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Analysis of Predictive Values Based on Individual Risk Factors in Multi-Modality Trials

Author(s): Katharina Lange | Edgar Brunner

Journal: Diagnostics
ISSN 2075-4418

Volume: 3;
Issue: 1;
Start page: 192;
Date: 2013;
Original page

Keywords: positive predictive value | negative predictive value | diagnostic trials | coronary artery disease

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.
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