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Year : 2020  |  Volume : 16  |  Issue : 4  |  Page : 731-736

Prognostic values of various hematological variables as markers of systemic inflammation in metastatic lung cancer

Department of Internal Medicine, Namik Kemal University Hospital, Tekirdag, Turkey

Date of Submission10-May-2017
Date of Decision19-Aug-2017
Date of Acceptance25-Feb-2018
Date of Web Publication27-Apr-2018

Correspondence Address:
Selcuk Seber
Department of Internal Medicine, Namik Kemal University Hospital, Suleymanpasa, Tekirdag 59030
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/jcrt.JCRT_397_17

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 > Abstract 

Background: Chronic state of inflammation is an important factor in advanced cancer which is used by tumor cells for maintaining survival and growth. Hematological parameters such as neutrophil/lymphocyte ratio (NLR), thrombocyte/lymphocyte ratio (TLR), and lymphocyte/monocyte ratio (LMR) are reliable indicators of systemic inflammation. We aimed to elucidate the effect of hematological parameters and clinical features of patients on the prognosis of advanced-stage non-small cell lung cancer (NSCLC).
Methods: We included 102 Stage IV NSCLC patients who presented to the oncology clinic between 2010 and 2016. Pretreatment clinical parameters and NLR, TLR, and LMR were retrieved from the medical records. The cutoff values, calculated with receiver operating curve analysis, for NLR, LMR, and TLR were 2.5, 3, and 183, respectively. All patients were divided into two groups according to cutoff values and analyzed accordingly.
Results: Median overall survival and progression-free survival were 10 and 6 months, respectively. In univariate analysis, high NLR, high TLR, and low LMR were found to be significantly associated with survival. Among clinical parameters having eastern cooperative oncology group performance score 0–1, older age (≥70 years) single metastatic disease was prognostic. In multivariate Cox regression analysis, only the number of metastatic lesions and LMR were found to be independent predictors for survival.
Conclusion: Among hematological parameters, only LMR was found to be an independent predictor of survival in patients with advanced-stage NSCLC.

Keywords: Advanced stage, lymphocyte-monocyte ratio, non-small cell lung cancer

How to cite this article:
Bayir D, Seber S, Yetisyigit T. Prognostic values of various hematological variables as markers of systemic inflammation in metastatic lung cancer. J Can Res Ther 2020;16:731-6

How to cite this URL:
Bayir D, Seber S, Yetisyigit T. Prognostic values of various hematological variables as markers of systemic inflammation in metastatic lung cancer. J Can Res Ther [serial online] 2020 [cited 2020 Sep 26];16:731-6. Available from: http://www.cancerjournal.net/text.asp?2020/16/4/731/231452

 > Introduction Top

Lung cancer is the leading cause of death associated with solid malignancies.[1] Nearly 80% of all lung cancer cases are of non-small cell type and more than two-thirds of patients present at an advanced stage of the disease.[2],[3]

The relation between inflammation and cancer was first described by Rudolf Virchow in 1863. He used the term “lymphoreticular infiltrate” for the presence of leukocytes localized near tumor tissue. Many other studies have identified the host inflammatory response against the cancer as a key factor in the course of malignant disease.[4],[5] Macrophages, thrombocytes, and lymphocytes act in an interactive manner in the tumor microenvironment as key counterparts of the inflammatory and immune response between the tumor and the host.[6]

We aimed to elucidate the prognostic values of various hematological parameters in patients with advanced-stage non-small cell lung cancer (NSCLC).

 > Methods Top

The study was conducted according to Helsinki Declaration rules. The local Ethical Committee of the Namik Kemal University Hospital approved the study. A total of 304 patients with the diagnosis of lung cancer who presented to the oncology department between 2010 and 2016 were scanned for the suitability to be included in the study. A total of 102 metastatic NSCLC patients with no prior surgical resection of lung cancer disease, and who have not received prior chemotherapy, were included in the study group. Relevant clinical ve demographic parameters of the study subjects were obtained from electronic medical records of the oncology clinic. Patients with a performance score of three or greater and those who were ineligible for chemotherapy treatment were not included in the study group. Clinical, pathological, and laboratory data were retrieved from the medical records of the patients retrospectively. Hematological parameters were calculated from blood counts routinely taken 1–2 days before the start of the first cycle of the first-line chemotherapy. Staging was done according to the seventh edition of tumor, node, and metastasis (TNM) classification. Neutrophil/lymphocyte ratio (NLR), thrombocyte/-lymphocyte ratio (TLR), and lymphocyte/monocyte ratio (LMR) were determined by division of the neutrophil count by lymphocyte count, thrombocyte count by lymphocyte count, and lymphocyte count by monocyte count, respectively.

