Association Between the Monocyte-to-Lymphocyte Ratio and Hemoglobin Levels in Lung Cancer Patients

Abstract

Background/Aim

Cancer-related anemia is common and associated with reduced quality of life, treatment intolerance, and poorer outcomes. Inflammation plays a central role in anemia of chronic disease, yet the specific inflammatory phenotype linked to reduced erythropoiesis remains poorly defined. The monocyte-to-lymphocyte ratio (MLR) reflects chronic macrophage-driven inflammation and may offer insight into erythropoietic suppression in cancer. The aim of this study was to evaluate the association between complete blood count (CBC)-derived inflammatory ratios and erythropoietic parameters in lung cancer patients, with particular focus on the monocyte-to-lymphocyte ratio.

Materials and Methods

This retrospective cross-sectional study included 90 adult lung cancer patients with CBC data, including neutrophils, lymphocytes, monocytes, platelets, hemoglobin, and hematocrit. The first available laboratory panel for each patient was analyzed. Derived inflammatory ratios included MLR, neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR). Correlations between inflammatory markers and erythropoietic parameters (hemoglobin, hematocrit) were evaluated using Spearman’s rank correlation coefficient in a complete-case cohort.

Results

MLR showed a moderate inverse correlation with hemoglobin (ρ=−0.34, p=0.001) and hematocrit (ρ=−0.31, p=0.003). PLR demonstrated weaker inverse correlations with hemoglobin (ρ=−0.24, p=0.026) and hematocrit (ρ=−0.25, p=0.019). NLR showed minimal correlation with hemoglobin (ρ=−0.12, p=0.251) and hematocrit (ρ=−0.12, p=0.248). Hemoglobin and hematocrit were strongly correlated (ρ=0.97, p<0.001), consistent with their physiological relationship.

Conclusion

Monocyte-associated inflammation is selectively linked to erythropoietic suppression in cancer patients. CBC-derived inflammatory ratios may serve as practical indicators of anemia of chronic disease and support the role of macrophage-driven inflammation in cancer-related anemia. These findings warrant further investigation into the inflammation-erythropoiesis axis and its clinical implications.

Introduction

Cancer-related anemia is highly prevalent and contributes to treatment intolerance, fatigue, reduced physical functioning, and diminished quality of life in oncology patients. Although multiple mechanisms contribute to anemia in cancer, including nutritional deficiencies, chemotherapy-induced myelosuppression, and renal impairment, chronic inflammation plays a central role in the pathogenesis of anemia of chronic disease (1).

Inflammation impairs erythropoiesis through several interrelated mechanisms. Pro-inflammatory cytokines suppress erythroid progenitor proliferation and impair erythropoietin production and responsiveness, contributing to ineffective erythropoiesis (2). In parallel, inflammatory signaling promotes iron sequestration within the reticuloendothelial system through induction of hepatic hepcidin expression, reducing iron availability for erythropoiesis (3). Monocytes and macrophages are central mediators of these processes, acting both as sources of inflammatory cytokines and as regulators of iron handling and recycling (4).

Peripheral blood-derived inflammatory markers have attracted increasing interest as practical, low-cost indicators of systemic inflammation in cancer. Among these, the neutrophil-to-lymphocyte ratio (NLR) has been widely studied as a general marker of systemic inflammation and physiological stress and has demonstrated prognostic relevance across multiple solid tumors (5). In lung cancer specifically, elevated NLR has been consistently associated with adverse clinical outcomes (6). However, NLR predominantly reflects neutrophil-driven inflammatory responses and may not fully capture chronic inflammatory processes related to iron metabolism and erythropoietic suppression.

In contrast, the monocyte-to-lymphocyte ratio (MLR) reflects relative expansion of circulating monocytes, precursors of tissue macrophages, and may serve as an accessible surrogate marker of inflammation involving the monocyte-macrophage axis (7). Activated macrophages contribute to anemia of chronic disease by promoting hepcidin-mediated iron sequestration within the reticuloendothelial system, thereby limiting iron availability for erythropoiesis.

While inflammatory mechanisms contributing to anemia of chronic disease are well established, direct clinical studies examining whether circulating monocyte-based indices correlate with erythropoietic parameters in cancer patients remain relatively scarce (8). Numerous oncology studies have evaluated the monocyte-to-lymphocyte ratio as a prognostic biomarker, whereas relatively few have examined its association with hemoglobin or hematocrit. Furthermore, the extent to which MLR provides clinically distinct information regarding anemia beyond other commonly used complete blood count (CBC)-derived ratios, such as NLR or platelet-to-lymphocyte ratio (PLR), has not been well characterized (9-11).

