Statistical Evaluation of Prognostic versus Diagnostic Models: Beyond the ROC Curve
نویسندگان
چکیده
منابع مشابه
Statistical evaluation of prognostic versus diagnostic models: beyond the ROC curve.
BACKGROUND Diagnostic and prognostic or predictive models serve different purposes. Whereas diagnostic models are usually used for classification, prognostic models incorporate the dimension of time, adding a stochastic element. CONTENT The ROC curve is typically used to evaluate clinical utility for both diagnostic and prognostic models. This curve assesses how well a test or model discrimin...
متن کاملStatistical Evaluation of Prognostic vs Diagnostic Models: Beyond the ROC Curve
CONTENT: The ROC curve is typically used to evaluate clinical utility for both diagnostic and prognostic models. This curve assesses how well a test or model discriminates, or separates individuals into two classes, such as diseased and nondiseased. A strong risk predictor, such as lipids for cardiovascular disease, may have limited impact on the area under the curve, called the AUC or c-statis...
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This review provides the basic principle and rational for ROC analysis of rating and continuous diagnostic test results versus a gold standard. Derived indexes of accuracy, in particular area under the curve (AUC) has a meaningful interpretation for disease classification from healthy subjects. The methods of estimate of AUC and its testing in single diagnostic test and also comparative studies...
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A number of new studies have introduced a different risk score in contrast to National Institute of Health Stroke Scale (NIHSS) to predict prognosis in ischemic stroke (1, 2). Other recent studies have evaluated NIHSS and compared traditionally established risk scores, with newly modified models (3–8). New modeling can ease the access of scaling systems, develop a better educational background,...
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Diagnostic tests commonly are characterized by their true positive (sensitivity) and true negative (specificity) classification rates, which rely on a single decision threshold to classify a test result as positive. A more complete description of test accuracy is given by the receiver operating characteristic (ROC) curve, a graph of the false positive and true positive rates obtained as the dec...
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ژورنال
عنوان ژورنال: Clinical Chemistry
سال: 2008
ISSN: 0009-9147,1530-8561
DOI: 10.1373/clinchem.2007.096529