Logistic regression and other statistical tools in diagnostic biomarker studies

• Dina Mohamed Ahmed Samir Elkahwagy ^[1] ; Caroline Joseph Kiriacos ^[1] ; Manar Mansour ^[1]
  1. [1] German University in Cairo

     German University in Cairo

     Egipto

     
• Localización: Clinical & translational oncology, ISSN 1699-048X, Vol. 26, Nº. 9, 2024, págs. 2172-2180
• Idioma: inglés
• Texto completo no disponible (Saber más ...)
• Resumen

  • 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 toprovide 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.