP score of 1, and 10 (25%) had an NTP score of (2) The median OS (mOS) of patients with scores of 0, 1, and 2 were 21, 12, and 5.3 months, respectively (P < 0.001) (Fig. 4G). The median PFS times of patients with scores of 0, 1, and 2 were 12.5, 7, and 4.1 months, respectively (P = 0.001) (Fig. 4H). The ROC curves were plotted for predicting OS (Fig. 4I). The AUC values for NLR, TKI-PFS, and NTP score were 0.72, 0.698, and 0.747 (P values of 0.001, 0.003, and P < 0.001, respectively), which indicated that the NTP score had better prognostic value than a single index.

Dynamic changes in NLR during second- or post-line ICI combination therapy

In the second- or post-line immunotherapy cohort, NLR data were collected again at three time points: baseline, RD, and PD. Among these, 15 patients had paired NLR data available at all three time points. NLR decreased at the RD time point compared to the baseline (P = 0.029). NLR increased again at the PD time point (P = 0.012), suggesting a substantial reduction in NLR levels during the treatment response phase followed by an elevation during immunotherapy resistance (Fig. 5).

Fig. 5
figure 5

Dynamic changes in NLR level before (pre) and after (post) second- or post-line ICI combination therapy for patients with paired blood samples

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Discussion

Advanced NSCLC can be categorized into two groups based on gene mutation status. For patients without targetable oncogenic driver alterations, ICI plus chemotherapy is now the first-line standard of care recommended in the guidelines. PD-L1 expression estimated from tumor tissue has gained approval from the US Food and Drug Administration as a biomarker for predicting the response to first-line immunotherapy. However, the therapeutic activity of ICI is the result of a complex interplay between multiple immune cells and factors in the TME [51], it is difficult for a single PD-L1 indicator to precisely predict responses to immunotherapy, especially in terms of the efficacy of ICI plus chemotherapy. Therefore, it remains imperative to discover more robust biomarkers for ICI plus chemotherapy.

Research has shown that the inflammatory environment substantially impacts the effectiveness of immunotherapy. Furthermore, peripheral blood inflammatory markers such as NLR and FIB have gained recognition for their relevance in predicting immunotherapy outcomes [25,26,27,28,29, 52]. Neutrophils contain a subpopulation that promotes tumor growth and metastasis, stimulates angiogenesis, and mediates immunosuppression [53]. Inflammatory processes can stimulate the migration of neutrophils to the tumor periphery, where they release reactive oxygen species (ROS), causing DNA damage in adjacent cells. Moreover, neutrophils induce the secretion of various chemokines, which contribute to tumor growth, neovascularization, and the acceleration of distant metastasis. In addition, lymphocytes can differentiate into tumor-infiltrating lymphocytes (TILs), which play an essential role in the host immune response by effectively inhibiting tumor growth, thus contributing significantly to anti-tumor immunity. A tumor microenvironment characterized by high neutrophil infiltration and low lymphocyte presence promotes angiogenesis, inhibits apoptosis, ultimately resulting in a poor prognosis. Existing research suggests that the expression of NLR was a strong indicator of survival in NSCLC patients [54]and was associated with poor response to ICI monotherapy in NSCLC patients [55]. Other published study also revealed the potential value of the dynamic change of NLR during treatment as a real-time indicator of ICI monotherapy [56, 57]. However, there are few reports on whether NLR and its dynamic changes can predict the efficacy of ICI plus chemotherapy. One study by Miriam et al. enrolled 12 patients with advanced NSCLC undergoing ICI plus chemotherapy and demonstrated that low NLR can be a predictive marker for therapy responses and outcomes [58]. However, the sample size in that study was relatively small; further research is needed to explore the prognostic value of NLR and its dynamic changes in ICI plus chemotherapy. FIB is an important plasma coagulation factor and a marker of a systemic inflammatory response. FIB can be deposited in the extracellular matrix and serves as a substrate for binding with the growth factors of tumor cells, thereby fostering tumor cell proliferation and neovascularization [59, 60]. Consequently, FIB is considered to have an association with poor prognosis in a variety of tumors [61,62,63,64]. Yuan et al. revealed that the pretreatment FIB-ALB ratio (FAR) was an independent predictor for the treatment response and an independent prognostic factor in patients with advanced NSCLC treated with first-line ICI plus chemotherapy [65]. However, the prognostic value of FIB in combination with NLR in advanced NSCLC patients treated with first-line ICI plus chemotherapy is still unknown.

