Nomogram Model Based on Serum Metabolic Biomarkers to Predict Outcomes of First-Line Chemoimmunotherapy in Advanced Non-Small Cell Lung Cancer

Background: This study attempted to combine Serum Metabolic Biomarkers with clinical factors to construct nomograms to predict outcomes of patients with advanced non-small cell lung cancer( NSCLC) receiving first-line chemoimmunotherapy (CIT). Methods: A retrospective analysis was conducted on 112 patients with stage IIIC–IVB NSCLC receiving first-line CIT between January 2019 and January 2022.The Serum Metabolic Biomarker including lactate dehydrogenase (LDH), lactate (LAC), uric acid (UA), albumin (ALB), triglycerides (TG) and total cholesterol (TC) were examined at baseline. Patients were stratified into responders (R)and non-responders（NR） based on treatment efficacy. Progression-free survival (PFS) and overall survival (OS) were assessed via Kaplan-Meier analysis. Nomograms was created based on the multivariate Cox regression analysis to predict OS and PFS. The nomogram was internally validated using bootstrap resampling. Nomogram was assessed using the concordance index (C-index), the time-dependent area under the receiver operating curves(ROC), calibration curves, and decision curve analysis (DCA). Results: Non-diabetic status, PD-L1 expression≥50%, low LDH, LAC, UA, TC and high ALB correlated with better response (all P<0.05). Multivariate analysis revealed that stage IV , LDH ≥193 U/L, LAC ≥2.5 mmol/L, UA ≥430 μmol/L, and TG ≥3.5 mmol/L independently predicted worse PFS, while distant metastases, stage IV , BMI <21 kg/m², LDH ≥208 U/L, LAC ≥2.5 mmol/L, UA ≥430 μmol/L, TG ≥3.5 mmol/L and ALB <36 g/L independently predicted inferior OS (all P<0.05). The C-indexes of the nomogram for predicting PFS and OS were 0.759 (95% CI: 0.705–0.803) and 0.729 (95% CI: 0.723–0.783), respectively. Time-dependent Area Under the Curve( AUCs)for 12-,24-,36-month PFS (0.810,0.800,0.860) and OS (0.870,0.820,0.780) confirmed reliability. Calibration curves demonstrated a good agreement between predictions and actual observations. DCA indicated that the nomograms had good net benefits. Conclusion: Serum metabolic biomarkers (LDH, LAC, UA, ALB, TG) hold significant value in predicting outcomes of chemoimmunotherapy in advanced NSCLC. The nomograms provide accurate and practical tools to guide personalized treatment decisions.