Prognostic impact of the 18F-fluorodeoxyglucose positron-emission tomography/computed tomography metabolic parameters and correlation with hematological inflammatory markers in lung cancer

Introduction: Hematological inflammatory markers and metabolic parameters in positron-emission tomography/computed tomography (PET/CT) are important indicators predicting the prognosis of the disease in lung cancer as in many cancers. This study aimed to evaluate the correlation between pretreatment hematological inflammatory markers and PET/CT metabolic parameters in nonsmall cell lung cancer (NSCLC) patients and to predict the prognostic value of these parameters. Materials and Methods: A total of 132 patients with diagnosed NSCLC who underwent PET/CT at staging were retrospectively evaluated. Hematological parameters were obtained from the hemogram taken no more than 2 weeks prior to PET/CT. Neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and mean platelet volume (MPV) were recorded. Maximum standard uptake value, SUVmean, metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were calculated. Clinical stage, tumor pathology, and overall survival were analyzed with these parameters. Results: NLR and PLR were significantly positively correlated with MTV and TLG (all P < 0.001), MPV was negatively correlated with TLG (P = 0.021). While TLG, MTV, NLR, and PLR were increased in advanced stage disease, MPV was decreased. Univariate Cox-regression analysis demonstrated that greater age (P = 0.015), advanced stage (P < 0.001), low MPV (P = 0.017), high NLR (P < 0.001), PLR (P < 0.001), MTV (P = 0.004), TLG (P = 0.001) values, multivariate Cox-regression analysis revealed that NLR (P < 0.001) and advanced stage (P < 0.001) were significant predictors of poor prognosis in patients with NSCLC. Conclusions: There were significant associations between hematological inflammatory markers and PET/CT metabolic parameters in the patients with NSCLC at the time of diagnosis. These indicators can contribute to predicting prognosis in patients with NSCLC.