Challenges in harmonizing immunoassays: The use of the Bland-Altman based harmonization algorithm

IF 3.2 3区医学 Q2 MEDICAL LABORATORY TECHNOLOGY

Clinica Chimica Acta Pub Date : 2025-03-22 DOI:10.1016/j.cca.2025.120247

Wenqing Liu , Xing Qi , Huaguo Wang , Sheng Lin , Yan Zhang , Ping Zhu , Xiaoqin Gou , Xin Chang , Wenqing Chu , Jinbo Liu , Yuanbiao Guo

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引用次数: 0

Abstract

Background

In this study, we compared the recently proposed Bland-Altman plot-based harmonization algorithm (BA-BHA) with the weighted Deming regression-based harmonization algorithm (WD-BHA) taken as an example in ISO 21151:2020, aiming to evaluate the effectiveness of BA-BHA and discuss the applicability of these two different harmonization algorithms.

Methods

BA-BHA and WD-BHA were applied to 19 measurands on LiCA medical devices, Chemclin Diagnostics Co., Ltd. A panel of 80 patient sera were collected for each measurand and the effectiveness of BA-BHA and the applicability of the two different harmonization algorithms were specified according to the Bland-Altman (B-A) plot, curve estimation and the Passing-Bablok regression.

Results

After harmonized with BA-BHA, the mean of the B-A plot for each measurand was close to zero, and the limits of agreement (LoAs) met the quality requirements. The distribution of the variations in the B-A plot was demonstrated approximately symmetric over the measuring interval. Furthermore, “0” was included in the 95% confidence interval of the intercept and “1” was included in the 95% confidence interval of the slope for the Passing-Bablok regression, indicating acceptable harmonization effects for all 19 measurands. In contrast, acceptable harmonization effects were achieved in only some of the 19 measurands.

Conclusion

Acceptable harmonization effects can be achieved for various measurands by BA-BHA because both the mean and the distribution of percent differences in the B-A plot can be adjusted, which demonstrating BA-BHA with a more extensive applicability compared to WD-BHA.

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协调免疫测定的挑战：使用基于Bland-Altman的协调算法。

背景：本研究以ISO 21151:2020为例，比较了最近提出的基于Bland-Altman标图的协调算法（BA-BHA）和基于加权Deming回归的协调算法（WD-BHA），旨在评价BA-BHA的有效性，并讨论这两种不同协调算法的适用性。方法：将BA-BHA和WD-BHA分别应用于化学临床诊断有限公司LiCA医疗器械的19个指标。每项测量收集80例患者血清，并根据Bland-Altman （B-A）图、曲线估计和passin - bablok回归来指定BA-BHA的有效性和两种不同协调算法的适用性。结果：经与BA-BHA协调后，各测量值的B-A图均值接近于零，一致性限（LoAs）满足质量要求。B-A图的变化分布在测量区间内近似对称。此外，Passing-Bablok回归的截距95%置信区间中包含“0”，斜率95%置信区间中包含“1”，表明所有19个测量值的协调效果都是可以接受的。相比之下，19项措施中只有一些达到了可接受的协调效果。结论：由于B-A图的平均值和百分比差异分布都可以调整，因此BA-BHA对各种测量的协调效果可以接受，这表明BA-BHA比WD-BHA具有更广泛的适用性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

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.