Association between neutrophil-to-lymphocyte ratio and risk of immune checkpoint inhibitors-related pneumonitis and radiation pneumonitis in lung cancer: a systematic review and meta-analysis

Introduction

Lung cancer remains leading cause of cancer-related death worldwide (1). There were approximately 2.2 million new cases and 1.8 million deaths attributable to lung cancer, accounting for 11.4% of all new cancer diagnoses and 18% of cancer-related deaths globally (1,2). Non-small cell lung cancer (NSCLC) constitutes about 85% of all lung cancer cases, with the majority diagnosed at an advanced stage. In recent years, immune checkpoint inhibitors (ICIs), such as programmed death-1 (PD-1) and programmed death-ligand 1 (PD-L1) inhibitors, have revolutionized the treatment landscape of advanced NSCLC, significantly improving survival outcomes (3,4). Additionally, radiotherapy continues to be a cornerstone in the management of lung cancer, particularly in locally advanced or oligometastatic settings. Both ICIs and radiotherapy have been increasingly integrated into treatment regimens, offering synergistic antitumor effects.

However, the widespread use of ICIs and thoracic radiotherapy has been accompanied by an increase in treatment-related toxicities, particularly pneumonitis. Immune checkpoint inhibitors-related pneumonitis (CIP) occurs in approximately 3–5% of patients treated with ICIs, with a higher incidence observed in those receiving combination therapies (5,6). Radiation pneumonitis (RP) is a well-recognized complication of thoracic radiotherapy and represents a multifactorial toxicity. Its risk is influenced not only by radiation dose and irradiated lung volume (dose-volume parameters), but also by patient-, tumor-, and treatment-related factors (7). Moreover, with the increasing use of thoracic reirradiation in clinical practice, the risk of severe RP may be even higher due to cumulative lung dose exposure (8). Both CIP and RP lead to treatment interruption, hospitalization, or even mortality, thereby negatively impacting patient prognosis and quality of life. Notably, CIP and RP are distinct clinical entities. CIP is an immune-mediated inflammatory lung toxicity triggered by immune checkpoint blockade, whereas RP is primarily radiation-induced lung injury that is strongly related to lung dose-volume exposure. Although their clinical and radiographic features may overlap in thoracic oncology, their underlying pathophysiology and risk factor profiles differ, which should be considered when interpreting biomarker associations. Despite their clinical significance, reliable biomarkers for predicting the risk of pneumonitis remain limited. The neutrophil-to-lymphocyte ratio (NLR), a readily available indicator of systemic inflammation, has been widely studied as a prognostic factor in various malignancies, including lung cancer (9,10). Elevated NLR has been associated with poor overall survival (OS) and progression-free survival (PFS) in lung cancer. However, whether NLR is associated with the risk of CIP or RP remains unclear.

Therefore, a comprehensive analysis is warranted to evaluate the potential role of NLR in predicting these clinically significant adverse events in lung cancer. We present this article in accordance with the PRISMA reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2026-0791/rc) (11).

Methods

Literature search

We searched PubMed, Embase, Web of Science and Chinese National Knowledge Infrastructure (CNKI) databases up to October 27, 2025 with following terms: neutrophil-to-lymphocyte ratio, NLR, neutrophil/lymphocyte ratio, lung, pulmonary, tumor, cancer, carcinoma, neoplasm, pneumonia AND pneumonitis. Detailed search strategy in PubMed was shown in Appendix 1. Besides, MeSH terms and free texts were applied.

Study selection

Studies meeting following criteria were included: (I) patients were diagnosed with lung cancer and received ICIs or radiotherapy; (II) the NLR was calculated before the ICIs and radiotherapy; (III) the association between NLR and risk of CIP or RP was explored; (IV) odds ratios (ORs) with 95% confidence intervals (CIs) were provided or enough data were provided for their calculation; (V) articles published in English or Chinese and available full texts.

Studies meeting following criteria were excluded: (I) duplicated, overlapped or insufficient data; (II) letters, editorials, reviews, case reports, or animal trials.

Data collection

We extracted following information: first authors, publication year, country, sample size, number of pneumonitis cases, tumor type, tumor stage, cutoff values of NLR, endpoints including the CIP and RP, OR and 95% CI.

Methodological quality assessment

Methodological quality was assessed by Newcastle-Ottawa Scale (NOS) score and studies with the NOS score ≥6 were defined as high-quality studies (12).

The literature search, selection, data extraction and quality assessment were all performed by two authors independently.

