title: Analysis of Predictive Values Based on Individual Risk Factors in Multi-Modality Trials.
abstract: The accuracy of diagnostic tests with binary end-points is most frequently measured by sensitivity and specificity. However, from the clinical perspective, the main purpose of a diagnostic agent is to assess the probability of a patient actually being diseased and hence predictive values are more suitable here. As predictive values depend on the pre-test probability of disease, we provide a method to take risk factors influencing the patient's prior probability of disease into account, when calculating predictive values. Furthermore, approaches to assess confidence intervals and a methodology to compare predictive values by statistical tests are presented. Hereby the methods can be used to analyze predictive values of factorial diagnostic trials, such as multi-modality, multi-reader-trials. We further performed a simulation study assessing length and coverage probability for different types of confidence intervals, and we present the R-Package facROC that can be used to analyze predictive values in factorial diagnostic trials in particular. The methods are applied to a study evaluating CT-angiography as a noninvasive alternative to coronary angiography for diagnosing coronary artery disease. Hereby the patients' symptoms are considered as risk factors influencing the respective predictive values.
authors.affiliation: Department of Medical Statistics, University of Göttingen, Humboldtallee 32, 37073 Göttingen, Germany. katharina.lange@ams.med.uni-goettingen.de.
authors.forename: Katharina
authors.initials: K
authors.lastname: Lange
authors.affiliation: Department of Medical Statistics, University of Göttingen, Humboldtallee 32, 37073 Göttingen, Germany. ebrunne1@gwdg.de.
authors.forename: Edgar
authors.initials: E
authors.lastname: Brunner
keywords: coronary artery disease; diagnostic trials; negative predictive value; positive predictive value
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