基于实验室参数的复发性多软骨炎诊断和活动评估模型的建立与验证。
Development and validation of diagnostic and activity-assessing models for relapsing polychondritis based on laboratory parameters.
机构信息
Department of Clinical Laboratory, State Key Laboratory of Complex, Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China.
Department of Rheumatology and Clinical Immunology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College. National Clinical Research Center for Dermatologic and Immunologic Diseases (NCRC-DID), Ministry of Science and Technology. Key Laboratory of Rheumatology and Clinical Immunology, Ministry of Education, Beijing, China.
出版信息
Front Immunol. 2023 Oct 3;14:1274677. doi: 10.3389/fimmu.2023.1274677. eCollection 2023.
BACKGROUND
Relapsing polychondritis (RP) as a rare autoimmune disease is characterized by recurrent inflammation of the organs containing cartilage. Currently, no biomarkers have been integrated into clinical practice. This study aimed to construct and evaluate models based on laboratory parameters to aid in RP diagnosis, assess activity assessment, and explore associations with the pathological process.
METHODS
RP patients and healthy controls (HCs) were recruited at the Peking Union Medical College Hospital from July 2017 to July 2023. Clinical data including Relapsing Polychondritis Disease Activity Index (RPDAI) score and laboratory tests were collected. Differences in laboratory data between RP patients and HCs and active and inactive patients were analyzed.
RESULTS
The discovery cohort (cohort 1) consisted of 78 RP patients and 94 HCs. A model based on monocyte counts and neutrophil to lymphocyte ratio (NLR) could effectively distinguish RP patients from HCs with an AUC of 0.845. Active RP patients exhibited increased erythrocyte sedimentation rate, complement 3, platelet to lymphocyte ratio (PLR), NLR, and C-reactive protein to albumin ratio (CAR) compared with stable patients, which were also positively correlated with RPDAI. Notably, CAR emerged as an independent risk factor of disease activity (OR = 4.422) and could identify active patients with an AUC of 0.758. To confirm the reliability and stability of the aforementioned models, a replication cohort (cohort 2) was enrolled, including 79 RP patients and 94 HCs. The monocyte-combined NLR and CAR showed a sensitivity of 0.886 and 0.577 and a specificity of 0.830 and 0.833 in RP diagnosis and activity prediction, respectively. Furthermore, lower natural killer cell levels in RP patients and higher B-cell levels in active patients may contribute to elucidating the pathological mechanisms of disease occurrence and exacerbation.
CONCLUSIONS
The utilization of laboratory parameters provides cost-effective and valuable markers that can assist in RP diagnosis, identify disease activity, and elucidate pathogenic mechanisms.
背景
复发性多软骨炎（RP）是一种罕见的自身免疫性疾病，其特征为含软骨的器官反复发生炎症。目前，尚无生物标志物被整合到临床实践中。本研究旨在构建和评估基于实验室参数的模型，以辅助 RP 诊断、评估疾病活动度，并探索与病理过程的相关性。
方法
本研究于 2017 年 7 月至 2023 年 7 月在北京协和医院招募 RP 患者和健康对照者（HCs）。收集临床数据，包括复发性多软骨炎疾病活动指数（RPDAI）评分和实验室检查。分析 RP 患者与 HCs 以及活动期和非活动期患者之间实验室数据的差异。
结果
发现队列（队列 1）包括 78 例 RP 患者和 94 例 HCs。基于单核细胞计数和中性粒细胞与淋巴细胞比值（NLR）的模型能够有效地区分 RP 患者和 HCs，AUC 为 0.845。与稳定期患者相比，活动期 RP 患者的红细胞沉降率、补体 3、血小板与淋巴细胞比值（PLR）、NLR 和 C 反应蛋白与白蛋白比值（CAR）升高，且与 RPDAI 呈正相关。值得注意的是，CAR 是疾病活动的独立危险因素（OR=4.422），并能以 AUC 为 0.758 识别活动期患者。为了验证上述模型的可靠性和稳定性，我们纳入了一个复制队列（队列 2），包括 79 例 RP 患者和 94 例 HCs。在 RP 诊断和活动预测中，单核细胞联合 NLR 和 CAR 的灵敏度分别为 0.886 和 0.577，特异性分别为 0.830 和 0.833。此外，RP 患者自然杀伤细胞水平降低，活动期患者 B 细胞水平升高，可能有助于阐明疾病发生和加重的病理机制。
结论
利用实验室参数提供了具有成本效益的有价值的标志物，可辅助 RP 诊断、识别疾病活动度，并阐明发病机制。
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