Statistical analysis

All statistical analysis was done using IBM Statistical Package fort he Social Sciences 22.0 Program (SPSS INC., Chicago, IL). Continuous variables were mean and standard deviation; categorical variables were represented as percentages. Normal distribution was analyzed with Kolmogorov–Smirnov test. If the variable distribution was normal, ANOVA and t-test were used for comparison of variables. If normal distribution was not present, Kruskal–Wallis and Mann–Whitney U-tests were used accordingly. Categorical variables were analyzed with Chi-square test. Correlations were compared by Pearson analysis if there was normal distribution and by Spearman if normal distribution was not achieved. The optimal cutoff values for hematological parameters were determined using receiver operating curve (ROC) analysis. Overall survival (OS) was defined as time between diagnosis and death. Progression-free survival (PFS) was defined as time between diagnosis and disease progression or the time when last record of the patient was taken or lost to follow-up. In survival analysis, Kaplan–Meier method was used, and survival duration of groups was compared with log-rank analysis. A two-tailed P ≤ 0.05 was accepted as statistically signifıcant. The post hoc power of LMR for survival was found as 0.84 and alpha as 0.05 by e-picos online calculator program.

 > Results Top

A total of 102 patients entered into the study group. The clinical and histopathological features of the study group are summarized in [Table 1]. All of the patients had Stage IV disease by TNM 7 classification at the time of diagnosis, and all of the patients received platinum-based doublet chemotherapy as the first-line treatment.
Table 1: Baseline patient characteristics

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The median follow-up time was 26 months (1–66 months). At the end of the follow-up, 85 (83.3%) patients had died. The response rate of patients with the first-line chemotherapy was 51%. Median OS was 10 months (95% confidence interval [CI] 14,48–9,52). During the follow-up period, median PFS was found to be 6 months (95% CI 9,78–6,21). The correlations between clinicopathological parameters and survival are summarized in [Table 2].
Table 2: Univariate survival analysis of clinicopathological parameters in advanced-stage lung cancer patients

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NLR, LMR, and TLR were determined from the blood counts taken 1–2 days before the start of the chemotherapy [Table 3]. The optimal cutoff values determined by ROC analysis for NLR, LMR, and TLR were 2.5, 3, and 183, respectively [Figure 1].
Table 3: Hematological parameters at diagnosis

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Figure 1: Receiver operating characteristics curves for (a) neutrophil lymphocyte ratio, (b) lymphocyte monocyte ratio, and (c) thrombocyte lymphocyte ratio

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Univariate analysis to determine the possible prognostic factors for OS and PFS revealed older age, having multiple metastatic disease, performance score, NLR, TLR, and LMR as possible candidates for multivariate analysis [Table 4]. Kaplan–Meier curve analysis by log-rank test have showed that NLR ≥2,5 (P 0.002), TLR >183 (P < 0.001), and LMR <3 (P < 0.001) were significantly associated with decreased OS and PFS for advanced-stage NSCLC patients [Figure 2].
Table 4: Univariate survival analysis of hematological parameters based on receiver operating curve analysis

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Figure 2: (1) Kaplan-Meier curves for (a) overall survival(OS) (P < 0.001), (b) progression free survival (PSF) (P < 0.001) comparing patients with LMR>3 to LMR≤3. (2) Kaplan-Meier curves for (a) overall survival(OS) (P < 0.002), (b) progression free survival (PSF) (P < 0.002) comparing patients with NLR>2.5 to NLR≤2.5. (3) Kaplan-Meier curves for (a) overall survival(OS) (P < 0.001), (b) progression free survival (PSF) (P < 0.001) comparing patients with TLR>183 to TLR≤183

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Multivariate analysis for determination of independent prognostic factors for OS identified LMR and multiple metastatic disease state as significant prognostic factors for OS [Table 5]. The odds ratio of LMR and multiple metastatic disease was 1.510 (95% CI 0.672–3.881) and 4.96 (95% CI 1.275–19.364) for OS, respectively.
Table 5: Multivariate analysis with logistic regression analysis of effective parameters on overall survival

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 > Discussion Top

In our study, we aimed to assess the effect of various hematological parameters prognostic features in patients with metastatic NSCLC.

The relation between inflammatory parameters and prognosis of solid tumor diseases has been a research interest in recent years. However, studies evaluating the inflammatory parameters of NLR, TLR, and LMR in a single study, exclusively including advanced-stage NSCLC patients, are rather limited.