In our study, we found that high pretreatment NLR and FIB levels were independent prognostic factors for poorer PFS in first-line ICI plus chemotherapy. Based on these two independent prognostic factors, we created a unique score called the NF score with three PFS risk prognosis categories: favorable, intermediate, and poor (corresponding mPFS: not reached, 13.5 and 6.5 months). Compared to single indicators that are susceptible to external influences, the more robust NF score demonstrated a better prognostic value. Interestingly, similar studies have not conducted comparisons with tumor PD-L1 expression, which may lead to an underestimation of the relationship between PD-L1 expression and the antitumor effects of ICI plus chemotherapy. Surprisingly, we further found that the NF score detected in blood samples had better performance than PD-L1 estimated from tumor tissue as a reliable efficacy and prognosis biomarkers of first-line ICI plus chemotherapy, with an impressive 79.8% accuracy rate in predicting efficacy (AUC = 0.798), outperforming the value of PD-L1 (AUC = 0.528), and a remarkable 74.7% accuracy rate in predicting prognosis (AUC = 0.747), which was also superior to that of PD-L1 (AUC = 0.54). While PD-L1 expression (TPS ≥ 1%) is a commonly used biomarker for patient selection in immunotherapy, its prognostic value is often limited by variability in its expression and the complex relationship with immune response, and is often not sufficient by itself to predict the outcome of ICI combination therapy. The NF score, which combines NLR and FIB, offers a more dynamic and comprehensive reflection of the systemic inflammatory and coagulation environment, which may be more directly associated with immune modulation and are integral to patient response to ICI plus chemotherapy. Our research suggest that the NF score may serve as a more reliable and specific predictor of ICI plus chemotherapy compared to PD-L1 alone, as it incorporates both immune and inflammatory components that influence response to ICI plus chemotherapy.

In NSCLC patients with targetable oncogenic driver alterations, resistance is inevitably developed after standard targeted therapy. As an emerging antitumor treatment method, the efficacy of immunotherapy in TKI-resistant patients is still a subject of debate. The results of the IMPOWER 150 and ORIENT 31 trials indicated that the PFS of TKI-resistant patients treated with ICI in combination with chemotherapy and bevacizumab are extended in comparison to patients treated with chemotherapy combined with anti-angiogenesis therapy. However, the KEYNOTE 789 (NCT03515837), CHECKMATE 722 (NCT02864251), and IMPOWER 151 trials did not yield positive outcomes. Therefore, the efficacy of ICI combination therapy in NSCLC patients with TKI resistance remains controversial, suggesting that only a subset of patients with unclear TKI resistance mechanisms can benefit from ICI combination therapy. How to utilize existing clinical data and laboratory indicators to select patients who are most likely to benefit from subsequent ICI combination therapy, thereby avoiding unnecessary waste of medical resources, is a challenging issue in clinical practice.

In this study, we further explored the currently challenging issue of whether NSCLC patients with unclear mechanisms after TKI resistance can benefit from second- or post-line ICI combination therapy. Our research results indicated that for TKI-resistant NSCLC patients: [1] ICI combination therapy achieved an ORR of 20%, and a median PFS of 5.85 months; [2] the factor associated with better ORR and prognosis was NLR ≤ 3.53; [3] the factors associated with worse PFS was with secondary T790M mutation, PLR > 196.81 and ALB < 40.25; [4] the factors related to better OS included NLR ≤ 3.53 and TKI-PFS ≤ 12 months. Additionally, based on NLR and TKI-PFS, an NTP score was constructed with three OS risk prognosis categories. Our research innovatively identified a group of low-risk patients (with NLR ≤ 3.53 and TKI-PFS ≤ 12 months), who had longer mOS and mPFS than those in the high-risk group. This was the first study to develop a comprehensive model that incorporates clinical characteristics and easily accessible peripheral blood parameters to predict the prognosis of TKI-resistant NSCLC patients treated with second- or post-line ICI combination therapy. Previous studies have reported that fewer than 60% of patients are willing to undergo invasive re-biopsy after disease progression [66]. Hence, our noninvasive NTP score will be of great importance in providing a reference to screen TKI-resistant NSCLC patients who may benefit from subsequent ICI combination therapy, especially those who are reluctant to undergo re-biopsy following disease progression.

