Department of Medicine and Therapeutics, The Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong, China.
Medical Data Analytics Centre, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China; State Key Laboratory of Digestive Disease, Institute of Digestive Disease, The Chinese University of Hong Kong, Hong Kong, China.
Int Immunopharmacol. 2024 Dec 25;143(Pt 1):113279. doi: 10.1016/j.intimp.2024.113279. Epub 2024 Oct 1.
To investigate the correlation of serum protein biomarkers and disease activity in patients with PsA.
176 patients fulfilled the CASPAR (ClASsification criteria for Psoriatic ARthritis) were recruited in this cross-sectional study. The level of 48 protein biomarkers, cartilage and bone turn-over markers were assessed. The patients were randomly divided into a derivation-cohort and a validation-cohort at a ratio of 7:3. Patients were further categorized based on their disease activity states using cDAPSA (remission/low disease activity and moderate/high disease activity). Least absolute shrinkage and selection operator (LASSO) was used to select biomarkers which were associated with moderate/high disease activity in the derivation cohort. Receiver operating characteristic (ROC) curve, GiViTI calibration belt were used to assess the performance of the model in both cohorts.
The cohort [age: 55.5 (44.0-62.75) years, male: 80 (45.5 %)] had moderate disease activity [DAPSA: 15.9 (8.3-26.9); PASI: 3.2 (0.5-6.8)]. 101 PsA patients (57.4 %) had clinical DAPSA moderate/high disease activity. Biomarker levels associated with moderate/high disease activity included SAA (Serum amyloid A), IL-8 (Interleukin 8), IP10 (Interferon gamma-induced protein 10)/CXCL10, M-CSF (Macrophage colony-stimulating factor), SCGF-β (Stem cell growth factor), SDF-1α (Stromal cell-derived factor 1α)/CXCL12. The model's equation including the 6 biomarker levels was applied to the validation-cohort. The area under the ROC curve (AUC) for discriminating moderate/high disease activity was 0.802 and 0.835 for the derivation-and-validation-cohorts, respectively. The multi-biomarkers panel model had higher-AUC when compared with that of C-reactive protein (CRP) (AUC = 0.727, p = 0.022). The P-values of calibration charts in the two sets were 0.902 and 0.123.
The multi-biomarkers panel demonstrated the ability to discriminate patients with moderate/high disease activity from those with low disease activity/remission.
研究银屑病关节炎（PsA）患者血清蛋白生物标志物与疾病活动度的相关性。
本研究为横断面研究，共纳入符合 CASPAR（银屑病关节炎分类标准）的 176 例患者。检测了 48 种蛋白生物标志物和软骨及骨转换标志物的水平。将患者按 7：3 的比例随机分为推导队列和验证队列。根据疾病活动状态（cDAPSA：缓解/低疾病活动度和中/高疾病活动度）将患者进一步分类。推导队列中使用最小绝对值收缩和选择算子（LASSO）选择与中/高疾病活动相关的生物标志物。使用受试者工作特征（ROC）曲线和 GiViTI 校准带评估该模型在两个队列中的性能。
该队列[年龄：55.5（44.0-62.75）岁，男性：80（45.5%）]疾病活动度为中度[DAPSA：15.9（8.3-26.9）；PASI：3.2（0.5-6.8）]。101 例 PsA 患者（57.4%）有临床 DAPSA 中/高疾病活动。与中/高疾病活动相关的生物标志物水平包括 SAA（血清淀粉样蛋白 A）、IL-8（白细胞介素 8）、IP10（干扰素 γ 诱导蛋白 10）/CXCL10、M-CSF（巨噬细胞集落刺激因子）、SCGF-β（干细胞生长因子）、SDF-1α（基质细胞衍生因子 1α）/CXCL12。将该模型包含 6 种生物标志物水平的方程应用于验证队列。推导和验证队列中，ROC 曲线下面积（AUC）用于区分中/高疾病活动的 AUC 分别为 0.802 和 0.835。与 C 反应蛋白（CRP）相比，多生物标志物面板模型的 AUC 更高（AUC=0.727，p=0.022）。两组校准图的 P 值分别为 0.902 和 0.123。
多生物标志物面板能够区分中/高疾病活动度和低疾病活动/缓解的患者。
