Skip to main content
Download PDF

Neutrophil-to-lymphocyte ratio as a prognostic marker for lung cancer in combined pulmonary fibrosis and emphysema patients

European Journal of Medical Research volume 30, Article number: 316 (2025) Cite this article

Abstract

Background

Combined pulmonary fibrosis and emphysema (CPFE) represents a distinct clinical syndrome characterized by the coexistence of upper lobe emphysema and lower lobe fibrosis, with an increased risk of lung cancer (LC) development. This study aimed to detect the clinical features and prognosis of CPFE patients with LC and the ability of neutrophil-to-lymphocyte ratio (NLR) to predict outcomes in those individuals.

Methods

A retrospective cohort study involving patients diagnosed with CPFE combined with LC between January 2017 and December 2023 was conducted. Clinical characteristics, laboratory parameters and survival data were collected.

Results

A total of 80 CPFE patients with LC were included, with a mean age of 68.1 years, and a male predominance (93.8%). The LCs were predominantly adenocarcinomas (38.8%), with a significant proportion diagnosed at advanced stages (22.5% at stage III, 47.5% at stage IV) and preferential peripheral pulmonary localization (72.5%). CPFE patients with LC had estimated 1-year, 3-year, and 5-year survival rates of 52%, 40%, and 37%, respectively, with a median overall survival of 29.2 months. Multivariate Cox regression analysis revealed that increased NLR [adjusted hazard ratio (HR) 1.180, 95% confidence interval CI 1.029–1.352, p = 0.018] and elevated carcinoembryonic antigen (CEA) (adjusted HR 1.005, 95% CI 1.000–1.010, p = 0.036) were related to an enhanced risk of all-cause mortality. Receiver-operating characteristic analysis identified an NLR cutoff value of 2.6 as a predictor of all-cause death within 24 months [area under the curve = 0.651; specificity = 62.1%; sensitivity = 66.6%; p < 0.05]. Patients with an NLR greater than 2.6 had a significantly greater risk of all-cause death than those with an NLR of 2.6 or less (adjusted HR 2.3, 95% CI 1.197–4.754; p = 0.011).

Conclusions

The NLR may serve as a cost-effective and widely accessible biomarker for risk stratification, particularly in CPFE patients with advanced-stage LC. In our cohort, an NLR cutoff value of 2.6 provides improved prognostic accuracy in predicting mortality outcomes.

Background

Combined pulmonary fibrosis and emphysema (CPFE) is a recently recognized clinic-radiologic syndrome closely associated with heavy tobacco exposure. First described by Cottin in 2005, CPFE is characterized by the presence of upper lobe emphysema and lower lobe fibrosis [1]. In 2022, an official statement formally established the research definition and classification criteria for CPFE as a distinct clinical syndrome [2]. The prevalence of CPFE among patients with idiopathic pulmonary fibrosis (IPF) has been reported to range from 8 to 67%. Current management strategies for CPFE primarily focus on alleviating symptoms and preventing complications, utilizing antifibrotic agents, bronchodilators for emphysema, and supplemental oxygen therapy [3]. Nonetheless, the therapeutic efficacy of these interventions remains limited. The prognosis of CPFE is influenced by three major complications: pulmonary hypertension, acute exacerbations and lung cancer (LC) [4]. Epidemiological data reported a higher prevalence of LC in patients with CPFE, estimated between 2 and 52%, compared to 3%−22% in IPF and 12%−14% in chronic obstructive pulmonary disease (COPD) cohorts [5,6,7]. This variability likely reflects methodological heterogeneity. A follow-up study revealed LC development in 7.14% of CPFE patients [8]. A comparative study from an Asian cohort indicated an LC incidence of 46.8% in CPFE patients [9]. Furthermore, the median survival time for CPFE patients with LC was 19.5 months, underscoring a substantially worse prognosis compared to 53.1 months observed in LC patients without CPFE [10]. This survival disparity is likely attributed to distinct pathobiological interactions among fibrotic, emphysematous, and neoplastic processes.

Inflammation plays a critical role in tumor progression and is strongly related to aggressive cancer behavior and poor clinical outcomes [11]. Chronic inflammation in CPFE promotes fibrosis and emphysema through dysregulated cytokine networks and oxidative stress, creating a pro-tumorigenic microenvironment that is marked by angiogenesis and immune evasion. Complete blood count, widely available and cost-effective, offer several hematological inflammatory indexes such as neutrophil, monocyte, lymphocyte, and platelet counts. These markers reflect systemic inflammatory responses and have been identified as significant predictors of tumor prognosis [12]. Notably, a previous study of 3656 patients indicated that the neutrophil-to-lymphocyte ratio (NLR) may serve as a valuable biomarker for predicting poor prognosis in nonsmall cell lung cancer (NSCLC) patients [13]. Similar associations have been observed in small-cell lung cancer (SCLC), where NLR correlates with patient outcomes [14]. Integrating NLR into LC screening protocols could enhance risk stratification, thereby facilitating the early identification of high-risk CPFE patients who might benefit from intensified surveillance or adjuvant therapies.