In a meta-analysis of 14 studies including 2734 lung cancer patients, the cutoff values of NLR have been reported to be ranging between 2.5 and 5 and high NLR levels have been found to be correlated with poor prognosis in NSCLC and small cell lung cancer.[7] In this meta-analysis, there was a single study which included only advanced-stage NSCLC patients.[8] In this study which included 171 Stage IV NSCLC patients, NLR ≥5 was found to be associated with worse prognosis and in patients where NLR ratios normalized after giving one cycle of chemotherapy OS was found to be longer. The cutoff value ≥5 was taken as a standard value based on the findings of previous studies; however, we think that this assumption may lower the sensitivity of this parameter. Our cutoff value for NLR was found to be 2.5 by ROC analysis, and we believe that until large studies with more homogenous populations are reported, NLR cutoff values should be based on its own study population rather than standard values.

Similar to NLR, TLR also seems to be affected by the systemic inflammatory process undergoing in the setting of metastatic disease. High platelet counts are thought to be as a result of direct stimulation of proinflammatory cytokines such as interleukin (IL)-6 which are also responsible for decreased peripheral lymphocyte counts.[9]

In a similar study to ours which also included Stage III and Stage IV patients, Liu et al. found the optimal cutoff value for TLR as >152 (it was 182 in our study) and reported that high TLR was associated with decreased survival.[10] However, in this study, other hematological parameters such as LMR were not assessed. Although we also found an association with high TLR and decreased OS, this association lost its significance in the multivariate analysis.

On the contrary, the role of LMR as a prognostic factor reported in various studies from the literature seems to be more valuable. Our cutoff value for LMR, which is >3, is also very similar to those values reported in the literature, which provides further evidence for accepting this parameter as a more reliable indicator for further studies. In addition, high LMR ratio was the only hematologic parameter in our study to be independently associated with increased survival (P < 0.049).

In a meta-analysis by Teng et al. which included 18 studies involving more than 8000 patients diagnosed with various cancer types, the cutoff value for LMR by ROC analysis was reported to be between 2.14 and 5.22. In subgroup analysis, high LMR was found to be correlated with good prognosis in patients with lung, nasopharynx, gastrointestinal, and urinary system malignancies.[11]

In a study by Chen et al.[12] involving advanced stage NSCLC patients, the cutoff value for LMR was reported to be 3.29 and high LMR was found to be associated with better eastern cooperative oncology group performance status and decreased incidence of distant metastatic disease.

The underlying causes of the association between lower LMR and poor prognosis remain elusive. LMR can be a thought as a reflection of the struggle between the immune reaction of the host against the tumor, represented by lymphocytes and the inflammatory reaction arising from the interaction of various factors present in the tumor microenvironment represented by the monocytes. Tumor-associated macrophages are shown to be proangiogenic and associated with tumor invasion, suppression of host immune response, and promotion of invasion of surrounding tissues by tumor cells. It can be hypothesized that circulating monocytes may be an indicator of the level of tumor-associated macrophages or reflect the level of activity of macrophages in the tumor tissue. On the contrary, circulating lymphocytes may be a surrogate for the presence of tumor-infiltrating cytotoxic lymphocytes and natural killer cells at the tumor microenvironment.[13],[14]

Hematologic parameters which were thought to be indicators of the balance between systemic inflammation and host immune response were chosen for assessment of their correlation with survival. The molecular basis of the prognostic role of systemic inflammation in disseminated cancer is still under study. Increased release of inflammatory cytokines such as IL-6, IL-8, and tumor necrosis factor alpha is thought to be responsible for loss of appetite, weight loss, and muscle wasting in the presence of progressive disease.[15],[16] These mediators such as IL-6 have angiogenic and antiapoptotic effects which directly aid in tumor growth and cell replication.[17] These inflammatory cytokines have also shown to have immune suppressive functions which can potentially hamper the efficacy of immune therapies.[18] Increased neutrophil, monocyte, and platelet levels with accompanying relative lymphopenia in the total blood counts could be a reflection of the tilting of the balance toward inflammation and loss of antitumoral T-cell activity in the tumor microenvironment.[19]

Our study has a number of limitations. This is a single-center retrospectively designed study. Although included in the exclusion criteria, unrecorded infection and drug usage could have altered the neutrophil and lymphocyte counts in some cases. There are several clinical prognostic factors which were not included such as weight loss and duration of chemotherapy which have an impact on survival. On the strong side, the study group was homogenous as only patients with advanced disease stage who were fit enough for receiving platin doublet chemotherapy were included in this study.

