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Activity Number:
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157
- Advances in Analytic Methods and Novel Applications of the Use of Synthetic Control for Causal Estimation of Effects of Therapeutic Interventions
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Type:
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Topic-Contributed
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Date/Time:
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Tuesday, August 10, 2021 : 10:00 AM to 11:50 AM
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Sponsor:
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Biometrics Section
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Abstract #317365
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Title:
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Evaluation of Diagnostic Tests for Low Prevalence Diseases with Leveraging Real-World Data
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Author(s):
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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
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Companies:
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FDA/CDRH and FDA/CDRH and FDA/CDRH and FDA/CDRH and JHU and FDA/CDRH and CDRH/FDA and FDA/CDRH
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Keywords:
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Composite likelihood;
Power prior;
In vitro diagnostics;
Sensitivity;
Specificity
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Abstract:
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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.
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Authors who are presenting talks have a * after their name.