The current study retrospectively analyzed the clinical characteristics of 80 patients diagnosed with CPFE combined with LC between January 2017 to December 2023, and evaluated their long-term outcomes. The analysis aimed to elucidate the predictive and prognostic value of the inflammatory biomarker NLR in overall survival (OS).

Methods

Study design

The retrospective observational study was conducted at a single tertiary care center to ensure homogeneity in diagnostic and therapeutic protocols. A total of eighty patients diagnosed with CPFE combined with LC admitted to the First Affiliated Hospital with Nanjing Medical University from January 2017 to December 2023 were enrolled. The inclusion criteria were as follows: (1) cytological or histological diagnosis of LC; (2) CPFE was defined via chest high-resolution computed tomography (CT) patterns showing coexistence of upper lobe predominant emphysema and basal fibrosis of any type; (3) availability of complete patient records. The exclusion criteria were as follows: (1) patients with other malignancies, including those with concurrent nonpulmonary primary cancers or pulmonary metastases of extrapulmonary origin; (2) patients with isolated asthma, severe cardiovascular/cerebrovascular conditions, autoimmune diseases which may take immunosuppressive therapies to have potential confounding effects on inflammatory biomarkers, or other illnesses impacting clinical indicators (Fig. 1).

Fig. 1
figure 1

Flow chart showing patient enrollment in the study. CPFE combined pulmonary fibrosis and emphysema, LC lung cancer

Full size image

Data sources

Baseline clinical characteristics including demographics, clinical or postoperative stage, and hematological results were collected via an electronic medical record system. To ensure data accuracy, two independent researchers (L.J. and M.H.) cross-validated all entries, resolving discrepancies through consensus. Hematological parameters, including whole blood count (WBC), absolute neutrophil count (ANC), absolute lymphocyte count (ALC), C-reactive protein (CRP), carcinoembryonic antigen (CEA), D-dimer, and fibrinogen (Fbg) were obtained at the time of LC diagnosis before the first treatment. The NLR was calculated by dividing the ANC by the ALC measured in peripheral blood.

Clinical follow-up and outcome assessment

All patients were followed up until March 1, 2024 via clinical visits, phone calls or internet interviews to establish the prognosis of the patients. Patients lost to follow-up were censored at the time of their last visit. OS was calculated from the date of LC diagnosis to the date of death or the last recorded follow-up.

Statistical analysis

Normally distributed continuous data are presented as means ± standard deviation (SD). Non-normally distributed continuous data are reported as medians [interquartile range (IQR)]. Categorical variables are reported as numbers (percentage). Survival curves were generated via the Kaplan–Meier method and compared via the log-rank test. A Cox proportional hazard regression model was used to evaluate the potential factors influencing OS, with multivariable analysis adjusted for age, sex and smoking history. To complement the regression analyses, the prognostic value of NLR was also assessed by calculating the area under the curve (AUC) from receiver operating characteristic (ROC) curves for the prediction of mortality within a 24-month period. All statistical analyses were performed using SPSS 26.0 (IBM Corp). A two-sided p value < 0.05 was considered statistically significant.

Results

Clinical characteristics

A total of 80 CPFE patients diagnosed with LC were included in the current study. The baseline characteristics were shown in Table 1. Males accounted for 93.8% (75/80) of the study participants, with a mean age of 68.1 ± 7.6 years. A smoking history was documented in 82.5% of the patients, with a mean tobacco exposure of 46.0 (25.0, 60.0) pack years. The most common pathological types of LC were adenocarcinoma (31/80, 38.8%) and squamous cell carcinoma (29/80, 36.3%). Most tumors combined with CPFE were localized as peripheral cancers (58/80, 72.5%). Fifty-six patients with CPFE were diagnosed at an advanced stage of LC (stage III 18/80, 22.5%, stage IV 38/80, 47.5%). The median NLR, CRP, and CEA levels were 2.8, 18.7 mg/L, and 5.2 ng/mL, respectively. Surgical resection was offered in seventeen (21.3%) patients.

Table 1 Baseline characteristics of CPFE patients with LC and tumor features
Full size table

Long-term survival in CPFE patients with LC

In our cohort of 80 CPFE patients with LC, 43 patients died and 10 were lost to follow up. The obtained median survival time was approximately 29.2 months. The overall survival rates were 52%, 40%, and 37% at the end of the first, third, and fifth years, respectively (Fig. 2).