The potential mechanisms underlying the association between TKI-PFS and the benefits of immunotherapy are not yet fully understood. Research by Liu et al. found that patients with shorter TKI-PFS have significantly prolonged PFS and higher ORR in subsequent immune therapy compared to patients with longer TKI-PFS [48]. Their study revealed that patients with shorter TKI-PFS had a higher proportion of CD8 + effector T cells and proliferating T cells; in the longer TKI-PFS cohort, there was a higher ratio of M2-like macrophages to M1-like macrophages. This may lead to a more suppressive tumor microenvironment, potentially impairing the clinical efficacy of immunotherapy. Further basic research is needed to explore these mechanisms in greater depth.

In addition to TKI-PFS, Haratani et al. reported that secondary T790M mutation was negatively correlated with immunotherapy efficacy following EGFR-TKI treatment [67]. In the present study, we also found that patients without secondary EGFR-T790M mutations were more likely to benefit from subsequent ICI combination therapy in terms of PFS than patients with secondary EGFR-T790M mutations. Our research results support the conclusions of Haratani et al., indicating that for patients with secondary EGFR-T790M mutations, subsequent ICI combination therapy may not be the optimal treatment choice.

Cheng et al. found that for EGFR-TKI-resistant patients with NSCLC, liver metastasis is a negative prognostic factor for subsequent ICI combination therapy [68]. In this study, we did not find a relationship between liver metastasis and the effectiveness of subsequent ICI combination therapy. Notably, however, we found that NLR can serve as a prognostic marker for TKI-resistant patients receiving subsequent ICI combination therapy. To our knowledge, previous findings have demonstrated that NLR is a promising biomarker to predict the survival of ICI in advanced NSCLC patients without targetable genomic alterations. However, patients with NSCLC carrying targetable genomic alterations have a unique TME [69, 70], and whether NLR has prognostic value for ICI combination therapy in NSCLC patients with sensitive driver gene mutations remains unclear. Our research elucidates the value of NLR in patients harboring sensitive gene mutations who are undergoing ICI combination therapy. We further integrated NLR and TKI-PFS; the established composite biomarker was more robust, further enhancing the predictive efficacy. Our study can serve as a reference for the selection of TKI-resistant NSCLC patients who may benefit from ICI plus chemotherapy.

Peripheral blood inflammatory biomarkers have shown great promise in predicting responses to ICI therapies due to easy specimen accessibility and the opportunity for serial monitoring. In the two cohorts in our study, it is noteworthy that with an enhanced immune response or ongoing tumor progression, the peripheral blood parameters of NLR also exhibited a corresponding decline or increase. Our study underscores the continued effectiveness of NLR as a reliable indicator of the body’s antitumor immune status over the course of treatment. Moreover, by closely tracking NLR fluctuations before and after treatment, clinicians can gain valuable insights to assess treatment efficacy and predict patient outcomes.

It is important to acknowledge the limitations of this study. This study was a retrospective analysis with a relatively small sample size from a single Chinese cancer institution, which may have resulted in potential objective bias for data collection and analysis. Also, there is currently no unified standard for the critical values of indicators like NLR. Moreover, this study lacks external data to verify the prognostic model. Therefore, future research should focus on establish unified critical thresholds for NLR and other inflammatory indices through large-scale prospective clinical trials, and should aim to conduct multicenter, large-sample, long-term follow-up clinical trials to validate and assess the prognostic ability of the NF and NTP scores. Moreover, future studies should investigate the molecular mechanisms linking NLR fluctuations to immune modulation and treatment resistance in NSCLC.