Statistical analysis

In our meta-analysis, the I² statistic and Chi-squared test (Q test) were used for statistical heterogeneity. I²>50% and P<0.10 in the Q test were considered indicative of substantial heterogeneity. But, the choice of fixed-effect or random-effects models was not based solely on these statistics. When included studies were judged to be clinically and methodologically homogeneous, and statistical heterogeneity was low (I²≤50%), a fixed-effect model was applied. When substantial clinical or methodological heterogeneity was shown, or if significant statistical heterogeneity was observed (I²>50%), a random-effects model was employed to account for between-study variation (13,14). ORs with 95% CIs were combined to assess the association of NLR with risk of CIP and RP. Subgroup analyses based on tumor type and grade of pneumonitis were performed. Our analysis was conducted by STATA version 17.0 software.

Results

Literature selection

In this study, 902 records were searched from databases and 141 duplicated records were excluded. Eventually, eleven studies were included after reviewing titles, abstracts and full texts of remaining publications (15-25) (Figure 1).

Figure 1 PRISMA flow diagram of this meta-analysis. CNKI, Chinese National Knowledge Infrastructure.

Basic characteristics of included studies

Among included 11 studies, 2,439 cases were enrolled with the sample size ranged from 61 to 788. Two hundred and ninety-eight (12.2%) patients experienced CIP or RP. Most studies focused on NSCLC patients receiving ICIs. All studies were high-quality studies with the NOS scores >5. Specific information was manifested in Table 1.

Association between NLR and risk of mixed pneumonitis (CIP and/or RP) in lung cancer patients receiving concurrent ICIs and radiotherapy

Only one studies explored the predictive role of NLR for pneumonitis among lung cancer patients who received both the ICIs and radiotherapy (18). According to their results, baseline was not related to the development of pneumonitis in this group of patients (OR =0.327, 95% CI: 0.071–1.471, P=0.14).

Association between NLR and risk of CIP in lung cancer patients receiving ICIs

Seven studies identified the predictive role of NLR for CIP (16,17,19-21,23,24). Pooled results indicated that NLR was not significantly associated with development of CIP in lung cancer (OR =1.22, 95% CI: 0.94–1.58, P=0.14) (Figure 2). Subgroup analysis also manifested negative results [NSCLC: OR =1.11, P=0.56; lung cancer: OR =2.71, P=0.29; small cell lung cancer (SCLC): OR =1.12, P=0.12] (Figure S1). However, subgroup analysis by the grade of pneumonitis demonstrated that higher NLR was significantly related to increased risk of grade 3–5 CIP (grade 3–5: OR =7.93, 95% CI: 3.51–17.92, P<0.001, Figure 3A; all grades: OR =1.09, P=0.45, Figure 3B). (Table 2)

Figure 2 Association between neutrophil-to-lymphocyte ratio and risk of checkpoint inhibitors-related pneumonitis in lung cancer patients. CI, confidence interval; OR, odds ratio.

Figure 3 Association between neutrophil-to-lymphocyte ratio and risk of checkpoint inhibitors-related pneumonitis in lung cancer patients. (A) For all grades pneumonitis; (B) for grade 3 or higher pneumonitis. CI, confidence interval; OR, odds ratio.

Association between NLR and risk of RP in lung cancer patients receiving radiotherapy

Three studies explored the relationship of NLR with risk of RP (15,22,25). Pooled results indicated that elevated NLR was related to increased RP risk in NSCLC patients (OR =2.75, 95% CI: 1.75–4.33, P<0.001) (Figure 4). Besides, subgroup analysis based on the grade of pneumonitis shown similar results (all grades: OR =3.10, 95% CI: 1.70–5.67, P<0.001; grade 3–5: OR =2.36, 95% CI: 1.19–4.69, P=0.01) (Figure S2; Table 2).

Figure 4 Association between neutrophil-to-lymphocyte ratio and risk of radiation pneumonitis in non-small cell lung cancer patients. CI, confidence interval; OR, odds ratio.

Discussion

Therefore, according to our findings, higher NLR was associated with increased risk of severe CIP in lung cancer and RP in NSCLC patients. NLR might contribute to the prediction and management of development of CIP and RP in lung cancer patients receiving ICIs and radiotherapy. However, more studies are needed to further verify our results. Importantly, our meta-analyses evaluated CIP and RP separately, and the results should not be interpreted as applying to “pneumonitis” as a single entity. Given the distinct mechanisms and risk factors of CIP versus RP, the predictive value of baseline NLR may differ across these toxicities. This distinction may also partly explain the heterogeneity observed in the CIP analysis.