Fig. 2
figure 2

Kaplan–Meier plot illustrating the survival rate of combined pulmonary fibrosis and emphysema (CPFE) patients diagnosed with lung cancer (LC). The median survival time was 29.2 months. The overall 1-year, 3-year, and 5-year survival rates were 52%, 40%, and 37%, respectively

Full size image

Factors associated with OS in CPFE patients with LC

As shown in Table 2, two baseline parameters were significantly associated with OS [CEA hazard ratio (HR): 1.005, 95% confidence interval CI 1.001–1.009, p = 0.009; NLR HR: 1.148, 95% CI 1.011–1.303, p = 0.033]. For multivariate Cox regression model, age, sex, smoking history, CEA level, and NLR were included for further analysis. The results suggested that increased NLR (adjusted HR 1.180, 95% CI 1.029–1.352, p = 0.018) and elevated CEA (adjusted HR 1.005, 95% CI 1.000–1.010, p = 0.036) were associated with a higher risk of all-cause mortality.

Table 2 Univariate and multivariate Cox hazard analyses of risk factors for survival
Full size table

The ability of NLR to predict mortality among CPFE patients with LC

Utilizing ROC analyses alongside the Youden index, we set a cutoff threshold of 2.6 for NLR, which yielded an AUC of 0.651, as a predictive marker for all-cause mortality within 24-month timeframe (Fig. 3A). This analysis revealed a specificity of 62.1% and a sensitivity of 66.6%, with a positive likelihood ratio of 1.76 and a negative likelihood ratio of 0.54 (p < 0.05). While the NLR cutoff of 2.6 exhibited clinical utility in our cohort, external validation in independent populations, such as multicenter CPFE registries, may be crucial to establish its generalizability.

Fig. 3
figure 3

Predictive value of neutrophil-to-lymphocyte ratio (NLR) for the prognosis of lung cancer (LC) in patients with combined pulmonary fibrosis and emphysema (CPFE). A ROC curves revealing the optimal threshold of NLR for predicting mortality within a 24-month period. An NLR of 2.6 as the optimal cutoff value. AUC represented area under cure. B Kaplan–Meier plot illustrated the survival rate in CPFE patients diagnosed with LC based on initial NLR levels. The median survival time of low NLR group was 106.0 months with the overall 1-year, 3-year, and 5-year survival rates were 67%, 54%, and 54%, respectively. The median survival time of high NLR group was 18.0 months with the overall 1-year, 3-year, and 5-year survival rates were 37%, 26%, and 26%, respectively

Full size image

The survival analysis revealed a substantial correlation between the NLR cutoff value and OS (Fig. 3B). Specifically, individuals with an NLR exceeding 2.6 were found to have a 2.3-fold increased likelihood of mortality (95% CI: 1.197–4.754, p = 0.011) in comparison with those whose NLR was 2.6 or lower. Notably, patients with an NLR greater than 2.6 experienced diminished overall survival rates at the 1-year, 3-year, and 5-year points (37%, 26%, and 26%, respectively), with a median survival duration of approximately 18.0 months. In contrast, patients with an NLR of 2.6 or less had a significantly better prognosis, as evidenced by their overall survival rates at these time points being markedly higher (67%, 54%, and 54%, respectively), along with an increased median survival time of approximately 106.0 months.

Discussion

This study investigated the clinical features of CPFE patients with LC and their long-term prognosis. Our results found that CPFE patients with lung carcinoma were predominantly elderly males with a heavy smoking history. The tumors were primarily lung adenocarcinomas and located mainly in the peripheral regions of the lungs. Most patients were diagnosed at an advanced stage of the disease. CPFE patients with LC had an estimated 5-year survival rate of 37% with a median OS of 29.2 months. Additionally, NLR may have prognosis value for CPFE patients with LC. The NLR cutoff value of 2.6 could enhance the prediction of mortality.

CPFE is a relatively newly defined syndrome that is strongly associated with current or former smoking, given that emphysema and lung fibrosis are both tobacco-related diseases. The"triple hit"of smoking, emphysema, and pulmonary fibrosis may be among the leading causes for the high incidence of pulmonary carcinomas in CPFE patients, compared with those with COPD or IPF alone [15]. The distribution of histopathological subtypes of LC in CPFE patients varies across studies. Our findings identified adenocarcinoma as the predominant subtype, which aligns with several previous reports [16, 17]. However, Kitaguch et al. [9] and Fujiwara et al. [18], in two Japanese cohorts, reported that squamous cell carcinoma was the predominant subtype in CPFE patients, based on relatively small sample sizes of 22 and 36 cases, respectively. There is a possibility that the characteristics of LC in Japan might differ from other countries [19], as well as potential selection bias due to limited sample sizes. Additionally, a study by Girard et al. [20], which analyzed a cohort of 47 CPFE patients with LC in France and Belgium, reported that squamous cell carcinoma accounted for 36% of cases, followed by adenocarcinoma at 30%. The reason for this discrepancy may be influenced by racial and the increasing prevalence of adenocarcinoma in LC over recent years.

