METHODS: Patients diagnosed with RA, with or without ILD, at Beijing Tiantan Hospital from October 2019 to October 2023 were analyzed. A total of 125 RA patients were included, with 76 diagnosed with RA-ILD. The study focused on three categories of indicators: tumor markers, inflammatory indicators, and disease activity measures. The heatmap correlation analysis was employed to analyze the correlation among these indicators. Logistic regression was used to determine odds ratios (OR) for indicators linked to RA-ILD risk. Receiver-operating characteristic (ROC) curve analysis was employed to evaluate the diagnostic potential of these indicators for RA-ILD.
RESULTS: The results of logistic regression analysis showed that tumor markers (carbohydrate antigen 19-9 (CA19-9), carbohydrate antigen 125 (CA125), and cytokeratin 19 fragment (CYFRA21-1)), as well as inflammatory indicators (neutrophil, neutrophil-to-lymphocyte ratio (NLR), platelet, C-reactive protein (CRP)) and disease activity measures (disease activity score-28-CRP (DAS28-CRP), rheumatoid factor (RF), and anti-cyclic peptide containing citrulline (anti-CCP)), were significantly associated with RA-ILD. The correlation coefficients among these indicators were relatively low. Notably, the combination indicator 4, which integrated the aforementioned three categories of biomarkers, demonstrated improved diagnostic accuracy with an AUC of 0.857.
CONCLUSIONS: The study demonstrated that combining tumor markers, inflammatory indicators, and disease activity measures significantly enhanced the prediction of RA-ILD. Key Points • Multidimensional strategy: Integrated tumor markers, inflammatory indicators, and disease activity measures to enhance early detection of rheumatoid arthritis-associated interstitial lung disease (RA-ILD). • Diagnostic accuracy: Employed heatmap correlation and logistic regression, identifying significant associations and improving diagnostic accuracy with a multidimensional biomarker combination. • Superior performance: The combined multidimensional biomarker strategy demonstrated higher diagnostic precision compared to individual or dual-category indicators. • Clinical relevance: Offers a promising, accessible approach for early detection of RA-ILD in clinical settings, potentially improving patient outcomes.
方法:诊断为RA的患者,有或没有ILD,2019年10月至2023年10月在北京天坛医院进行分析。共纳入125例RA患者,76例诊断为RA-ILD。该研究集中在三类指标上:肿瘤标志物,炎症指标,和疾病活动措施。采用热图相关性分析对这些指标进行相关性分析。使用Logistic回归确定与RA-ILD风险相关的指标的比值比(OR)。采用受试者工作特征(ROC)曲线分析来评估这些指标对RA-ILD的诊断潜力。
结果:logistic回归分析结果显示肿瘤标志物(糖类抗原19-9(CA19-9),糖类抗原125(CA125),和细胞角蛋白19片段(CYFRA21-1),以及炎症指标(中性粒细胞,中性粒细胞与淋巴细胞比率(NLR),血小板,C反应蛋白(CRP))和疾病活动测量(疾病活动评分-28-CRP(DAS28-CRP),类风湿因子(RF),和含瓜氨酸的抗环肽(抗CCP),与RA-ILD显著相关。这些指标之间的相关系数相对较低。值得注意的是,组合指标4,整合了上述三类生物标志物,AUC为0.857时,诊断准确性得到改善。
结论:研究表明,结合肿瘤标志物,炎症指标,和疾病活动措施显着增强了RA-ILD的预测。关键点•多维策略:整合肿瘤标志物,炎症指标,和疾病活动措施,以增强类风湿关节炎相关间质性肺病(RA-ILD)的早期检测。•诊断准确性:采用热图相关性和逻辑回归,通过多维生物标志物组合识别显著关联并提高诊断准确性。•优异的性能:与个体或双类别指标相比,组合的多维生物标志物策略显示出更高的诊断精度。•临床相关性:提供有希望的,在临床环境中早期检测RA-ILD的可访问方法,可能改善患者预后。