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Evaluation of Analytical Performance Specifications for Clinical Laboratory Tests Based on Test Misclassification
Qian Sun1,2,3, Maureen Sampson1, Claire Auger1
1Department of Laboratory Medicine, Clinical Center, National Institutes of Health, Bethesda, MD, United States.
The Journal of Applied Laboratory Medicine
|March 11, 2026
Summary
Total allowable error (TEa) does not fully capture test misclassification (TM) risk. Test misclassification is a better metric for evaluating laboratory test performance and clinical impact, accounting for bias and imprecision effects.
Area of Science:
- Clinical Chemistry
- Laboratory Medicine
- Quality Assurance
Background:
- Analytical performance specifications are crucial for clinical laboratory quality assurance.
- Total allowable error (TEa) is a common performance criterion, but its link to test result misclassification is unclear.
- TEa combines bias and imprecision, which can lead to test inaccuracies.
Purpose of the Study:
- To investigate the relationship between TEa and test misclassification (TM).
- To evaluate TM as a clinically relevant quality measure.
- To compare TM with TEa for assessing laboratory test performance.
Main Methods:
- Generated hypothetical test results with bias and imprecision using 4 test models.
- Determined test misclassification (TM) based on pre-defined cutoffs.
- Conducted simulation analyses on 14 chemistry analytes using NIH patient data.
Main Results:
- Observed a complex, nonlinear relationship between bias, imprecision, and TM.
- TM was influenced by population distribution, cutoffs, and baseline abnormal test values.
- Stringent TEa did not guarantee low TM; TM correlated with TEa to population distribution width ratio.
Conclusions:
- Test misclassification (TM) accounts for differential bias and imprecision effects.
- TM is a more accessible metric than TEa for evaluating performance.
- TM better reflects the clinical impact of laboratory test errors.
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