Paper
1 April 1996 Theoretical and practical implications of a new definition of the minimal detectable concentration for immunoassays
Emery N. Brown
Author Affiliations +
Abstract
The minimal detectable concentration (MDC), the smallest analyte concentration an immunoassay can reliably measure, is a fundamental property of an assay. Different interpretations of 'the smallest concentration an immunoassay can reliably measure' have led to different mathematical formulations of the MDC definition. We interpret this concept to mean the smallest analyte concentration the immunoassay may report as greater than the zero dose with high probability, say 0.95. Using Bayes' theorem we have developed a new MDC definition and shown that each of the current definitions approximates some component of the new one. We extend our paradigm for computing the MDC and derive a statistical framework for analyzing uncertainty in small analyte concentrations. We compute for any immunoassay measurement the probability that it exceeds the zero dose, its 95% confidence interval, its coefficient-of-variation (CV) and the probability that it is greater than any previous measurement. We illustrate the framework in a study of theoretical data based on our previous analyses of the Abbott microparticle capture enzyme immunoassay assay (MEIA) for prostate- specific antigen (PSA). The paradigm provides a sounder conceptual and computational approach for measuring reliably low concentrations of biological substances and for defining a positive result for screening and diagnostic tests.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Emery N. Brown "Theoretical and practical implications of a new definition of the minimal detectable concentration for immunoassays", Proc. SPIE 2680, Ultrasensitive Biochemical Diagnostics, (1 April 1996); https://doi.org/10.1117/12.237638
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Cited by 1 scholarly publication.
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KEYWORDS
Statistical analysis

Calibration

Error analysis

Analytical research

Biological research

Cancer

Data analysis

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