Evaluation Value of Peripheral Absolute Eosinophil Count for the Prognosis of Lung Cancer

Abstract

Background Lung cancer remains a significant global health challenge, with both its incidence and mortality rates on the rise worldwide. Despite numerous investigations into its etiology, progression, and prognostic indicators, a pressing need persists for straightforward and efficient methods to assess the early prognosis of lung cancer. Objective This study aims to investigate the prognostic significance of absolute eosinophil count level in patients with lung cancer. Methods We conducted a retrospective analysis of clinical data from 152 lung cancer patients admitted to the First Affiliated Hospital of Anhui Medical University between June 2019 and December 2022, with follow-up conducted until May 2023. Patients experiencing tumor recurrence, metastasis, or mortality were categorized into the poor prognosis group, while the remaining patients comprised the good prognosis group. Progression-free survival time (PFS) was meticulously recorded. Group comparisons were made to identify factors influencing lung cancer prognosis, followed by multivariate Cox regression analysis. Additionally, Kaplan-Meier survival analysis was employed to assess the impact of absolute eosinophil count on survival. Receiver operating characteristic (ROC) curve analysis was utilized to evaluate the prognostic efficacy of lung cancer, with the area under the ROC curve (AUC) calculated to gauge its predictive value. To further explore the relationship between eosinophil counts and lung cancer, datasets were procured from genome-wide association analysis pooled data and the International Consortium for Lung Cancer Research for Mendelian randomization analysis, elucidating potential causal links. Results Patients were stratified into good and poor prognosis groups based on their lung cancer prognosis. A statistically significant contrast in absolute eosinophil count was observed between these groups (P=0.004). Multivariate Cox regression analysis highlighted absolute eosinophil count as an independent risk factor for lung cancer survival outcomes (HR=1.58, 95%CI=1.03-2.44, P=0.037). Kaplan-Meier analysis revealed that the PFS time for patients with elevated absolute eosinophilic counts (n=76) (618.44±72.57 ) days was shorter compared to those with normal counts (n=76) (842.32±76.04) days (P=0.048). Furthermore, the AUC was 0.634. Mendelian randomization findings indicated that eosinophil count might serve as an adverse overall risk factor for lung cancer in the East Asian population (OR=1.07, 95%CI=1.01-1.13, P=0.030) . Conclusion The elevation of absolute eosinophil count levels may adversely impact the prognosis of lung cancer patients.

Keywords

• lung neoplasms|absolute eosinophil count|prognosis|cox regression analysis|mendelian randomization analysis