# Combined inflammatory-lipid index and tumor markers for predicting the spatial localization of lesions in early-stage non-small cell lung cancer

## TL;DR

This study developed a model combining blood markers and tumor indicators to predict where lung cancer tumors are located in early-stage patients.

## Contribution

The novelty lies in combining inflammatory-lipid indices and tumor markers to predict lesion localization in early-stage non-small cell lung cancer.

## Key findings

- WBC, α-HBDH, HDL, CEA, SF, CA153, and CA199 were identified as independent predictors of lower lobe tumor localization.
- The developed nomogram achieved an AUC of 0.806, showing good predictive performance and calibration.
- The model showed favorable clinical utility based on decision curve analysis.

## Abstract

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.

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.

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).

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.