Diagnostic accuracy evaluation using ROC curve analysis

Abstract

The diagnostic accuracy of a biochemical quantity is inversely related to the overlapping zone between the values of the population suffering from a disease and the population which does not. The ROC curves are an indirect measure of the overlapping zone between both populations. Specimens (plasma and urine) taken from 928 patients with symptoms of acute abdominal pain were used and the catalytic concentration of alpha-amylase, pancreatic alpha-amylase and triacylglycerol lipase (determined by two methods) were measured. Definitive diagnosis was obtained by following the directives of expert groups on the evaluation of diagnostic tests. Diagnostic accuracy was characterized by calculating the diagnostic sensitivity and specificity, by representing the ROC curves and by quantifying the areas under the ROC curves. The catalytic concentration of pancreatic alpha-amylase in plasma was the quantity with a greater area under the ROC curve (A = 0.9740) and then the one which had greatest diagnostic accuracy. If we considered the upper limit of the reference interval to be the cut-off value, the catalytic concentration of pancreatic alpha-amylase in plasma had a diagnostic sensitivity and specificity values of 0.96 and 0.88 respectively for the acute pancreatitis.

Evaluation of Serum Procollagen Aminoterminal Propeptide III, Laminin, and Hydroxyproline as Predictors of Severe Fibrosis in Patients with Chronic Hepatitis C

“…An AUC of 1.0 is characteristic of an ideal test, whereas 0.5 indicates a test of no diagnostic value. [15] The multivariate discriminant analysis (MDA) was carried out stepwise with use of the minimum Wilks' lambda. The diagnostic sensitivity, specificity, efficiency, and positive predictive (PPV) and negative predictive (NPV) values were calculated.…”

Reliability and validity of lumbar and abdominal trunk muscle endurance tests in office workers with nonspecific subacute low back pain

“…The two tests performed in the present study were associated with acceptable AUC values [28] for both men and women. This indicates that the tests had good predictive validity.…”

Analysis of a Multilevel Diagnosis Decision Support System and Its Implications: A Case Study

“…However, if a DDSS is used in real medical practice, and if a physician is expected to rely on it to guide his own diagnoses, it is important to ensure that the accuracy of the system is also sufficiently high. As per Miller et al [4], a critical area relevant to all medical diagnosis decision systems (MDDSs) is validation, evaluation, and ongoing quality assurance, with accuracy being the most important metric to be evaluated [5, 6]. …”