Estimating Antigen Test Sensitivity via Target Distribution Balancing: Development and Validation Study
We present a distribution-aware framework that models PPA as a logistic function of Ct and reweights results to a standardized reference Ct distribution to produce bias-corrected sensitivity estimates. This yields fairer, more consistent comparisons across AT suppliers and studies, strengthens quality control, and supports regulatory review. Collectively, our results provide a robust basis for recalibrating reported sensitivities and underscore the importance of distribution-aware evaluation in diagnostic test assessment.
Authors
- Nol Salcedo (ORCID: https://orcid.org/0000-0002-4232-3268)
- Jose Arocha
- Miguel Bosch (ORCID: https://orcid.org/0000-0003-0206-2427)
- Adriana Moreno
- Raul Colmenares
- Irene Bosch (ORCID: https://orcid.org/0000-0003-1352-5888)
- Dawlyn García (ORCID: https://orcid.org/0000-0002-9489-8506)
- A. Garcia
- Daniela Hall
- Lindsey Rudtner
- Sina Hoche (ORCID: https://orcid.org/0000-0003-0452-4146)
Institutions
- Clinton Foundation (US)
- EP Analytics (United States) (US)
- Brookline Public Schools (US)
Publication Details
- Journal
- JMIR Bioinformatics and Biotechnology
- Published
- 2025-10-20
- DOI
- https://doi.org/10.2196/68476
- Primary Topic
- SARS-CoV-2 detection and testing
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Broad Institute
- National Institutes of Health
- Centers for Disease Control and Prevention