Pei Bei, Sun Qin, Zhang Yi, Wen Ziang, Ding Wenjing, Wu Kairui, Li Tingting, Li Xuejun
The First Clinical Medical College, Anhui University of Traditional Chinese Medicine, Hefei, 230000, Anhui, China.
Department of Gastroenterology, The Second Affiliated Hospital of Anhui University of Traditional Chinese Medicine, Hefei, 230000, Anhui, China.
BMC Cancer. 2025 Jan 10;25(1):63. doi: 10.1186/s12885-024-13394-0.
This study aimed to investigate the diagnostic potential of serum CXC chemokine ligand 5 (CXCL5) in patients with chronic atrophic gastritis (CAG) and to establish a prediction model for better diagnosis of CAG.
A retrospective analysis was conducted, encompassing 570 cases of CAG patients admitted to the Department of Gastroenterology of the Second Affiliated Hospital of Anhui University of Traditional Chinese Medicine, who underwent gastroscopy and received pathologically confirmed diagnoses between June 2018 and June 2023. Additionally, 570 cases without CAG who underwent health checkups were included and classified into the control group. Single-factor and multi-factorial logistic regression analyses were employed to identify risk factors of CAG, and a prediction model for diagnosing CAG was developed using R software. The predictive performance of the constructed model was verified and evaluated through ROC analysis, decision curve analysis (DCA), and prediction efficacy curve.
Multi-factorial logistic regression analysis revealed that history of smoking, family history of tumurs, Pepsinogen I (PG I), Gastrin 17 (G-17), Helicobacter pylori infection, D-dimer, and CXCL5 were independent risk factors in CAG patients. A nomogram for the diagnosis of CAG was constructed using R software. The ROC curve demonstrated that CXCL5 showed the best predictive efficacy as a single indicator, with an AUC of 0.897, a sensitivity of 0.789, and a specificity of 0.999. Furthermore, the nomogram exhibited an AUC of 0.992, a sensitivity of 0.958, and a specificity of 0.970. Calibration and DCA curves indicated that the predicted values of the nomogram were highly concordant with the observed values, thus demonstrating a high predictive value.
In this study, we found a correlation between serum CXCL5 level and CAG, and developed a prediction model to assist the clinical diagnosis of CAG.
本研究旨在探讨血清CXC趋化因子配体5（CXCL5）在慢性萎缩性胃炎（CAG）患者中的诊断潜力，并建立一个预测模型以更好地诊断CAG。
进行回顾性分析，纳入安徽中医药大学第二附属医院胃肠科收治的570例CAG患者，这些患者在2018年6月至2023年6月期间接受了胃镜检查并获得病理确诊。此外，纳入570例未患CAG的健康体检者作为对照组。采用单因素和多因素逻辑回归分析确定CAG的危险因素，并使用R软件建立诊断CAG的预测模型。通过ROC分析、决策曲线分析（DCA）和预测效能曲线对构建模型的预测性能进行验证和评估。
多因素逻辑回归分析显示，吸烟史、肿瘤家族史、胃蛋白酶原I（PG I）、胃泌素17（G-17）、幽门螺杆菌感染、D-二聚体和CXCL5是CAG患者的独立危险因素。使用R软件构建了CAG诊断列线图。ROC曲线显示，CXCL5作为单一指标预测效能最佳，AUC为0.897，灵敏度为0.789，特异度为0.999。此外，列线图的AUC为0.992，灵敏度为0.958，特异度为0.970。校准曲线和DCA曲线表明，列线图的预测值与观察值高度一致，具有较高的预测价值。
在本研究中，我们发现血清CXCL5水平与CAG之间存在相关性，并建立了一个预测模型以辅助CAG的临床诊断。