Emerging epidemiological evidence highlights significant differences in LC susceptibility among distinct chronic pulmonary diseases. A heightened prevalence of cancer has been observed in large epidemiological cohorts of patients with lung fibrosis, ranging from 4.4% to 4.9% in cases reported in the United Kingdom [21]. The incidence of LC appears to be approximately 1% per year in patients with COPD [22]. Notably, in a large cohort involving 230 CPFE cases, malignant tumors were diagnosed in 11.6% of their patients [23]. Furthermore, the prognosis of patients with CPFE is profoundly affected by LC, often leading to worsened outcomes. According to a meta-analysis, LC patients with a non-CPFE phenotype or a normal lung had 1-year, 3-year, and 5-year survival rates of 93.1%, 68.5%, and 44.0%, respectively, with a median OS of 53.1 months [10]. When compared with LC patients with emphysema or fibrosis alone, CPFE combined with LC patients had a higher mortality risk. Previous studies reported a 1-year mortality rate of 55% in COPD with LC patients [24] and a 5-year mortality rate of 85.65% in IPF with LC patients [25]. The poor prognosis in CPFE patients may be due to diagnostic challenges in early tumor detection. Malignant lesions in CPFE often occur near areas of dense fibrosis with architectural distortion [26]. Although low-dose CT screening has proven effective for LC detection in high-risk populations, its utility diminishes in CPFE patients due to this characteristic anatomical camouflage. Emerging biomarker-based approaches hold promise for enhancing diagnostic accuracy. The recent research showed that longitudinal monitoring of circulating tumor DNA (ctDNA) might be useful to discriminate malignant nodules in radiologically ambiguous cases, thereby reducing diagnostic delays [27]. These strategies merit further investigation in CPFE patient cohorts, particularly by combining NLR profiling with ctDNA panels, to improve diagnostic precision.

Over the past few decades, numerous laboratory parameters, such as hemoglobin levels, leukocyte counts, and CRP levels, have been associated with prognosis in malignant tumors [28,29,30]. However, studies focusing on CPFE patients complicated by LC remain limited. It is widely recognized that patients with CPFE show elevated levels of serum inflammatory biomarkers, which is further exacerbated by the presence of cancer [31]. Systemic inflammation plays a critical role in cancer progression and prognosis. NLR, as a hematological inflammatory index, is easily derived from routine hematological parameters. The association between elevated NLR and mortality may reflect neutrophilia-driven pro-tumorigenic inflammation and lymphopenia-induced immune exhaustion. Elevated NLR indicates an increased neutrophil-driven pro-inflammatory response promoting tumor progression, angiogenesis, and immune suppression, while lymphopenia signifies weakened adaptive immunity and reduced antitumor defenses [32, 33]. Prior studies have shown that an elevated pretreatment NLR is associated with shorter OS and progression-free survival, as well as lower response rates, in patients with NSCLC treated with nivolumab [34]. In patients with extensive-stage SCLC, the NLR may also serve as a good prognostic marker [35]. Our results identified NLR as a potential prognostic marker in CPFE patients with LC. ROC analysis determined 2.6 as the optimal mortality prediction threshold for NLR, however, it exhibited discriminative capacity, relatively low sensitivity and specificity, and broad confidence intervals. These findings suggest that while NLR may serve as a prognostic marker, its predictive accuracy should be interpreted with caution. Previously, Ueno et al. found no significant prognostic value of NLR in their cohort of 59 CPFE patients, of whom 79.7% were early-stage (I–II) and only 20.3% were advanced-stage (III–IV) [36]. This discrepancy likely caused by differences in patient stage distribution, as our cohort predominantly comprised advanced-stage cases. Moreover, emerging evidence links high NLR levels with increased tumor burden in LC [37,38,39]. In early-stage LC, NLR may primarily indicate the underlying inflammatory state characteristic of CPFE itself rather than tumor burden, thereby limiting its prognostic utility in that setting. While NLR emerged as a robust prognostic marker, comparative analyses with other inflammatory indices revealed divergent predictive utility. In our cohort, CRP showed weak association with OS compared to NLR. This aligns with prior evidence suggesting that NLR integrates both neutrophilic inflammation and lymphopenic immune dysfunction, whereas CRP primarily reflects acute-phase responses [40]. In addition to NLR, emerging composite indices are reshaping prognostic evaluation in LC. The recent studies identified platelet-to-lymphocyte ratio (PLR), immune-inflammatory index (SII) and lymphocyte-albumin–neutrophil ratio (LANR) provide predictive information on survival and disease course in NSCLC [41, 42]. Future studies should synergize inflammatory, nutritional, and immune parameters to evaluate composite scores to optimize prognostic stratification.

