RRML - Evaluation of Diagnostic Tests: Receiver Operating Characteristic Curves
AMLR

ISSN online: 2284-5623

ISSN-L: 1841-6624

Rejection rate (2020): 75%

Română English


Journal Metrics

Impact Factor 0.5
Five Year Impact Factor 0.5
JCI 0.12


Advanced search


Top 10 downloaded articles
- December 2024 -
 
Biomarkers of acute kidney inj... 6
A comprehensive review of glyc... 6
Investigation of cytokine chan... 6
Validation of GOD / PAP method... 4
Romanian Review of Laboratory ... 4
Towards appropriate training f... 4
Small patients, big challenges... 3
Expressions of vascular endoth... 3
Role of Th1/Th2 imbalance medi... 3
Recomandările naționale ale ... 3

Log in

Concept, Design & Programming
Dr. Adrian Man

   
 
Nr. 19(3)/2011
XML
TXT

Evaluation of Diagnostic Tests: Receiver Operating Characteristic Curves

Cristian Baicus, Adriana Hristea, Anda Baicus


Abstract:

Receiver operator characteristic (ROC) curves are used in order to assess the accuracy of diagnostic tests whose results are continuous numeric variables. This curve is a graph of the sensitivity (or true positive rate) on the Y-axis as a function of 1-specificity (the false positive rate) on the Y-axis. ROC curves have multiple utilizations: 1. The comparison of more tests for the same disease (bigger the area under the ROC curve (AUROC), better the test; an AUROC of 1 means a perfect test, while an AUROC of 0.5 means a useless test; 2. The choice of a cut-off point (in case of a test with a big AUROC, one can choose the closest point to the upper left corner of the graph, in order to have both a good sensitivity and a good specificity); 3. It shows how, for the same diagnostic test, there is a negotiation between sensitivity and specificity so that, for a cut-off with a very good sensitivity it will be a weak specificity and the reverse.

 
  PDF Download full text PDF
(353 KB)
     
 
How to cite
Baicus C, Hristea A, Baicus A. Evaluation of Diagnostic Tests: Receiver Operating Characteristic Curves. Rev Romana Med Lab. 2011;19(3):303-6