Neutrophil-To-Lymphocyte Ratio and Systemic Immune-Inflammation Index-Biomarkers in Interstitial Lung Disease

Background and objectives: The aims of the study were to evaluate the utility of neutrophil-to-lymphocyte ratio (NLR) and the systemic immune-inflammation index (SII) as inflammation markers and prognostic factors in patients with known interstitial lung disease secondary to connective tissue diseases (CTD-ILD) compared with idiopathic pulmonary fibrosis (IPF). Materials and Methods: Forty-two patients with known interstitial lung disease (21 with IPF and 21 with CTD-ILD) and 42 control matched healthy patients were included. The NLR was calculated as the absolute neutrophil count divided by the absolute lymphocyte count, and the SII was calculated as follows: SII = platelets × neutrophils/lymphocytes, with the data being obtained from the patients data charts at admission, before any treatment. Results: our hypothesis was that in patients with interstitial lung disease NLR and SII would have higher values compared with patients with CTD-ILD or control healthy patients. The mean NLR value was 3.01 (±1.35) among patients with idiopathic pulmonary fibrosis, and 2.38 (±1.08) among patients with CTD-ILD without significant statistical difference (p = 0.92). There was however a clinically significant statistical difference when compared with the control group, where NLR was 2.00 (±1.05) (p = 0.003). SII values were 619.37 (±329.51) in patients with IPF, 671.55 (±365.73) in CTD-ILD group and 569.73 (±326.67) in healthy subjects (p = 0.13) Conclusions: A mean NLR value of 2.8 and a SII value over 500 in patients with connective diseases can become a marker of pulmonary interstitial involvement. In the context of non-exacerbated interstitial lung disease, NLR and SII have reduced numerical values, without being statistically correlated with prognosis when we compared with patients with connective tissue diseases without exacerbation or with healthy people, the cut off being of 2.4. However subsequent studies in larger patient samples might provide changes in these cut-off values.