A Step-by-Step Guide to Selecting an Optimal Cut-Off Value Based on the Receiver Operating Characteristic and Youden Index in Methods Designed to Diagnose Lyme Disease.

Abstract

Detection tools designed to diagnose complex diseases such as Lyme Borreliosis require an optimal cutoff point to distinguish the healthy from the diseased. The chapter will provide a practical guide to selecting an optimal cutoff mark by creating the receiver operating characteristic (ROC) in Microsoft Excel. To guide the creation of a ROC graphical plot, we will use example data from an enzyme-linked immunosorbent assay (ELISA) measuring anti-human immunoglobulin G (IgG) against whole-cell Borrelia lysates. Herein, the ROC method will demonstrate that an optical density (OD) value from ELISA with the highest Youden Index (J) is an optimal cutoff value to differentiate positive and negative IgG immune responses in human serum samples.