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A benefit risk approach in cutoff determination for diagnostic tests
Jeng Mah1, Robert Magari2, Karen Kw Lo2
1Department of Biostatistics and Data Management, Beckman Coulter, Inc. Chaska, MN, USA.
Summary
Determining the optimal cutoff for diagnostic tests is crucial. A proposed net benefit-risk (BR) equation helps optimize test performance by considering disease prevalence and diagnostic accuracy, as demonstrated with a SARS-CoV-2 test.
Area of Science:
- Biomedical engineering
- Medical diagnostics
- Health informatics
Background:
- Accurate diagnostic testing relies on establishing an appropriate cutoff point to distinguish between negative and positive results.
- Clinical decisions and patient outcomes are directly influenced by the accuracy of diagnostic test results.
- Benefit-Risk (BR) analysis offers a framework for optimizing these cutoff points by quantifying potential benefits and risks.
Purpose of the Study:
- To propose a quantitative method for determining the optimal cutoff point for diagnostic tests.
- To introduce a net benefit-risk (linear BR) equation for optimizing diagnostic test performance.
- To provide a framework for comparing diagnostic tests based on their benefit-risk profiles.
Main Methods:
- Development of a net benefit-risk (linear BR) equation.
- Scaling benefit and risk components in units of risk from untreated disease.
- Utilizing diagnostic parameters, disease prevalence, and accuracy metrics within the BR equation.
- Application of the method to a biosensor rapid antigen test for SARS-CoV-2.
Main Results:
- The proposed net BR equation provides a function to determine the optimal cutoff point for diagnostic tests.
- The method allows for the comparison of different diagnostic tests based on their overall benefit and risk.
- The framework is illustrated effectively using a real-world example of a SARS-CoV-2 rapid antigen test.
Conclusions:
- The net benefit-risk equation offers a robust approach to optimizing diagnostic test cutoff points.
- This quantitative method enhances clinical decision-making by balancing the benefits of accurate diagnosis against the risks of errors.
- The framework is broadly applicable to various diagnostic tests, improving their clinical utility and design.
Keywords:
BR categoriesBR functionsComparison of diagnostic testsDiagnostic test for SARS- CoV-2Optimization of BR functionsMore Related Videos
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