Our findings showed that the prognostic utility of NLR in CPFE-LC may have certain limitations, showing significant predictive value specifically in male patients with advanced-stage disease, which may restrict the generalizability of the findings to general populations. One possible explanation is the small proportion of female patients in our cohort, which could have reduced the power to detect significant associations in the subgroup. The variations in inflammatory and immune responses across different tumor stages and between genders may influence the predictive utility of NLR. This limitation suggest that future research is necessary to validate NLR utility across a more diverse patient population, including females and those with early-stage disease. Although our study identified NLR as a significant predictor of mortality in CPFE patients with LC, potential confounding factors in NLR interpretation should be acknowledged. Acute infections, corticosteroid use, and concurrent inflammatory conditions, such as exacerbations of fibrosis or emphysema, may transiently elevate NLR, potentially distorting its prognostic value. Furthermore, comorbidities like heart failure and other cardiovascular diseases, are known to impact NLR levels, underscoring the need to consider these factors in future prognostic evaluations. In addition, treatments such as chemotherapy or immunotherapy could modulate neutrophil and lymphocyte counts, indirectly affecting NLR. To address this, future studies should stratify NLR measurements by clinical context and adjust for treatment regimens in multivariable models. Moreover, as a single-center, retrospective analysis, it limits the ability to establish causal relationships, and presents potential biases related to patient selection and data accuracy. To mitigate these biases, we recommend prospective, multicenter studies with balanced demographic representation. Additionally, integrating standardized protocols for CPFE diagnosis and NLR measurement across centers would enhance reproducibility.

Conclusions

CPFE significantly elevates the risk of lung cancer development, particularly in elderly males with substantial tobacco exposure. Elevated NLR levels may indicate heightened mortality risk in LC combine with CPFE, particularly in advanced-stage patients, with a cutoff value of 2.6 showing improved predictive accuracy. Specifically, patients with an NLR greater than 2.6 had a 2.3-fold increased risk of all-cause death compared with those with an NLR of 2.6 or less. Although implementing NLR thresholds in clinical algorithms could facilitate patient management, these findings require validation through multicenter prospective cohorts encompassing diverse ethnicities and disease stages.

Data availability

The datasets used and analyzed in the current study are available from the corresponding author upon reasonable request.

Abbreviations

ANC:

Absolute neutrophil count

ALC:

Absolute lymphocyte count

AUC:

Area under the curve

CEA:

Carcinoembryonic antigen

COPD:

Chronic obstructive pulmonary disease

CPFE:

Combined pulmonary fibrosis and emphysema

CRP:

C-reactive protein

Fbg:

Fibrinogen

IPF:

Idiopathic pulmonary fibrosis

LC:

Lung cancer

NLR:

Neutrophil-to-lymphocyte ratio

NSCLC:

Nonsmall cell lung cancer

OS:

Overall survival

ROC:

Receiver operating characteristic

SCLC:

Small-cell lung cancer

WBC:

Whole blood count

References

  1. Cottin V, Nunes H, Brillet PY, Delaval P, Devouassoux G, Tillie-Leblond I, et al. Combined pulmonary fibrosis and emphysema: a distinct underrecognised entity. Eur Respir J. 2005;26(4):586–93.

    Article  CAS  PubMed  Google Scholar 

  2. Cottin V, Selman M, Inoue Y, Wong AW, Corte TJ, Flaherty KR, et al. Syndrome of combined pulmonary fibrosis and emphysema: an official ATS/ERS/JRS/ALAT research statement. Am J Respir Crit Care Med. 2022;206(4):e7–41.

    Article  PubMed  Google Scholar 

  3. Caceres JD, Venkata A. Combined pulmonary fibrosis and emphysema. Curr Opin Pulm Med. 2024;30(2):167–73.

    Article  CAS  PubMed  Google Scholar 

  4. Hage R, Gautschi F, Steinack C, Schuurmans MM. Combined pulmonary fibrosis and emphysema (CPFE) clinical features and management. Int J Chron Obstruct Pulmon Dis. 2021;16:167–77.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Oh JY, Lee YS, Min KH, Hur GY, Lee SY, Kang KH, et al. Impact and prognosis of lung cancer in patients with combined pulmonary fibrosis and emphysema. Sarcoidosis Vasc Diffuse Lung Dis. 2020;37(4): e2020020.