Conclusions

The NF score we established has the advantages of being noninvasive, easy to access and monitor, economical, and can discriminate potential patients benefit from ICI combined with chemotherapy, while PD-L1 underperformed in predicting response to combination immunotherapy. More importantly, the noninvasive NTP score constructed in this study may provide new insights for screening TKI-resistant NSCLC patients who may benefit from subsequent ICI combination therapy, especially those who are reluctant to undergo re-biopsy following disease progression.

Future perspectives

Future research should focus on establish unified critical thresholds for NLR and other inflammatory indices through multicenter collaborations to enhance reproducibility and clinical applicability, and conduct multicenter, prospective trials with diverse NSCLC cohorts to validate the generalizability of the NF and NTP scores.

Data availability

The datasets used and analysed during the current study available from the corresponding author (Yuanyuan Wang: doc_wang@126.com) on reasonable request.

Abbreviations

NSCLC:

Non-small cell lung cancer

ICI:

Immune checkpoint inhibitor

PD-L1 TPS:

Programmed cell death ligand 1 tumor cell proportion score

NLR:

Neutrophil-to-lymphocyte ratio

FIB:

Fibrinogen

PFS:

Progression-free survival

OS:

Overall survival

ORR:

Objective response rate

DCR:

Disease control rate

EGFR:

Epidermal growth factor receptor

TKI:

Tyrosine kinase inhibitor

NF score:

NLR-FIB score

NTP score:

NLR-TKI-PFS score

TME:

Tumor microenvironment

TMB:

Tumor mutation burden

LDH:

Lactate dehydrogenase

HGB:

Hemoglobin

CRP:

C-reactive protein

ALB:

Albumin

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Acknowledgements

The author would like to thank all the patients involved in this study and to all of the research staff who participated in this study.

Funding

This work was supported by the Wu Jieping Medical Foundation (Grant Number: 320.6750.2022-22-21) and the Chinese Thoracic Oncology Group Lung Cancer Research Foundation (Grant Number: CTONG-YC20220107).

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Authors and Affiliations

  1. Department of Oncology, Nanfang Hospital, Southern Medical University, 1838 North Guangzhou Avenue, Guangzhou, 510515, Guangdong, China

    Shan Liao, Huiying Sun, Hao Lu, Jiani Wu, Jianhua Wu, Zhe Wu, Jingle Xi, Wangjun Liao & Yuanyuan Wang

  2. Cancer Center, the Sixth Affiliated Hospital, School of Medicine, South China University of Technology, Foshan, China

    Wangjun Liao

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  1. Shan Liao
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  2. Huiying Sun
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  3. Hao Lu
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  9. Yuanyuan Wang
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Contributions

Yuanyuan Wang and Wangjun Liao were responsible for the conception and design of this study. Shan Liao conducted research and performed statistical analysis. Huiying Sun, Hao Lu, Jiani Wu, Jianhua Wu, Zhe Wu and Jingle Xi collected and analyzed the data and provided critical input. Shan Liao interpreted the data. Shan Liao wrote the manuscript. All authors reviewed the manuscript and approved the final version of manuscript.

Corresponding authors

Correspondence to Wangjun Liao or Yuanyuan Wang.

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Ethics approval and consent to participate

The study was approved by the Ethics Committee of Nanfang Hospital (NFEC-BPE-098). This is an observational and retrospective study that has obtained exemption from informed consent from the Ethics Committee.

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Not applicable.

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The authors declare no competing interests.

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Liao, S., Sun, H., Lu, H. et al. Neutrophil-to-lymphocyte ratio-based prognostic score can predict outcomes in patients with advanced non-small cell lung cancer treated with immunotherapy plus chemotherapy. BMC Cancer 25, 697 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12885-025-13811-y

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Keywords

BMC Cancer

ISSN: 1471-2407

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