Lung cancer represents a particularly informative clinical population because it is frequently characterized by both high systemic inflammatory burden and a high prevalence of cancer-related anemia, making it a suitable model for examining associations between inflammatory indices and erythropoietic parameters.

Cancer-related anemia reflects interactions among inflammatory signaling, iron regulation, and erythropoiesis rather than a single linear defect. CBC-derived inflammatory markers may therefore serve as indirect clinical indicators of inflammation-erythropoiesis coupling. In this study, we conducted a retrospective cross-sectional analysis of lung cancer patients to examine the associations between CBC-derived inflammatory ratios and erythropoietic parameters. The objective of this study was to characterize the relationship between systemic inflammatory status and erythropoietic parameters in lung cancer patients and to determine whether different CBC-derived inflammatory indices exhibit differential associations with hemoglobin and hematocrit. We hypothesized that MLR, but not necessarily NLR or PLR, would be inversely correlated with hemoglobin and hematocrit, reflecting selective coupling between monocyte-associated inflammation and erythropoiesis.

Materials and Methods

Study design and patient selection. This study was designed as a retrospective cross-sectional analysis aimed at investigating the association between CBC-derived inflammatory ratios and erythropoietic parameters in cancer patients. The primary objective was to examine whether the MLR correlates with hemoglobin and hematocrit, and to compare its performance with other inflammatory ratios, namely the NLR and PLR.

Data were obtained from electronic medical records of the Medeuropa Oradea clinic, an outpatient oncology center providing clinical evaluation, treatment and follow-up for adult patients with solid tumors; records dated between January 2016 and December 2025 were eligible for inclusion. All laboratory measurements were collected as part of routine clinical care. For the present analysis, only existing medical records were accessed, and all data were anonymized prior to processing.

Patients were eligible for inclusion if they were 18 years of age or older, had a confirmed diagnosis of lung cancer, and had a CBC with differential containing neutrophils, lymphocytes, monocytes, and platelets, as well as same-day measurements of hemoglobin and hematocrit. To ensure analytic uniformity, missing laboratory values in any of the required CBC components or erythropoietic markers led to exclusion, and in cases where multiple laboratory records existed for the same patient, only the first eligible CBC profile obtained prior to radiotherapy was retained. After applying these strict complete-case criteria, a total of 90 patients formed the final analytic cohort.

Clinical and laboratory data collection. Demographic and clinical data extracted for the cohort included age, sex, cancer type, tumor stage when available, and treatment timing relative to radiotherapy. ECOG performance status and smoking history were not systematically documented in the available records and were therefore not included in the analysis. Analyses were conducted on the overall cohort because subgroup stratification by histologic type or disease stage was limited by sample size. Quantitative measures of tumor burden and comprehensive comorbidity data were not consistently documented and therefore were not included in adjusted multivariable analyses. Because of the retrospective design and reliance on routinely documented medical records, detailed information on comorbid inflammatory conditions, intercurrent illness, and medication exposure was not consistently available and therefore could not be applied as formal exclusion criteria.

Inflammatory ratios were derived from CBC components as follows: MLR was defined as the monocyte-to-lymphocyte ratio, NLR as the neutrophil-to-lymphocyte ratio, and PLR as the platelet-to-lymphocyte ratio. Hemoglobin (g/dl) and hematocrit (%) were evaluated as continuous markers of erythropoietic status and anemia.

Statistical analysis. Data underwent an initial quality control process that involved screening for duplicate entries and physiologically implausible laboratory values based on predefined biological ranges (e.g., hemoglobin <3 or >20 g/dl, negative cell counts). No observations met criteria for exclusion during this step. All calculations and statistical procedures were performed on a strict complete-case dataset without imputation. Correlation analyses were conducted on this predefined strict complete-case cohort including all analyzed variables (n=90). Continuous variables were summarized using means and standard deviations, along with medians and interquartile ranges when appropriate, while categorical variables were summarized using counts and percentages. Distributional assumptions were evaluated using the Shapiro-Wilk test together with visual inspection of histograms. Shapiro-Wilk testing indicated significant deviation from normality for the analyzed continuous variables. Correlation analyses between inflammatory ratios and erythropoietic markers were performed using Spearman’s rank correlation coefficient because variables demonstrated non-normal distributions on formal testing. Two-sided p-values <0.05 were considered statistically significant. Because analyses were exploratory and not based on prespecified hypotheses, no formal correction for multiple comparisons was applied. All analyses were conducted in Python (version 3.11). Accordingly, the analysis was designed as an exploratory correlation study rather than a multivariable causal model. Multivariable analyses were not performed due to the exploratory design, modest sample size, and incomplete availability of key covariates. Given incomplete covariate availability and the risk of model instability, multivariable modeling was not considered statistically robust.

