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Activity Number:
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25
- Medical Devices and Diagnostics Speed Session
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Type:
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Contributed
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Date/Time:
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Sunday, August 8, 2021 : 1:30 PM to 3:20 PM
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Sponsor:
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Section on Medical Devices and Diagnostics
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Abstract #318692
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Title:
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The Multistage Diagnostic Testing Algorithm for Accommodating Indeterminate Results and Its Associated Inference
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Author(s):
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Ziqiang Chen* and Gregory Wilding
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Companies:
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Merck and University at Buffalo
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Keywords:
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Indeterminate results;
Multistage diagnostic testing;
Cost function;
ROC analysis
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Abstract:
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A challenge facing clinical research is in the realm of diagnostic testing in the presence of intermediate results. Several methods have been proposed recently for defining intermediate testing results to reduce erroneous decisions. All methods approach the problem without consideration of the likely retesting in practice when a given test result is deemed intermediate. We review a multistage diagnostic testing (MSDT) algorithm that addresses the problem, where a given test may be used up to k times sequentially for a given patient, with additional testing only taking place if the result from the previous stage is intermediate. We furthermore extend the method to incorporate a cost function representing either the burden on the healthcare system or patient. A bootstrap approach to statistical inference about measures of diagnostic accuracy is implemented and found to perform satisfactorily as seen in simulation studies. An application to a real data set is given to compare the traditional single-stage and the proposed multistage methods.
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Authors who are presenting talks have a * after their name.
