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Estimating the Accuracy of Polymerase Chain Reaction–Based Tests Using Endpoint Dilution

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Polymerase chain reaction (PCR)–based tests for various microorganisms or target DNA sequences are generally acknowledged to be highly “sensitive,” yet the concept of sensitivity is ill-defined in the literature on these tests. We propose that sensitivity should be expressed as a function of the number of target DNA molecules in the sample (or specificity, when the target number is 0). However, estimating this “sensitivity curve” is problematic, since it is difficult to construct samples with a fixed number of targets. Nonetheless, using serially diluted replicate aliquots of a known concentration of the target DNA sequence, we show that it is possible to disentangle random variations in the number of target DNA molecules from the underlying test sensitivity. We develop parametric, nonparametric, and semiparametric (spline-based) models for the sensitivity curve. The methods are compared on a new test for M. genitalium.
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Keywords: Endpoint dilution; Expectation maximization algorithm; Isotonic estimation; Monotone smoothing spline; Polymerase chain reaction; Sensitivity; Specificity

Document Type: Research Article

Affiliations: 1: Department of Biostatistics 357232, University of Washington, Seattle, Washington 98195, U.S.A. 2: Department of Medicine, University of Washington, Seattle, Washington, U.S.A.

Publication date: 2003-09-01

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