The Impact of the Histologic Types of Lung Cancer on CBC-Derived Inflammatory Markers-Current Knowledge and Future Perspectives.

Background/

Objectives: The analysis of the complete blood count (CBC)-derived inflammatory indexes across different histological subtypes of lung cancer supports the early detection of tumor-induced inflammation and has a good predictive value for severity in cancer patients. The main objective of this article was to assess the variations in CBC-derived inflammatory markers across different histologic subtypes of lung cancer, with the final goal of identifying specific predictors of severity for each histologic subtype of lung cancer.

Methods: We conducted a retrospective descriptive study that included 202 patients diagnosed with lung carcinoma at the Clinical County Hospital Mureș. The analyzed parameters were as follows: the histological type, the stage of the tumor, patients' general data, and associated comorbidities. In addition, nine CBC-derived inflammatory indexes, like the neutrophil-to-lymphocyte ratio (NLR), derived neutrophil-to-lymphocyte ratio (d-NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), eosinophil-to-neutrophil ratio (ENR), eosinophil-to-monocyte ratio (EMR), systemic inflammatory index (SII), systemic inflammatory response index (SIRI), and aggregate index of systemic inflammation (AISI), were analyzed as predictors of severity and correlated with histologic findings.

Results: The predictors of severity differed across the histologic subtypes. SIRI, d-NLR, and age were predictors of severity in adenocarcinoma patients, while the d-NLR, ENR, leukocyte, and neutrophil count predicted severity in squamous cell carcinoma. For SCLC patients, AISI, SIRI, SII, d-NLR, EMR, ENR, MLR, leukocyte count, lymphocyte count, neutrophil count, platelets count, COPD, smoking, and male gender were predictors for severity.

Conclusions: Understanding the complexity and variations in the inflammatory response across different histologic types of lung cancer can personalize treatment regimens and target specific abnormal cellular lines, thus improving the outcome of this highly deadly condition.