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Activity Number: 157 - Advances in Analytic Methods and Novel Applications of the Use of Synthetic Control for Causal Estimation of Effects of Therapeutic Interventions
Type: Topic-Contributed
Date/Time: Tuesday, August 10, 2021 : 10:00 AM to 11:50 AM
Sponsor: Biometrics Section
Abstract #317365
Title: Evaluation of Diagnostic Tests for Low Prevalence Diseases with Leveraging Real-World Data
Author(s): Wei-Chen Chen* and Heng Li and Nelson Lu and Changhong Song and Chenguang Wang and Ram Tiwari and Yunling Xu and Lilly Q. Yue
Companies: FDA/CDRH and FDA/CDRH and FDA/CDRH and FDA/CDRH and JHU and FDA/CDRH and CDRH/FDA and FDA/CDRH
Keywords: Composite likelihood; Power prior; In vitro diagnostics; Sensitivity; Specificity
Abstract:

Low prevalence diseases can pose challenges in diagnostic device evaluations. For example, the clinical validation of diagnostic tests for low prevalence diseases may require a large and lengthy clinical study through evaluating a large number of subjects to observe adequate number of positive cases. In this talk, we will discuss recent developments of propensity score-integrated approaches that help to accelerate such diagnostic clinical studies by leveraging the real-world data. The approaches include a Frequentist’s method based on the composite likelihood (PSCL) and a Bayesian method based on the power prior (PSPP) that allow down-weighting of the real-world data. We then introduce a statistical procedure based on propensity score matching and PSCL/PSPP to ensure that the real-world data being leveraged are similar to prospectively screened subjects in the diagnostic device evaluations. An illustrative example will be presented for the proposed procedure.


Authors who are presenting talks have a * after their name.

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