ORIGINAL RESEARCH article
Front. Oncol.
Sec. Thoracic Oncology
Volume 15 - 2025 | doi: 10.3389/fonc.2025.1635315
This article is part of the Research TopicLiquid Biopsy in Non-Small Cell Lung Cancer for Diagnosis, Treatment Selection and MonitoringView all articles
Combined Inflammatory-Lipid Index and Tumor Markers for Predicting the Spatial Localization of Lesions in Early-Stage Non-Small Cell Lung Cancer
Provisionally accepted- 1Nanjing University of Chinese Medicine, Nanjing, China
- 2Jiangsu Province Hospital of Chinese Medicine, Nanjing, China
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Objective: This study evaluated the predictive value of combined inflammatory-lipid indices and tumor markers in determining lesion localization in early-stage non-small cell lung cancer (NSCLC) and developed a predictive model. Methods: A retrospective analysis of 206 early-stage NSCLC patients was conducted from December 1, 2023, to September 30, 2024. Patients were grouped based on tumor location: upper lobe and lower lobe. Significant predictors were identified through univariate and multivariate logistic regression analyses, leading to the development of a nomogram.Predictive performance was assessed using the receiver operating characteristic (ROC) curve and area under the curve (AUC). Model calibration was evaluated with a calibration plot, and decision curve analysis (DCA) was utilized to assess the model's relevance in clinical settings. Results: Among the 206 patients, 135 (65.53%) had upper lobe tumors, and 71 (34.47%) had lower lobe tumors. Significant differences were found in white blood cell (WBC) count, lymphocyte count, α-hydroxybutyrate dehydrogenase (α-HBDH), high density lipoprotein cholesterol (HDL) triglycerides, low-density lipoprotein cholesterol (LDL), total cholesterol, carcinoembryonic antigen (CEA), serum ferritin (SF), carbohydrate antigen 125 (CA125), carbohydrate antigen 153 (CA153), and carbohydrate antigen 199 (CA199) (all p < 0.05). Multivariate logistic regression identified WBC (OR: 1.46, 95% CI: 1.13–1.95, p = 0.007), a-HBDH (OR: 1.01, 95% CI: 1.00–1.03, p = 0.041), HDL (OR: 7.08, 95% CI: 1.50–36.16, p = 0.015), CEA (OR: 1.12, 95% CI: 1.02–1.23, p = 0.021), SF (OR: 1.01, 95% CI: 1.00–1.02, p = 0.020), CA153 (OR: 1.08, 95% CI: 1.00–1.16, p = 0.037), and CA199 (OR: 1.16, 95% CI: 1.07–1.27, p < 0.001) as independent risk factors for lower lobe tumor localization. An AUC of 0.806 was obtained for the nomogram (95% CI: 0.743–0.868), indicating good calibration, and showed favorable clinical utility based on decision curve analysis (DCA). Conclusion: WBC count, lymphocyte count, α-HBDH, HDL, CEA, SF, CA153, and CA199 are significant predictors of lesion localization in early-stage NSCLC. The developed nomogram, based on readily available clinical parameters, demonstrated strong predictive performance and may aid in individualized diagnosis and treatment planning. Further large-scale external validation is needed.
Keywords: NSCLC1, Spatial localization of lesions2, Predictive mode3, Tumor markers4, Inflammatory-lipid indices6
Received: 26 May 2025; Accepted: 24 Sep 2025.
Copyright: © 2025 Yang, Zhao, Cheng, Ge, Ren, Xu and Zhang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Bin Zhang, drzhangbin@163.com
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