Predictive value of dynamic changes in peripheral blood inflammation and blood lipid-related indices for the lung cancer treatment efficacy.

Abstract

To investigate the dynamics of inflammation and lipid-related indicators in lung cancer patients and their impact on treatment efficacy. A retrospective analysis was conducted on 133 lung cancer patients who seek for primary treatment at Wujin Hospital Affiliated to Jiangsu University from January 2019 to August 2022. The inflammation and blood lipid-related indicators were collected 1 week before treatment and after 2 cycles of treatment. We compared the changes in these indicators among patients with different treatment methods and outcomes. The diagnostic value of the dynamic changes in each index for disease progression was calculated using the ROC curve. The risk factors influencing disease development were identified using multifactorial logistic regression analysis. After 2 cycles of treatment, the white blood cell count (WBC, P<0.001), neutrophil count (NC, P<0.001), neutrophil-to-lymphocyte ratio (NLR, P<0.001) in the disease progression (PD) group were significantly increased, triglyceride (TG, P=0.023), apolipoprotein A1 (APO-A1, P=0.009) was significantly decreased. The results showed that ∆NC had the highest sensitivity (88.24%) in predicting disease progression, and ∆WBC had the best specificity (77.78%). Multivariate regression analysis showed that ΔWBC (P<0.001), ΔTG (P=0.041), and treatment method (P=0.010) were independent risk factors for disease progression (PD). The changes of WBC and TG before and after treatment are promising indicators for predicting the progression of lung cancer and may offer a new direction for lung cancer treatment.