ReferenceRangeR:一个新颖的工具,旨在促进参考区间估计和验证。

IF 3.7 2区 医学 Q1 MEDICAL LABORATORY TECHNOLOGY
Gunnar Brandhorst, Maike Voß, Werner Wosniok, Farhad Arzideh, Rainer Haeckel, Daniel Rosenkranz, Thomas Streichert, Astrid Petersmann
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引用次数: 0

摘要

目的:参考区间(RIs)对解释实验室检测结果至关重要。建议每个医学实验室建立和审查自己的RIs。对于大多数实验室来说,直接方法的使用往往是不可行的,而间接方法是一种更可行的替代方法。然而,这些方法不仅需要医学知识,还需要统计和技术专门知识,从而限制了许多实验室的可及性。为了应对这一挑战,开发了一个基于web的应用程序,以使用真实的实验室数据来促进RIs的估计和验证。方法:使用R Studio和Shiny web框架开发应用程序。该工具支持5种间接的参考区间估计方法:refineR、TMC、TML、cosmic和reflimR。此外,Docker容器被设计为支持安全的本地部署。结果:通过简单的复制和粘贴输入,可包含多达200,000个实验室测试结果。该工具通过统计分析为基于性别的分层提供建议。此外,还开发了一种漂移检测算法来分析是否需要基于年龄的分层。RI估计的结果与底层数据分布一起显示和可视化。现有的RIs可以通过将它们与计算的区间进行比较来验证。结论:ReferenceRangeR是一个用户友好的工具,用于使用真实实验室数据估计和验证RIs,消除了对统计或技术专业知识的需求,从而支持实验室专业人员满足当前的监管标准。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ReferenceRangeR: a novel tool designed to facilitate reference interval estimation and verification.

Objectives: Reference intervals (RIs) are essential for interpreting laboratory test results. It is recommended that each medical laboratory establishes and reviews its own RIs. The use of direct methods is often unfeasible for most laboratories, while indirect methods are a more viable alternative. However, these methods require not only medical, but also statistical and technical expertise, thereby limiting accessibility for many laboratories. To address this challenge, a web-based application was developed to facilitate the estimation and verification of RIs using real-world laboratory data.

Methods: The application was developed using R Studio and the Shiny web framework. The tool supports five indirect methods for reference interval estimation: refineR, TMC, TML, kosmic and reflimR. Furthermore, a Docker container was designed to enable a secure local deployment.

Results: Up to 200,000 laboratory test results can be included via a straightforward copy-and-paste input. The tool provides recommendations for sex-based stratification by performing statistical analysis. In addition, a drift-detection algorithm was developed to analyze whether age-based stratification is necessary. The results of RI estimation are displayed and visualized alongside the underlying data distribution. Existing RIs can be verified by comparing them against calculated intervals.

Conclusions: ReferenceRangeR is a user-friendly tool for estimating and verifying RIs using real-world laboratory data, eliminating the need for statistical or technological expertise, thereby supporting laboratory professionals in meeting the current regulatory standards.

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来源期刊
Clinical chemistry and laboratory medicine
Clinical chemistry and laboratory medicine 医学-医学实验技术
CiteScore
11.30
自引率
16.20%
发文量
306
审稿时长
3 months
期刊介绍: Clinical Chemistry and Laboratory Medicine (CCLM) publishes articles on novel teaching and training methods applicable to laboratory medicine. CCLM welcomes contributions on the progress in fundamental and applied research and cutting-edge clinical laboratory medicine. It is one of the leading journals in the field, with an impact factor over 3. CCLM is issued monthly, and it is published in print and electronically. CCLM is the official journal of the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) and publishes regularly EFLM recommendations and news. CCLM is the official journal of the National Societies from Austria (ÖGLMKC); Belgium (RBSLM); Germany (DGKL); Hungary (MLDT); Ireland (ACBI); Italy (SIBioC); Portugal (SPML); and Slovenia (SZKK); and it is affiliated to AACB (Australia) and SFBC (France). Topics: - clinical biochemistry - clinical genomics and molecular biology - clinical haematology and coagulation - clinical immunology and autoimmunity - clinical microbiology - drug monitoring and analysis - evaluation of diagnostic biomarkers - disease-oriented topics (cardiovascular disease, cancer diagnostics, diabetes) - new reagents, instrumentation and technologies - new methodologies - reference materials and methods - reference values and decision limits - quality and safety in laboratory medicine - translational laboratory medicine - clinical metrology Follow @cclm_degruyter on Twitter!
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