Autoimmune diseases drive biological false-positive syphilis serology: A retrospective cohort of 35,995 tests

IF 2.9 3区医学 Q2 MEDICAL LABORATORY TECHNOLOGY

Clinica Chimica Acta Pub Date : 2025-10-09 DOI:10.1016/j.cca.2025.120643

Bin Chen , ZiJian Jiang , MinHong Lyu

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引用次数: 0

Abstract

Objectives

To analyze the related factors that may cause the biological false-positive (BFP) reaction of syphilis screening test, with a particular focus on the correlation between autoimmune diseases and the biological false-positive results of syphilis screening test. This study aims to provide insights into the mechanisms underlying BFP reactions in autoimmune diseases and to improve the accuracy of syphilis serological diagnosis.

Methods

We conducted a retrospective review of 35,995 individuals who underwent syphilis screening at Guangzhou First People's Hospital from 2016 to 2023. The clinical characteristics including age, gender, and underlying diseases were compared between patients with BFP and those with a negative result of syphlilis screening test. The differences in autoantibody profiles and anticardiolipin antibody detection results of BFP patients and negative groups were analyzed.

Results

The observed incidence rate for biological false-positive reactions was 0.78 %, among which 96.7 % of cases exhibited relatively low titers (≤1:4). Significant differences in BFP responses were observed across different age groups (P < 0.05). In the false positive group, the positive rates of anti-double-stranded DNA antibody (ds-DNA), anti-ribosomal antibody (rRNP), soluble substance A (SSA), anti-Sm antibody (Sm), anti-ribonucleoprotein antibody (nRNP), histone, anti-nucleosome antibody (AauA), centromere antibody (CENP B), and antinuclear antibody (ANA) were significantly higher compared to the negative group (P < 0.05).

Conclusion

Autoimmune diseases and specific autoantibodies are key contributors to syphilis BFP reactions. Incorporating autoimmune testing may improve screening accuracy.

查看原文本刊更多论文

自身免疫性疾病驱动生物学假阳性梅毒血清学：35,995项试验的回顾性队列

目的分析可能导致梅毒筛查生物学假阳性（BFP）反应的相关因素，探讨自身免疫性疾病与梅毒筛查生物学假阳性的相关性。本研究旨在揭示自身免疫性疾病中BFP反应的机制，并提高梅毒血清学诊断的准确性。方法回顾性分析2016年至2023年在广州市第一人民医院接受梅毒筛查的35,995例患者。比较BFP患者与梅毒筛查试验阴性患者的年龄、性别、基础疾病等临床特征。分析BFP患者与阴性组自身抗体谱及抗心磷脂抗体检测结果的差异。结果生物学假阳性反应发生率为0.78%，其中96.7%的病例滴度较低（≤1:4）。不同年龄组BFP反应差异有统计学意义（P < 0.05）。假阳性组抗双链DNA抗体（ds-DNA）、抗核糖体抗体（rnp）、可溶性物质A （SSA）、抗Sm抗体（Sm）、抗核糖核蛋白抗体（nRNP）、组蛋白、抗核小体抗体（AauA）、着丝粒抗体（CENP B）、抗核抗体（ANA）的阳性率显著高于阴性组（P < 0.05）。结论自身免疫性疾病和特异性自身抗体是梅毒BFP反应的关键因素。结合自身免疫检测可提高筛查的准确性。

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.