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逻辑回归和其他统计工具在诊断生物标志物研究中的应用。

Logistic regression and other statistical tools in diagnostic biomarker studies.

机构信息

Pharmaceutical Biology Department, Faculty of Pharmacy and Biotechnology, German University in Cairo, Cairo, 11835, Egypt.

出版信息

Clin Transl Oncol. 2024 Sep;26(9):2172-2180. doi: 10.1007/s12094-024-03413-8. Epub 2024 Mar 26.

Abstract

A biomarker is a measured indicator of a variety of processes, and is often used as a clinical tool for the diagnosis of diseases. While the developmental process of biomarkers from lab to clinic is complex, initial exploratory stages often focus on characterizing the potential of biomarkers through utilizing various statistical methods that can be used to assess their discriminatory performance, establish an appropriate cut-off that transforms continuous data to apt binary responses of confirming or excluding a diagnosis, or establish a robust association when tested against confounders. This review aims to provide a gentle introduction to the most common tools found in diagnostic biomarker studies used to assess the performance of biomarkers with an emphasis on logistic regression.

摘要

生物标志物是多种过程的测量指标,通常用作疾病诊断的临床工具。虽然生物标志物从实验室到临床的发展过程很复杂,但最初的探索阶段通常侧重于通过利用各种统计方法来描述生物标志物的潜力,这些方法可用于评估其判别性能、建立适当的截断值,将连续数据转换为确认或排除诊断的适当二进制响应,或在针对混杂因素进行测试时建立稳健的关联。本篇综述旨在对诊断生物标志物研究中最常用的工具进行简要介绍,重点介绍逻辑回归,以评估生物标志物的性能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2136/11333519/0a7fd77e16a2/12094_2024_3413_Fig1_HTML.jpg

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