Lack of standardisation in interpretation and reporting of autoantibody assays: a survey analysis of Australasian laboratories with focus on line immunoassays.

Pathology(2021)

引用 3|浏览6
暂无评分
摘要
Autoantibody assays are reported in a variety of formats. Results only slightly above established cut-offs provide lower likelihood ratios; therefore, their clinical significance may be more uncertain, which is not readily communicated with dichotomous qualitative reporting. Line immunoassays (LIA) are a common method for detecting antibodies to extractable nuclear antigens (ENA) and myositis-associated antibodies. However, recommended positive cut-offs are contentious. We distributed a survey via e-mail to participants in the Royal College of Pathologists of Australasia Quality Assurance Program (RCPAQAP) Immunology modules and to a dedicated immunology mailing list in Australasia. Questions explored general viewpoints surrounding autoantibody reporting, as well as current laboratory practices, with particular focus on interpretation and reporting of the most commonly used ENA LIA manufactured by Euroimmun. There were 31 responders, representative of at least 17 unique laboratories across Australia (8 public, 5 private) and New Zealand (4 laboratories). Responses suggest that autoantibody reporting is not standardised; there was variation in general viewpoints and reporting practices, particularly regarding the interpretation of and positive cut-offs used for the Euroimmun ENA LIA, which were contrary to the manufacturer's guidelines in a majority of the responses. Interpretative qualitative reporting based on results from other investigations and the clinical history was a common theme. There is large variation in the reporting of autoantibody assays within Australasia, especially by LIA. A majority of respondents report the most commonly used ENA LIA contrary to manufacturer's guidelines; alternative positive cut-offs are commonly utilised. LIA reports should indicate the level of positivity to enhance their relevance in the clinical decision-making process.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要