Diagnostic value of peripheral blood eosinophils for benign and malignant pulmonary nodule

Author:

Xiu Jiawei12,Wang Xilong1,Xu Wei1,Wang Shiqi1,Hu Yuhang1,Ding Renquan1,Hua Yujuan3,Liu Dazhi1ORCID

Affiliation:

1. Department of Thoracic Surgery, General Hospital of Northern Theater Command, Shenyang, China

2. Graduate School, China Medical University, Shenyang, China

3. Department of Anesthesiology, General Hospital of Northern Theater Command, Shenyang, China.

Abstract

This retrospective study aims to assess the diagnostic utility of peripheral blood eosinophil counts in distinguishing between benign and malignant pulmonary nodules (PNs) prior to surgical intervention. We involved patients presenting with PNs measuring ≤30 mm as the primary CT imaging finding prior to surgical procedures at the General Hospital of Northern Theater Command in Shenyang, China, during the period spanning 2021 to 2022. Multivariable logistic regression analysis and receiver operator characteristic curve analysis, along with area under the curve (AUC) calculations, were used to determine the diagnostic value of eosinophil. A total of 361 patients with PN were included, consisting of 135 with benign PN and 226 with malignant PN. Multivariable logistic regression analysis showed that eosinophil percentage (OR = 1.909, 95% CI: 1.323–2.844, P < .001), absolute eosinophil value (OR = 0.001, 95% CI: 0.000–0.452, P = .033), tumor diameter (OR = 0.918, 95% CI: 0.877–0.959, P < .001), nodule type (OR = 0.227, 95% CI: 0.125–0.400, P < .001), sex (OR = 2.577, 95% CI: 1.554–4.329, P < .001), and age (OR = 0.967, 95% CI: 0.945–0.989, P = .004) were independently associated with malignant PN. The diagnostic value of regression model (AUC [95% CI]: 0.775 [0.725–0.825]; sensitivity: 74.3%; specificity: 71.1%) was superior to eosinophil percentage (AUC [95% CI]: 0.616 [0.556–0.677]; specificity: 66.8%; specificity: 51.1%) (Delong test: P < .001). Peripheral blood eosinophil percentage might be useful for early malignant PN diagnosis, and combining that with other characteristics might improve the diagnostic performance.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

General Medicine

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