Notes

A Note on Uncertainty of Diagnostic Measures

A. Measurement Uncertainty

The intrinsic variability of measurements in diagnostic assays is expressed as measurement uncertainty. This concept replaces the traditional notion of total analytical error.

B. Sampling Uncertainty

Diagnostic measures are derived from screening or diagnostic tests applied to population samples. The variability within these samples contributes to their overall uncertainty. This intrinsic heterogeneity is present even when simple random sampling techniques are used.

C. Combined Uncertainty

Combined uncertainty is computed via uncertainty propagation rules, employing a Taylor series approximation. Estimating, evaluating, and mitigating the combined uncertainty of diagnostic measures is critical in medical diagnosis and for defining analytical performance specifications.

We have developed software tools for exploring the uncertainty of diagnostic accuracy measures and Bayes' theorem derived posterior probability for disease, which can significantly impact their clinical usefulness^2-5. The Task Group: Analytical Performance Specifications based on Outcomes of the European Federation of Clinical Chemistry and Laboratory Medicine has proposed our program Relation as a tool 'that could help us inform our clinicians, guideline developers and the IVD industry about the impact of analytical performance on test accuracy and clinical decisions' ⁶.

Theodora Chatzimichail, M.R.C.S.,
tc@hcsl.com

Related Publications

1. Kallner A, Boyd JC, Duewer DL, Giroud C, Hatjimihail AT, Klee GG, et al. Expression of Measurement Uncertainty in Laboratory Medicine; Approved Guideline. CLSI document EP29-A. Clinical and Laboratory Standards Institute; 2012:1-56.
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2. Chatzimichail T, Hatjimihail AT. A Software Tool for Exploring the Relation between Diagnostic Accuracy and Measurement Uncertainty. Diagnostics 2020;10(9):610.
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3. Chatzimichail T, Hatjimihail AT. A Software Tool for Calculating the Uncertainty of Diagnostic Accuracy Measures. Diagnostics. 2021;11(3):406.
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4. Chatzimichail T, Hatjimihail AT. A Software Tool for Estimating Uncertainty of Bayesian Posterior Probability for Disease. Diagnostics. 2024;14(4):402.
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5. Chatzimichail T, Hatjimihail AT. A Software Tool for Applying Bayes Theorem in Medical Diagnostics. BMC Medical Informatics and Decision Making, in press.
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6. Horvath AR, Bell KJL, Ceriotti F, Jones GRD, Loh TP, Lord S, Sandberg S, et al. "Outcome-based Analytical Performance Specifications: Current Status and Future Challenges." Clinical Chemistry and Laboratory Medicine. 2024;62(8):1485-1493.
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