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Although the single “pooled” ROC gives the average performance of the test in the population, we are frequently interested in knowing how the test performs in subgroups of patients-for example, patients with early disease or with a specific value on another covariate.ĭiagnostic tests tend to be more sensitive in advanced stages of the disease, and measures of diagnostic accuracy obtained from studies that include only patients with moderate or severe disease may not be applicable to patients with early disease or to those suspected of having the disease. Patients in these studies, however, frequently have different degrees of disease severity or different values of other covariates, such as age. For example, in most studies of diagnostic tests in glaucoma, a single ROC curve is reported to represent the performance of the test in all included patients.
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In most studies, however, ROC curves for diagnostic tests have been reported without taking into account the possible effects of covariates on test results. Thus, it describes the whole range of possible operating characteristics for the test and hence its inherent capacity for distinguishing between subjects with and those without glaucoma. 1 2Based on the notion of using a threshold to classify subjects as positive (diseased) or negative (nondiseased), an ROC curve is a plot of the true-positive rate (TPR) versus the false-positive rate (FPR) for all possible cutpoints. Receiver operating characteristic (ROC) curves are a well-accepted measure of accuracy of diagnostic tests that yield continuous or ordinal results. Using the proposed methodology, a significantly better performance of FDT 24-2 compared to SAP SITA for diagnosis of early glaucoma was demonstrated. A regression methodology to evaluate covariate effects on ROC curves can be useful for assessment of diagnostic tests in glaucoma. For 10% and 30% rim loss, FDT 24-2 PSD had a significantly larger AUC than did SAP SITA PSD.Ĭonclusions. After adjustment for age, the areas under the ROC curves (AUCs) for SAP SITA PSD for 10%, 30%, 50%, and 70% loss of neuroretinal rim area were 0.638, 0.756, 0.852, and 0.920, respectively. An ROC regression model was fitted to evaluate the influence of disease severity and age on the diagnostic performance of the pattern SD (PSD) index from FDT 24-2 and SAP SITA. Disease severity was evaluated by the amount of neuroretinal rim loss assessed by confocal scanning laser ophthalmoscopy. All patients underwent visual function testing with FDT 24-2 Humphrey Matrix and SAP SITA (Carl Zeiss Meditec, Inc., Dublin, CA). The study included 370 eyes of 211 participants, with 174 eyes of 110 patients having glaucomatous optic neuropathy and 196 eyes of 101 subjects being normal.
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To describe an approach for the evaluation of covariate effects on receiver operating characteristic (ROC) curves and to apply this methodology to the investigation of the effects of disease severity and age on the diagnostic performance of frequency doubling technology (FDT) and standard automated perimetry (SAP) visual function tests for glaucoma detection.