 > Conclusions Top

Although the interaction between tumor cells and the host immune system is a very complex process, LMR, NLR, and TLR are hematological parameters that can be easily derived from total blood counts and can be used in daily clinical practice. Among these markers, we suggest that LMR holds the greatest potential as a viable prognostic factor in the setting of metastatic NSCLC.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

 > References Top

Torre LA, Bray F, Siegel RL, Ferlay J, Lortet-Tieulent J, Jemal A, et al. Global cancer statistics, 2012. CA Cancer J Clin 2015;65:87-108.  Back to cited text no. 1
Heist RS, Engelman JA. SnapShot: Non-small cell lung cancer. Cancer Cell 2012;21:448.e2.  Back to cited text no. 2
Ettinger DS, Wood DE, Akerley W, Bazhenova LA, Borghaei H, Camidge DR, et al. Non-small cell lung cancer, version 1.2015. J Natl Compr Canc Netw 2014;12:1738-61.  Back to cited text no. 3
Molina JR, Yang P, Cassivi SD, Schild SE, Adjei AA. Non-small cell lung cancer: Epidemiology, risk factors, treatment, and survivorship. Mayo Clin Proc 2008;83:584-94.  Back to cited text no. 4
Hanahan D, Weinberg RA. Hallmarks of cancer: The next generation. Cell 2011;144:646-74.  Back to cited text no. 5
Grivennikov SI, Greten FR, Karin M. Immunity, inflammation, and cancer. Cell 2010;140:883-99.  Back to cited text no. 6
Yin Y, Wang J, Wang X, Gu L, Pei H, Kuai S, et al. Prognostic value of the neutrophil to lymphocyte ratio in lung cancer: A meta-analysis. Clinics (Sao Paulo) 2015;70:524-30.  Back to cited text no. 7
Cedrés S, Torrejon D, Martínez A, Martinez P, Navarro A, Zamora E, et al. Neutrophil to lymphocyte ratio (NLR) as an indicator of poor prognosis in stage IV non-small cell lung cancer. Clin Transl Oncol 2012;14:864-9.  Back to cited text no. 8
Lin RJ, Afshar-Kharghan V, Schafer AI. Paraneoplastic thrombocytosis: The secrets of tumor self-promotion. Blood 2014;124:184-7.  Back to cited text no. 9
Liu H, Wu Y, Wang Z, Yao Y, Chen F, Zhang H, et al. Pretreatment platelet-to-lymphocyte ratio (PLR) as a predictor of response to first-line platinum-based chemotherapy and prognosis for patients with non-small cell lung cancer. J Thorac Dis 2013;5:783-9.  Back to cited text no. 10
Teng JJ, Zhang J, Zhang TY, Zhang S, Li BS. Prognostic value of peripheral blood lymphocyte-to-monocyte ratio in patients with solid tumors: A meta-analysis. Onco Targets Ther 2016;9:37-47.  Back to cited text no. 11
Chen YM, Lai CH, Chang HC, Chao TY, Tseng CC, Fang WF, et al. Baseline and trend of lymphocyte-to-monocyte ratio as prognostic factors in epidermal growth factor receptor mutant non-small cell lung cancer patients treated with first-line epidermal growth factor receptor tyrosine kinase inhibitors. PLoS One 2015;10:e0136252.  Back to cited text no. 12
Hutterer GC, Stoeckigt C, Stojakovic T, Jesche J, Eberhard K, Pummer K, et al. Low preoperative lymphocyte-monocyte ratio (LMR) represents a potentially poor prognostic factor in nonmetastatic clear cell renal cell carcinoma. Urol Oncol 2014;32:1041-8.  Back to cited text no. 13
Hu P, Shen H, Wang G, Zhang P, Liu Q, Du J, et al. Prognostic significance of systemic inflammation-based lymphocyte- monocyte ratio in patients with lung cancer: Based on a large cohort study. PLoS One 2014;9:e108062.  Back to cited text no. 14
Batista ML Jr., Olivan M, Alcantara PS, Sandoval R, Peres SB, Neves RX, et al. Adipose tissue-derived factors as potential biomarkers in cachectic cancer patients. Cytokine 2013;61:532-9.  Back to cited text no. 15
Esper DH, Harb WA. The cancer cachexia syndrome: A review of metabolic and clinical manifestations. Nutr Clin Pract 2005;20:369-76.  Back to cited text no. 16
Guo Y, Xu F, Lu T, Duan Z, Zhang Z. Interleukin-6 signaling pathway in targeted therapy for cancer. Cancer Treat Rev 2012;38:904-10.  Back to cited text no. 17
Elkord E, Alcantar-Orozco EM, Dovedi SJ, Tran DQ, Hawkins RE, Gilham DE, et al. Tregulatory cells in cancer: Recent advances and therapeutic potential. Expert Opin Biol Ther 2010;10:1573-86.  Back to cited text no. 18
Ray-Coquard I, Cropet C, Van Glabbeke M, Sebban C, Le Cesne A, Judson I, et al. Lymphopenia as a prognostic factor for overall survival in advanced carcinomas, sarcomas, and lymphomas. Cancer Res 2009;69:5383-91.  Back to cited text no. 19


  [Figure 1], [Figure 2]

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5]


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