ROC curve analysis: a useful statistic multi-tool in the research of nephrology
Stefanos Roumeliotis, Juul Schurgers, Dimitrios Tsalikakis, Graziella D’Arrigo, Mercedes Gori, Annalisa Pitino, Daniela Leonardis, Giovanni Tripepi, Vassilios Liakopoulos
Abstract
In the past decade, scientific research in the area of Nephrology has focused on evaluating the clinical utility and performance of various biomarkers for diagnosis, risk stratification and prognosis. Before implementing a biomarker in everyday clinical practice for screening a specific disease context, specific statistic measures are necessary to evaluate the diagnostic accuracy and performance of this biomarker. Receiver Operating Characteristic (ROC) Curve analysis is an important statistical method used to estimate the discriminatory performance of a novel diagnostic test, identify the optimal cut-off value for a test that maximizes sensitivity and specificity, and evaluate the predictive value of a certain biomarker or risk, prediction score. Herein, through practical examples, we aim to present a simple methodological approach to explain in detail the principles and applications of ROC curve analysis in the field of nephrology pertaining diagnosis and prognosis.