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Youden index estimation based on group-tested data
Jin Yang1, Aiyi Liu1, Neil Perkins1
1National Institute of Child Health and Human Development, Bethesda, Maryland, United States.
Statistical Methods in Medical Research
|December 11, 2024
Summary
This study introduces methods to estimate the Youden index, a measure of diagnostic accuracy, using group-tested data. The research demonstrates how to assess biomarker effectiveness even without individual disease status information.
Area of Science:
- Biostatistics
- Diagnostic Accuracy
- Epidemiology
Background:
- The Youden index quantifies a biomarker's maximum diagnostic accuracy by balancing sensitivity and specificity.
- Estimating the Youden index is challenging with group-tested data due to the lack of individual disease status.
- Differential false positives and negatives further complicate estimation in disease screening scenarios.
Purpose of the Study:
- To develop and present methods for estimating the Youden index from group-tested data.
- To address the challenges posed by unavailable individual disease statuses and differential error rates.
- To evaluate the diagnostic performance of monocytes in predicting chlamydia using real-world data.
Main Methods:
- Proposed both parametric and nonparametric statistical procedures for Youden index estimation.
- Utilized data from the National Health and Nutrition Examination Survey (NHANES) for practical application.
- Applied methods to assess the diagnostic utility of monocyte counts for chlamydia prediction.
Main Results:
- Successfully developed and demonstrated methods for estimating the Youden index with group-tested data.
- The NHANES data analysis provided an evaluation of monocyte's diagnostic capability for chlamydia.
- The proposed procedures offer a viable approach for biomarker accuracy assessment in resource-limited settings.
Conclusions:
- Parametric and nonparametric methods can effectively estimate the Youden index using group-tested data.
- Monocyte evaluation using these methods highlights potential diagnostic applications.
- The study contributes robust statistical techniques for biomarker assessment in public health research.
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