    PubMed  PubMed Central  Google Scholar 

  6. Qi C, Sun SW, Xiong XZ. From COPD to lung cancer: mechanisms linking, diagnosis, treatment, and prognosis. Int J Chron Obstruct Pulmon Dis. 2022;17:2603–21.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Tzouvelekis A, Gomatou G, Bouros E, Trigidou R, Tzilas V, Bouros D. Common pathogenic mechanisms between idiopathic pulmonary fibrosis and lung cancer. Chest. 2019;156(2):383–91.

    Article  PubMed  Google Scholar 

  8. Chae KJ, Jin GY, Han YM, Kim YS, Chon SB, Lee YS, et al. Prevalence and progression of combined pulmonary fibrosis and emphysema in asymptomatic smokers: a case-control study. Eur Radiol. 2015;25(8):2326–34.

    Article  PubMed  Google Scholar 

  9. Kitaguchi Y, Fujimoto K, Hanaoka M, Kawakami S, Honda T, Kubo K. Clinical characteristics of combined pulmonary fibrosis and emphysema. Respirology. 2010;15(2):265–71.

    Article  PubMed  Google Scholar 

  10. Koo HJ, Do KH, Lee JB, Alblushi S, Lee SM. Lung cancer in combined pulmonary fibrosis and emphysema: a systematic review and meta-analysis. PLoS ONE. 2016;11(9): e0161437.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Mantovani A, Allavena P, Sica A, Balkwill F. Cancer-related inflammation. Nature. 2008;454(7203):436–44.

    Article  CAS  PubMed  Google Scholar 

  12. Zhang T, Liu W, Xu C. Correlation analysis of hemoglobin, albumin, lymphocyte, platelet score and platelet to albumin ratio and prognosis in patients with lung adenosquamous carcinoma. Front Oncol. 2023;13:1166802.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Gu XB, Tian T, Tian XJ, Zhang XJ. Prognostic significance of neutrophil-to-lymphocyte ratio in non-small cell lung cancer: a meta-analysis. Sci Rep. 2015;5:12493.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Chen C, Yang H, Cai D, Xiang L, Fang W, Wang R. Preoperative peripheral blood neutrophil-to-lymphocyte ratios (NLR) and platelet-to-lymphocyte ratio (PLR) related nomograms predict the survival of patients with limited-stage small-cell lung cancer. Transl Lung Cancer Res. 2021;10(2):866–77.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Chen Q, Liu P, Zhou H, Kong H, Xie W. An increased risk of lung cancer in combined pulmonary fibrosis and emphysema patients with usual interstitial pneumonia compared with patients with idiopathic pulmonary fibrosis alone: a systematic review and meta-analysis. Ther Adv Respir Dis. 2021;15:17534666211017050.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Usui K, Tanai C, Tanaka Y, Noda H, Ishihara T. The prevalence of pulmonary fibrosis combined with emphysema in patients with lung cancer. Respirology. 2011;16(2):326–31.

    Article  PubMed  Google Scholar 

  17. Kumagai S, Marumo S, Yamanashi K, Tokuno J, Ueda Y, Shoji T, et al. Prognostic significance of combined pulmonary fibrosis and emphysema in patients with resected non-small-cell lung cancer: a retrospective cohort study. Eur J Cardiothorac Surg. 2014;46(6):e113–9.

    Article  PubMed  Google Scholar 

  18. Fujiwara A, Tsushima K, Sugiyama S, Yamaguchi K, Soeda S, Togashi Y, et al. Histological types and localizations of lung cancers in patients with combined pulmonary fibrosis and emphysema. Thorac Cancer. 2013;4(4):354–60.

    Article  PubMed  Google Scholar 

  19. Tanaka I, Matsubara O, Kasuga T, Takemura T, Inoue M. Increasing incidence and changing histopathology of primary lung cancer in Japan. A review of 282 autopsied cases. Cancer. 1988;62(5):1035–9.

    Article  CAS  PubMed  Google Scholar 

  20. Girard N, Marchand-Adam S, Naccache JM, Borie R, Urban T, Jouneau S, et al. Lung cancer in combined pulmonary fibrosis and emphysema: a series of 47 Western patients. J Thorac Oncol. 2014;9(8):1162–70.

    Article  PubMed  Google Scholar 

  21. Le Jeune I, Gribbin J, West J, Smith C, Cullinan P, Hubbard R. The incidence of cancer in patients with idiopathic pulmonary fibrosis and sarcoidosis in the UK. Respir Med. 2007;101(12):2534–40.