Our findings suggest that systemic inflammation, as reflected by elevated NLR, may play a pivotal role in the pathogenesis of treatment-related pneumonitis. Neutrophils are known to contribute to inflammatory tissue injury by releasing proteolytic enzymes and reactive oxygen species, while a relative reduction in lymphocytes may reflect impaired immune regulation (26). The imbalance between pro-inflammatory and regulatory immune components could exacerbate lung tissue damage when exposed to immune checkpoint blockade or thoracic radiation (27,28). Our results highlight the potential of NLR as a simple, cost-effective, and easily accessible biomarker for risk stratification prior to initiating ICIs or radiotherapy. Identifying patients at higher risk of pneumonitis could enable closer monitoring, individualized treatment strategies, or preemptive interventions.

Actually, beyond its predictive value for immune-related pneumonitis and RP, NLR also holds significant prognostic value in lung cancer patients undergoing immunotherapy and radiotherapy. Numerous studies have demonstrated that a high baseline NLR is frequently associated with worse OS and PFS (29,30). This correlation may reflect the ability of NLR to serve as a surrogate biomarker for systemic immune and inflammatory status. An elevated NLR typically indicates an enhanced tumor-associated inflammatory response, while a reduced lymphocyte count suggests diminished antitumor immunity—both of which can compromise treatment efficacy. For instance, Diem et al. reported that NSCLC patients treated with PD-1 inhibitors who had a baseline NLR ≥5 exhibited significantly shorter OS and PFS compared to those with a lower NLR (31). Similarly, a systematic review and meta-analysis by Sacdalan et al. confirmed the close association between high NLR and poor survival outcomes in cancer patients receiving immunotherapy, including those with lung cancer (32). In the context of radiotherapy, NLR not only correlates with survival prognosis but may also predict the risk of treatment-related toxicities (33,34). These findings collectively support the broad clinical utility of NLR in the management of lung cancer. Therefore, NLR is not merely a static marker of systemic inflammation but may also serve as a valuable tool in guiding personalized immunotherapeutic or radiotherapeutic strategies.

Currently, there is a limited number of studies specifically focused on the role of the NLR in predicting the risk of CIP and RP in lung cancer patients. Most available evidence is derived from small retrospective cohorts or extrapolated from studies addressing NLR’s general prognostic value. Our study contributes to this emerging field by demonstrating a significant association between baseline NLR and the risk of severe CIP and RP, particularly in NSCLC patients. However, we acknowledge that our analysis only explored baseline NLR, and the dynamic changes in NLR during treatment, as well as the impact of other inflammatory or immune-related markers, remain largely uninvestigated. In fact, several potential research directions could further refine the clinical utility of NLR in this context. For instance, prospective studies incorporating longitudinal monitoring of NLR during the course of immunotherapy and radiotherapy may help capture real-time immune dynamics that precede the onset of pulmonary toxicity. Additionally, integrating NLR with other biomarkers—such as IL-6, C-reactive protein, or T-cell subsets—may improve predictive performance and risk stratification. Furthermore, studies exploring machine learning-based predictive models that incorporate NLR and clinical-radiological features may offer more accurate and individualized risk assessments. Given the potential severity of CIP and RP, and the growing use of immunotherapy and radiotherapy in lung cancer, further well-designed, prospective, and mechanistically oriented studies are urgently needed to validate and expand upon these findings.

There are several limitations in our meta-analysis. First, the number of included studies and patients was relatively small, which may reduce statistical power. Second, substantial between-study heterogeneity was observed, particularly in the CIP analysis (I²=83.9%), likely due to differences in patient populations (e.g., tumor type/stage and baseline lung conditions), treatment characteristics (ICI agents, combination strategies, prior thoracic radiotherapy), outcome definitions and grading of CIP/RP, and the NLR cut-off values and timing of NLR measurement. This heterogeneity may limit the robustness and generalizability of the pooled estimates. Third, most included studies were retrospective, which may introduce selection bias, information bias, and residual confounding despite adjustments in individual studies. Fourth, we were unable to perform more subgroup analyses based on other important parameters such as comorbidities (e.g., emphysema/interstitial lung abnormality), age, and specific ICI drugs due to limited data. Finally, we could not determine an optimal NLR threshold for predicting CIP/RP because of insufficient original data and inconsistent cut-off definitions across studies.

Conclusions

According to our findings, NLR might serve as a predictor for the development of severe CIP in lung cancer and RP in NSCLC. However, more relevant studies are still needed to further clarify the predictive role of NLR for CIP and RP among lung cancer patients due to limitations in this meta-analysis and included studies.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the PRISMA reporting checklist. Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2026-0791/rc

Peer Review File: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2026-0791/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2026-0791/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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