干扰胆红素检测:肺边缘区淋巴瘤表现单克隆冷球蛋白。

IF 3.2 3区 医学 Q2 MEDICAL LABORATORY TECHNOLOGY
Clinica Chimica Acta Pub Date : 2025-02-01 Epub Date: 2024-12-06 DOI:10.1016/j.cca.2024.120066
Yi Li, Liangqiong Zhou, Kangyi Wang, Xiaoge Luo, Liqun Zhang, Kaiyong Cai
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引用次数: 0

摘要

肺边缘带淋巴瘤(MZL)是一种惰性b细胞淋巴瘤。大多数肺部MZL患者的外周血含有低或检测不到的单克隆免疫球蛋白(M蛋白)水平。在本例中,临床实验室发现肺部MZL患者不仅与高浓度的单克隆igg型蛋白相关,而且表现出明显的凝胶形成特征,干扰了临床生化检查。因此,本研究考察了M蛋白在总胆红素测定中的作用。进行单克隆IgG蛋白与多克隆免疫球蛋白的总胆红素检测曲线差异比较、干扰实验、稀释消除实验。这些实验不仅表明M蛋白对胆红素检测的干扰与其浓度呈正相关,而且表明M蛋白特异性干扰不同于多克隆免疫球蛋白。我们采用R和灌顶统计系统评估血清单克隆蛋白和总胆红素吸光度曲线数据的相关性。多变量分析显示,球蛋白(GLB)与平方根变换曲线光密度(OD)数据之间存在非线性相关。受试者工作特征(ROC)曲线分析显示,GLB ≥ 31.9 g/L亚组的曲线下面积(AUC)为0.852。我们的发现可以加强临床对M蛋白的筛查和对需要进行血清蛋白电泳检测人群的科学评估,从而降低M蛋白人群的漏诊率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An interference in bilirubin detection: Pulmonary marginal zone lymphoma presenting monoclonal cryoglobulin.

Marginal zone lymphoma (MZL) of the lung is an indolent B-cell lymphoma. The peripheral blood of most patients with pulmonary MZL contains low or undetectable monoclonal immunoglobulin (M protein) levels. In this case, the clinical laboratory discovered that the pulmonary MZL patient not only associated with high concentration of monoclonal IgG-type protein but also exhibited obvious gel formation characteristics that interfered with clinical biochemistry tests. Thus, the role of M protein in total bilirubin determination was examined in this study. Total bilirubin detection curve difference comparison between monoclonal IgG protein and polyclonal immunoglobulin, interference experiments, and dilution elimination experiments were conducted. These experiments revealed not only a positive correlation between M protein interference in bilirubin detection with its concentration, but also M protein-specific interference distinct from polyclonal immunoglobulin. We employed the R and EmpowerStat statistical systems to evaluate the correlation between serum monoclonal protein and total bilirubin absorbance curve data. Multivariate analysis revealed a nonlinear correlation between with globulin (GLB) and square root transformed curve optical density (OD) data. The receiver operating characteristic (ROC) curve analysis indicated an area under the curve (AUC) of 0.852 for the GLB ≥ 31.9 g/L subgroup using combined curve indicators. Our findings can enhance clinical M protein screening and scientific assessment of the populations requiring serum protein electrophoresis testing, thereby reducing the rate of missed diagnoses in the M protein population.

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来源期刊
Clinica Chimica Acta
Clinica Chimica Acta 医学-医学实验技术
CiteScore
10.10
自引率
2.00%
发文量
1268
审稿时长
23 days
期刊介绍: The Official Journal of the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) Clinica Chimica Acta is a high-quality journal which publishes original Research Communications in the field of clinical chemistry and laboratory medicine, defined as the diagnostic application of chemistry, biochemistry, immunochemistry, biochemical aspects of hematology, toxicology, and molecular biology to the study of human disease in body fluids and cells. The objective of the journal is to publish novel information leading to a better understanding of biological mechanisms of human diseases, their prevention, diagnosis, and patient management. Reports of an applied clinical character are also welcome. Papers concerned with normal metabolic processes or with constituents of normal cells or body fluids, such as reports of experimental or clinical studies in animals, are only considered when they are clearly and directly relevant to human disease. Evaluation of commercial products have a low priority for publication, unless they are novel or represent a technological breakthrough. Studies dealing with effects of drugs and natural products and studies dealing with the redox status in various diseases are not within the journal''s scope. Development and evaluation of novel analytical methodologies where applicable to diagnostic clinical chemistry and laboratory medicine, including point-of-care testing, and topics on laboratory management and informatics will also be considered. Studies focused on emerging diagnostic technologies and (big) data analysis procedures including digitalization, mobile Health, and artificial Intelligence applied to Laboratory Medicine are also of interest.
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