    Article  PubMed  Google Scholar 

  22. Sekine Y, Katsura H, Koh E, Hiroshima K, Fujisawa T. Early detection of COPD is important for lung cancer surveillance. Eur Respir J. 2012;39(5):1230–40.

    Article  PubMed  Google Scholar 

  23. Nasim F, Moua T. Lung cancer in combined pulmonary fibrosis and emphysema: a large retrospective cohort analysis. ERJ Open Res. 2020. https://doiorg.publicaciones.saludcastillayleon.es/10.1183/23120541.00521-2020.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Petta V, Loukides S, Kostikas K, Papaioannou AI, Papatheodorou G, Cholidou K, et al. Serum osteopontin in patients with lung cancer and chronic obstructive pulmonary disease: does the co-existence make the difference? J Thorac Dis. 2018;10(2):740–8.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Kim HC, Lee S, Song JW. Impact of idiopathic pulmonary fibrosis on clinical outcomes of lung cancer patients. Sci Rep. 2021;11(1):8312.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Inomata M, Ikushima S, Awano N, Kondoh K, Satake K, Masuo M, et al. An autopsy study of combined pulmonary fibrosis and emphysema: correlations among clinical, radiological, and pathological features. BMC Pulm Med. 2014;14:104.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Phallen J, Sausen M, Adleff V, Leal A, Hruban C, White J, et al. Direct detection of early-stage cancers using circulating tumor DNA. Sci Transl Med. 2017. https://doiorg.publicaciones.saludcastillayleon.es/10.1126/scitranslmed.aan2415.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Dong P, Li W, Deng J, Huang L, Liu B, Wang S, et al. Relationship between hemoglobin and lung cancer: evidence from Mendelian randomization and National Health and Nutrition Examination Survey. Clin Transl Oncol. 2024;26(3):623–9.

    Article  CAS  PubMed  Google Scholar 

  29. Tibaldi C, Vasile E, Bernardini I, Orlandini C, Andreuccetti M, Falcone A. Baseline elevated leukocyte count in peripheral blood is associated with poor survival in patients with advanced non-small cell lung cancer: a prognostic model. J Cancer Res Clin Oncol. 2008;134(10):1143–9.

    Article  CAS  PubMed  Google Scholar 

  30. Zhu M, Ma Z, Zhang X, Hang D, Yin R, Feng J, et al. C-reactive protein and cancer risk: a pan-cancer study of prospective cohort and Mendelian randomization analysis. BMC Med. 2022;20(1):301.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Cornwell WD, Kim C, Lastra AC, Dass C, Bolla S, Wang H, et al. Inflammatory signature in lung tissues in patients with combined pulmonary fibrosis and emphysema. Biomarkers. 2019;24(3):232–9.

    Article  CAS  PubMed  Google Scholar 

  32. Mosca M, Nigro MC, Pagani R, De Giglio A, Di Federico A. Neutrophil-to-lymphocyte ratio (NLR) in NSCLC, gastrointestinal, and other solid tumors: immunotherapy and beyond. Biomolecules. 2023. https://doiorg.publicaciones.saludcastillayleon.es/10.3390/biom13121803.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Song M, Graubard BI, Loftfield E, Rabkin CS, Engels EA. White blood cell count, neutrophil-to-lymphocyte ratio, and incident cancer in the UK Biobank. Cancer Epidemiol Biomarkers Prev. 2024;33(6):821–9.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Liu J, Li S, Zhang S, Liu Y, Ma L, Zhu J, et al. Systemic immune-inflammation index, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio can predict clinical outcomes in patients with metastatic non-small-cell lung cancer treated with nivolumab. J Clin Lab Anal. 2019;33(8): e22964.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Drpa G, Sutic M, Baranasic J, Jakopovic M, Samarzija M, Kukulj S, et al. Neutrophil-to-lymphocyte ratio can predict outcome in extensive-stage small cell lung cancer. Radiol Oncol. 2020;54(4):437–46.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Ueno F, Kitaguchi Y, Shiina T, Asaka S, Miura K, Yasuo M, et al. The preoperative composite physiologic index may predict mortality in lung cancer patients with combined pulmonary fibrosis and emphysema. Respiration. 2017;94(2):198–206.

    Article  CAS  PubMed  Google Scholar 

  37. Bar-Ad V, Palmer J, Li L, Lai Y, Lu B, Myers RE, et al. Neutrophil to lymphocyte ratio associated with prognosis of lung cancer. Clin Transl Oncol. 2017;19(6):711–7.