All analyzed data were generated during routine clinical care, and no additional procedures or follow-up were performed for research purposes. Ethical approval for this retrospective study was obtained from the Ethics Committee of MedEuropa Oradea according to decision Med039/22.01.2026 prior to data analysis. The study used de-identified data and involved no direct patient intervention. The protocol adhered to the Declaration of Helsinki.

Results

Patient characteristics. Of 112 patients initially identified, 22 (19.6%) were excluded because of missing laboratory values, leaving 90 patients in the final analytic cohort. Among excluded patients, age and sex distributions were similar to those of included patients, indicating no major demographic differences. The mean age was 64.4±7.1 years, and the median age was 64 years [interquartile range (IQR)=9.8 years]. Most patients were male (n=70, 77.8%). Histologic subtype distribution showed that most patients had non-small cell lung cancer (n=74), while smaller proportions had small cell lung cancer (n=12) or pulmonary metastases from other primary malignancies (n=4). Tumor stage distribution was predominantly advanced, with 8 patients in stage II and 69 in stages III-IV; staging information was unavailable for 13 patients. Laboratory measurements were obtained prior to radiotherapy in 82 of 90 patients, and none were receiving active chemotherapy or immunotherapy at the time of blood sampling. Treatment timing could not be confirmed for the remaining patients. ECOG performance status and smoking history were not systematically documented in the available records.

Inflammatory ratio profiles and erythropoietic parameters. Inflammatory ratios and erythropoietic markers demonstrated distributions consistent with systemic inflammation and cancer-associated anemia. Median values for NLR, MLR, and PLR were 3.55, 0.41, and 193.15, respectively, and were elevated in relation to commonly reported reference ranges for CBC-derived inflammatory markers, while hemoglobin and hematocrit values reflected mild anemia within the expected range for patients with solid tumors. Summary statistics for inflammatory ratios and erythropoietic markers are presented in Table I.

Table I. Inflammatory ratios and erythropoietic markers in lung cancer patients.

NLR: Neutrophil-to-lymphocyte ratio; MLR: monocyte-to-lymphocyte ratio; PLR: platelet-to-lymphocyte ratio.

Correlation analyses between inflammatory ratios and erythropoietic markers. Correlation analyses revealed selective associations between inflammatory ratios and erythropoietic parameters. MLR demonstrated a moderate inverse correlation with hemoglobin (ρ=−0.34, p=0.001) and hematocrit (ρ=−0.31, p=0.003). PLR exhibited weaker inverse associations with hemoglobin and hematocrit, whereas NLR showed minimal correlation with either erythropoietic marker. Hemoglobin and hematocrit were strongly correlated with each other (ρ=0.97, p<0.001) as expected for physiologically related erythropoietic parameters. A summary of correlation coefficients is provided in Table II.

Table II. Spearman correlations between inflammatory ratios and erythropoietic markers.

Spearman rank correlation coefficients (ρ) with corresponding two-sided p-values are presented for all variable pairs. NLR: Neutrophil-tolymphocyte ratio; MLR: monocyte-to-lymphocyte ratio; PLR: platelet-to-lymphocyte ratio.

Among the inflammatory ratios assessed, MLR showed the strongest association with erythropoietic suppression, whereas NLR, despite its widespread use as a general inflammatory marker in oncology, did not demonstrate a meaningful relationship with hemoglobin or hematocrit in this cohort. Scatterplots further illustrated these patterns, with MLR showing a clear inverse trend relative to hemoglobin, while NLR and PLR displayed weaker dispersion patterns. Together, these findings indicate that monocyte-related inflammatory activity may be more closely linked to erythropoietic status than neutrophil-associated or platelet-associated inflammation in patients with lung cancer.

These findings are consistent with the concept that inflammatory and erythropoietic processes operate as interconnected physiological subsystems. Although mechanistic pathways such as cytokine signaling and iron regulation were not directly assessed in this study, the observed associations align with models in which inflammation exerts distributed effects on erythropoietic output.

Summary statistics of complete blood count-derived inflammatory ratios and erythropoietic markers in the analytic cohort of lung cancer patients (n=90). Values are presented as mean±standard deviation, median with IQR, and minimum-maximum, as appropriate. Reference ranges reported in healthy adult populations: NLR ≈ 0.8-3.5; MLR ≈ 0.2-0.4; PLR ≈ 90-210.

