Zhang Yamin, Wan Wei, Shen Rui, Zhang Bohao, Wang Li, Zhang Hongyi, Ren Xiaoyue, Cui Jie, Liu Jinpeng
Department of Oncology, Xi'an International Medical Center Hospital, Xi'an, Shaanxi, 710100, People's Republic of China.
Department of Urology, The First Affiliated Hospital of Xi'an Medical University, Xi'an, Shaanxi, 710077, People's Republic of China.
Onco Targets Ther. 2024 Feb 21;17:131-144. doi: 10.2147/OTT.S444396. eCollection 2024.
This work aimed to explore the prognostic risk factors of lung cancer (LC) patients and establish a line chart prediction model.
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.
Single-factor analysis revealed significant differences in PFS (<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 (<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.
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.
本研究旨在探讨肺癌（LC）患者的预后危险因素，并建立线图预测模型。
选取322例LC患者作为研究对象。将他们随机分为训练集（n = 202）和验证集（n = 120）。收集基本信息和实验室指标，并对无进展生存期（PFS）和总生存期（OS）进行随访。对训练集进行单因素和环氧化酶（COX）多因素分析以构建列线图预测模型，该模型在验证集的120例患者中进行验证，并分析Harrell一致性。
单因素分析显示，性别、体重指数（BMI）、癌胚抗原（CEA）、癌抗原125（CA125）、鳞状细胞癌抗原（SCCA）、治疗方法、治疗反应评估、吸烟状况、心包积液的存在以及程序性死亡配体1（PD-L1）在0和1-50%时PFS存在显著差异（<0.05）。年龄、肿瘤位置、治疗方法、白细胞（WBC）、尿酸（UA）、CA125、胃泌素释放肽前体（ProGRP）、SCCA、细胞角蛋白片段21（CYFRA21）和吸烟状况在OS方面存在显著差异（<0.05）。COX分析确定男性、疾病进展（PD）作为治疗反应以及SCCA>1.6为LC患者PFS的危险因素。预测PFS和OS的线图模型的一致性指数分别为0.782和0.772。
男性、PD治疗反应以及SCCA>1.6是影响LC患者生存的独立危险因素。PFS线图模型显示出良好的一致性。