    Article  CAS  PubMed  Google Scholar 

  38. Mi HL, Wei WL, Zhang DH, Liang HY, Yue CF, Xu JN. Neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, and prognostic nutritional index as prognostic markers for lung carcinoma. Br J Hosp Med (Lond). 2024;85(10):1–13.

    Article  PubMed  Google Scholar 

  39. Ma A, Wang G, Du Y, Guo W, Guo J, Hu Y, et al. The clinical relevance of neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio in chronic obstructive pulmonary disease with lung cancer. Front Oncol. 2022;12: 902955.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Alparslan Bekir S, Sonkaya E, Ozbaki F, Aydogan Eroglu S, Sertcelik L, Duman D, et al. The utility of neutrophil-to-lymphocyte ratio determined at initial diagnosis in predicting disease stage and discriminating between active and stable disease in patients with sarcoidosis: a cross-sectional study. Postgrad Med. 2022;134(6):603–8.

    Article  CAS  PubMed  Google Scholar 

  41. Erciyestepe M, Selvi O, Dinc Sonusen S, Ozturk AE, Dinc G, Gunes TK, et al. Prognostic value of inflammation and nutrition-based scores in non-small cell lung cancer. Med Princ Pract. 2024;33(2):122–32.

    Article  PubMed  Google Scholar 

  42. Xu Y, Zhang L, Chen Z, Sun X, Zhao M, Wu Q, et al. The diagnostic value of systemic immune-inflammatory index (SII) and lymphocyte-albumin-neutrophil ratio (LANR) in chronic obstructive pulmonary disease with lung cancer. J Inflamm Res. 2024;17:5555–65.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank Hai Li, PhD and Shuying Ma, MMeD (Department of Pathology, the First Affiliated Hospital with Nanjing Medical University) for their expert assistance in pathological data extraction and analysis.

Funding

This work was funded by the Key Project of National Science & Technology for Infectious Diseases of China (2018ZX10722301), and the Jiangsu Province Capability Improvement Project through Science, Technology and Education; Jiangsu Provincial Medical Innovation Center (CXZX202206), and the Young Scholars Fostering Fund of the First Affiliated Hospital of Nanjing Medical University (No. PY2022012).

Author information

Author notes

  1. Linling Jin, Shulan Zhou and Lei Huang have contributed equally to the work.

Authors and Affiliations

  1. Department of Pulmonary and Critical Care Medicine, the First Affiliated Hospital With Nanjing Medical University, 300 Guangzhou Road, Nanjing, 210029, Jiangsu, China

    Linling Jin, Lei Huang, Yiting He, Jiayi Zhang, Hui Kong, Weiping Xie & Mengyu He

  2. Department of Respiratory and Critical Care Medicine, the Second Affiliated Hospital of Soochow University, Suzhou, 215004, Jiangsu, China

    Shulan Zhou

  3. Department of Pulmonary and Critical Care Medicine, the First People’s Hospital of Kunshan, Suzhou, 215300, Jiangsu, China

    Ling Chen

Authors
  1. Linling Jin
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Shulan Zhou
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Lei Huang
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Yiting He
    View author publications

    You can also search for this author inPubMed Google Scholar

  5. Jiayi Zhang
    View author publications

    You can also search for this author inPubMed Google Scholar

  6. Ling Chen
    View author publications

    You can also search for this author inPubMed Google Scholar

  7. Hui Kong
    View author publications

    You can also search for this author inPubMed Google Scholar

  8. Weiping Xie
    View author publications

    You can also search for this author inPubMed Google Scholar

  9. Mengyu He
    View author publications

    You can also search for this author inPubMed Google Scholar

Contributions

JLL, KH, XWP, and HMY, study concepts/study design; JLL, ZSL, HL, HYT, ZJY, and CL, data extraction; JLL, ZSL, HYT, and HMY, data analysis/interpretation; JLL, ZSL, and HL, literature research; manuscript drafting or manuscript revision for important intellectual content, all authors; approval of final version of submitted manuscript, all authors; agrees to ensure any questions related to the work are appropriately resolved, all authors.

Corresponding authors

Correspondence to Weiping Xie or Mengyu He.

Ethics declarations

Ethics approval and consent to participate

This study was approved by the ethics committee of the First Affiliated Hospital with Nanjing Medical University (2024-SR-877), which waived the requirement for informed consent due to the retrospective study design.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jin, L., Zhou, S., Huang, L. et al. Neutrophil-to-lymphocyte ratio as a prognostic marker for lung cancer in combined pulmonary fibrosis and emphysema patients. Eur J Med Res 30, 316 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s40001-025-02595-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s40001-025-02595-3

Keywords

European Journal of Medical Research

ISSN: 2047-783X

Contact us