Development of high-performance point-of-care aqueous VEGF detection system and proof-of-concept validation in RVO patients

概念证明 注意事项 计算机科学 检测点注意事项 点(几何) 血管内皮生长因子受体 水溶液 重症监护医学 医学 风险分析(工程) 化学 内科学 数学 病理 操作系统 有机化学 几何学
作者
Yuelin Wang,Siqi Zhang,Weixing Zhong,Huan Chen,Yiming Zhao,Hang Song,Tien Yin Wong,Youxin Chen,Yanchun Zhang,Chan Zhao
出处
期刊:Clinical Chemistry and Laboratory Medicine [De Gruyter]
卷期号:62 (3): 472-483 被引量:1
标识
DOI:10.1515/cclm-2023-0749
摘要

Abstract Objectives To develop a sensitive point-of-care testing (POCT) aqueous vascular endothelial growth factor (VEGF) detection system, and assess its role for predicting the response to anti-VEGF treatment in macular edema secondary to retinal vein occlusion (RVO-ME) patients. Methods An automatic point-of-care aqueous humor Magnetic Particle Chemiluminescence Enzyme Immuno-Assay (MPCLEIA) VEGF detection system was developed. The predictive values of aqueous cytokine levels, in combination with imaging parameters, on anatomical treatment response (ATR, the relative central macular thickness change [ΔCMT/bl-CMT]) were analyzed. Results The automatic MPCLEIA system was able to provide results in 45 min with only 20 μL sample. Among the 57 eyes with available pre- and post-treatment evaluation, ATR significantly correlated with levels of interleukin (IL)-6, IL-8, monocyte chemoattractant protein-1 (MCP-1) and VEGF measured by Luminex xMAP platform, and VEGF measured by MPCLEIA. Optimal cut-off values for these biomarkers were 13.26 ng/L, 23.57 ng/L, 1,110.12 ng/L, 105.52 ng/L, and 85.39 ng/L, respectively. Univariate analysis showed significant associations between ATR category (good response if ATR≤−25 % or poor response otherwise) and IL-6, IL-8, MCP-1, VEGF-xMAP, and VEGF-MPCLEIA (p<0.05). Multivariate logistic regression revealed that ATR category was significantly associated with aqueous VEGF-MPCLEIA (p=0.006) and baseline(bl)-CMT (p=0.008). Receiver operating characteristics analysis yielded an AUC of 0.959 for the regression model combining VEGF-MPCLEIA and bl-CMT, for predicting ATR category. Conclusions Our novel MPCLEIA-based automatic VEGF detection system enables accurate POCT of aqueous VEGF, which shows promise in predicting the treatment response of RVO-ME to anti-VEGF agents when combined with bl-CMT.
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