Yamin Zhang,1 Wei Wan,1 Rui Shen,1 Bohao Zhang,1 Li Wang,1 Hongyi Zhang,2 Xiaoyue Ren,3 Jie Cui,4,* Jinpeng Liu1,* 1Department of Oncology, Xi’an International Medical Center Hospital, Xi’an, Shaanxi, 710100, People’s Republic of China; 2Department of Urology, The First Affiliated Hospital of Xi’an Medical University, Xi’an, Shaanxi, 710077, People’s Republic of China; 3College of Life Sciences, Northwest University, Xi’an, Shaanxi, 710069, People’s Republic of China; 4Department of Oncology, The First Affiliated Hospital of Xi’an Medical University, Xi’an, Shaanxi, 710077, People’s Republic of China*These authors contributed equally to this workCorrespondence: Jie Cui, Department of Oncology, The First Affiliated Hospital of Xi’an Medical University, No. 48 Fenghao West Road, Lianhu District, Xi’an, Shaanxi, 710077, People’s Republic of China, Tel/Fax +86-15209277121, Email cuicui780204@163.com Jinpeng Liu, Department of Oncology, Xi’an International Medical Center Hospital, No. 777, Xitai Road, Chang’an District, Xi’an, Shaanxi, 710100, People’s Republic of China, Tel/Fax +86-13772079179, Email lekai0822@163.comObjective: This work aimed to explore the prognostic risk factors of lung cancer (LC) patients and establish a line chart prediction model.Methods: A total of 322 LC patients were taken as the study subjects. They were randomly divided into a training set (n = 202) and a validation set (n = 120). Basic information and laboratory indicators were collected, and the progression-free survival (PFS) and overall survival (OS) were followed up. Single-factor and cyclooxygenase (COX) multivariate analyses were performed on the training set to construct a Nomogram prediction model, which was validated with 120 patients in the validation set, and Harrell’s consistency was analyzed.Results: Single-factor analysis revealed significant differences in PFS (P< 0.05) between genders, body mass index (BMI), carcinoembryonic antigen (CEA), cancer antigen 125 (CA125), squamous cell carcinoma antigen (SCCA), treatment methods, treatment response evaluation, smoking status, presence of pericardial effusion, and programmed death ligand 1 (PD-L1) at 0 and 1– 50%. Significant differences in OS (P< 0.05) were observed for age, tumor location, treatment methods, White blood cells (WBC), uric acid (UA), CA125, pro-gastrin-releasing peptide (ProGRP), SCCA, cytokeratin fragment 21 (CYFRA21), and smoking status. COX analysis identified male gender, progressive disease (PD) as treatment response, and SCCA > 1.6 as risk factors for LC PFS. The consistency indices of the line chart models for predicting PFS and OS were 0.782 and 0.772, respectively.Conclusion: Male gender, treatment response of PD, and SCCA > 1.6 are independent risk factors affecting the survival of LC patients. The PFS line chart model demonstrates good concordance.Keywords: laboratory parameters, LC, nomogram prediction model, KM analysis, cox multivariate analysis