Spearman rank correlation coefficients describing the associations between CBC-derived inflammatory ratios (NLR, MLR, PLR) and erythropoietic markers (hemoglobin and hematocrit) in lung cancer patients. Correlation coefficients (ρ) with two-sided p values are shown for all variable pairs.

Higher monocyte-to-lymphocyte ratios were inversely associated with hemoglobin levels, whereas weaker or nonsignificant associations were observed for platelet-to-lymphocyte and neutrophil-to-lymphocyte ratios. These relationships are illustrated in Figure 1.

Figure 1.

Relationship between CBC-derived inflammatory ratios and hemoglobin levels in lung cancer patients. The scatterplots illustrate the relationship between complete blood count-derived inflammatory ratios and hemoglobin levels in lung cancer patients. (A) MLR versus hemoglobin (ρ=−0.34, p=0.001); (B) PLR versus hemoglobin (ρ=−0.24, p=0.026); (C) NLR versus hemoglobin (ρ=−0.12, p=0.251). Each point represents an individual patient. LOESS curves illustrate overall trend direction. CBC: Complete blood count; MLR: monocyte-to-lymphocyte ratio; PLR: platelet-to-lymphocyte ratio; NLR: Neutrophil-to-lymphocyte ratio.

Discussion

In this retrospective cross-sectional analysis of patients with lung cancer, higher monocyte-to-lymphocyte ratios were associated with lower levels of hemoglobin and hematocrit, whereas neutrophil-to-lymphocyte and platelet-to-lymphocyte ratios demonstrated weaker or negligible associations with erythropoietic markers. These findings suggest that MLR showed stronger statistical associations with erythropoietic parameters than other commonly used CBC-derived inflammatory ratios in this dataset.

Given the cross-sectional nature of this study, the observed associations between inflammatory ratios and erythropoietic parameters should be interpreted as non-causal, and the directionality of these relationships cannot be determined.

The conceptual contribution of this study lies in the comparative evaluation of distinct inflammatory indices rather than in demonstrating a general association between inflammation and anemia, which is already well established.

The observed inverse relationship between MLR and erythropoietic parameters is consistent with previous descriptions of inflammation-driven suppression of erythropoiesis in cancer and other chronic inflammatory states (12). Pro-inflammatory cytokines, including interleukin-6 and tumor necrosis factor-α, have been shown to impair erythroid progenitor differentiation, reduce erythropoietin responsiveness, and promote functional iron deficiency through inflammatory signaling pathways (13, 14). Monocytes and macrophages are central effectors of these processes, contributing both to cytokine production and to iron retention within the reticuloendothelial system (15). In this context, an elevated MLR may be interpreted as a marker of systemic inflammatory activity that coincides with variation in erythropoietic parameters. Although this association was statistically significant, the magnitude of correlation was moderate (ρ=−0.34), corresponding to a limited proportion of explained variance, indicating that MLR captures only a partial component of erythropoietic variation.

In contrast, NLR did not demonstrate a meaningful association with hemoglobin or hematocrit in this cohort, despite its widespread use as a general inflammatory marker in oncology. Neutrophil-associated inflammation has been proposed to reflect acute inflammatory stress rather than chronic immune-mediated alterations in iron metabolism and erythropoiesis (16). PLR showed modest inverse associations with erythropoietic markers, which is biologically plausible given the acute-phase behavior of platelets and their responsiveness to inflammatory cytokines, although this association was weaker than that observed for MLR (17). The intermediate associations observed for PLR may reflect the broader role of platelets as acute-phase reactants influenced by systemic inflammatory signaling (18). Although platelet counts can increase in inflammatory states, they are not directly involved in iron regulation or erythropoietic control to the same extent as monocyte-macrophage pathways (19). PLR may therefore capture general inflammatory activity without specifically reflecting mechanisms underlying anemia of chronic disease. These findings suggest that MLR demonstrated stronger associations with anemia-related markers than other inflammatory ratios in this cohort.

Clinical interpretation of these results should consider the multifactorial nature of anemia in lung cancer, which includes nutritional deficiencies, treatment-related marrow suppression, bleeding, renal dysfunction, and bone marrow infiltration in addition to inflammation (20, 21). Although the present study does not differentiate among these mechanisms, the observed association between MLR and erythropoietic markers is consistent with a potential association between monocyte-associated inflammation and erythropoietic status in the hematologic phenotype of cancer patients. Clinically, MLR may represent a readily available adjunct marker for evaluating inflammation-associated anemia, as it is derived from routine complete blood count testing. Although specific diagnostic cutoffs cannot be established from this cross-sectional analysis, elevated MLR values may help identify patients in whom inflammatory mechanisms contribute to reduced hemoglobin levels. Prospective studies are required to determine clinically meaningful thresholds and assess integration into anemia workup algorithms. The identification of CBC-derived markers associated with these hematologic patterns may have clinical utility in risk stratification and supportive care planning, particularly in settings where advanced iron studies or cytokine measurements are not routinely available.

Few prior studies have examined CBC-derived inflammatory ratios in relation to erythropoietic outcomes, as most investigations have focused on prognostic endpoints such as survival or treatment response (22-25). Recent studies have further emphasized the relevance of inflammatory and hematologic biomarkers in lung cancer progression, prognosis and metastatic behavior (26-28). By directly comparing MLR, NLR, and PLR in relation to hemoglobin and hematocrit, the present study provides preliminary comparative evidence suggesting that MLR may outperform more commonly reported ratios in reflecting inflammation-related erythropoietic alterations. Future prospective studies incorporating iron metabolism parameters, erythropoietin levels, and treatment characteristics are needed to further clarify the mechanistic and clinical significance of these findings.

Study limitations. A key limitation of this study is its cross-sectional design, which precludes determination of directionality or causality. Although elevated MLR may reflect inflammatory processes related to erythropoiesis, it is also possible that reduced hemoglobin levels themselves influence immune cell distributions. Therefore, the relationships identified in this study should be interpreted as associative rather than mechanistic. Unmeasured clinical factors such as infection, inflammatory comorbidities, or medication exposure may have influenced inflammatory ratios and represent potential sources of residual confounding. In addition, the absence of multivariable adjustment limits the ability to account for potential confounding factors.

Additionally, although tumor stage, histologic subtype, and treatment timing were reported descriptively, subgroup-specific analyses were not performed due to limited sample sizes within individual categories. In addition, tumor burden and comorbidity burden could not be formally controlled because these variables were not uniformly documented in the available records, representing potential sources of residual confounding. The inclusion of both primary lung cancers and a small proportion of pulmonary metastases from extrapulmonary primary tumors introduces biological heterogeneity that may influence inflammatory and erythropoietic parameters. Metastatic lesions originating from different primary malignancies may exhibit distinct systemic inflammatory profiles and mechanisms of anemia compared with primary lung cancers. However, because the study objective focused on broad associations between CBC-derived inflammatory ratios and erythropoietic markers rather than tumor-specific molecular behavior, these patients were retained in the exploratory analysis. Nevertheless, this heterogeneity should be considered when interpreting the findings. In addition, because analyses were performed using a strict complete-case dataset, some degree of selection bias related to missing laboratory data cannot be excluded.

Smoking status and chronic pulmonary comorbidities such as COPD were not systematically recorded and therefore could not be evaluated as potential confounders. Furthermore, data on iron metabolism, erythropoietin levels, nutritional status, and inflammatory cytokines were not available, and therefore the biological pathways linking monocyte-associated inflammation to anemia could not be directly assessed. Despite these limitations, the study leverages routinely available hematologic indices and laboratory values, which enhances its relevance to everyday clinical practice.

Conclusion

Among lung cancer patients in this cohort, higher monocyte-to-lymphocyte ratios were associated with lower hemoglobin and hematocrit levels, whereas neutrophil-to-lymphocyte and platelet-to-lymphocyte ratios showed weaker or negligible relationships with erythropoietic markers. These findings suggest that monocyte-related inflammation may represent a relevant component of cancer-associated anemia and support the use of routine CBC-derived indices as accessible markers of inflammatory suppression of erythropoiesis. Prospective studies incorporating iron metabolism, cytokine profiling, and treatment characteristics are warranted to clarify the clinical and mechanistic implications of these observations.

Conflicts of Interest

The Authors declare no conflicts of interest.

Authors’ Contributions

Conceptualization, O.S. and N.V.; methodology, O.S.; software, O.S. and V.C.B.; validation, N.V.; formal analysis, H-D.L. and V.C.B.; investigation, O.S.; resources, O.S.; data curation, O.S.; writing–original draft preparation, O.S.; writing–review and editing, H-D.L. G.C.P. and V.C.B.; visualization, N.V.; supervision, N.V.; project administration, O.S.; funding acquisition, H-D.L. and G.C.P. All Authors have read and agreed to the published version of the manuscript.

Funding

No funding received.

Artificial Intelligence (AI) Disclosure

No artificial intelligence (AI) tools, including large language models or machine learning software, were used in the preparation, analysis, or presentation of this manuscript.