Bayesian analysis of an international ELISA comparability study

Abstract

Decisions which are based on plausible ranges of measurements (such as credible intervals), are generally superior to those solely based on point estimates (such as the mean). Reliable uncertainties are thus vital, and not only in metrology. In this paper, a general method is developed to derive concentration estimates and valid uncertainties for ELISAs. Guidance on applying this Bayesian method is provided and the importance of reliable uncertainties associated with ELISAs is underlined. The applicability and virtues of the presented method are demonstrated in the context of an international comparability study.

Novel mathematical and statistical approaches to uncertainty evaluation in the context of regression and inverse problems

“…A Markov chain Monte Carlo method was used to sample from the posterior distribution of the parameters, and Figure 1 shows the logistic function obtained, cf. also [8].…”

“…The sample concentration then follows from the result of applying equation (8). Since the mean and variance of the Poisson and binomial distributions are well defined, estimates of the uncertainty in λˆ based on a GUM-type approach are fairly straightforward to derive [16].…”

Multiple-Point Evaluation Algorithms for Enhanced Precision of Pathogen-Specific Cerebrospinal Fluid/Serum Antibody Index Calculation

“…In the method catalog of the German Society for CSF Diagnosis and Clinical Neurochemistry (DGLN), a recommendation is given to preferentially use CSF/serum concentration pairs measured with similar ODs. 4 Klauenberg et al 5 use Bayesian statistics to estimate uncertainties of concentrations derived from ELISA measurements and the four-parameter logistic (4PL) equation 6 as a calibration model. The authors found results based on a range of measurements to be generally superior to those solely based on point estimates.…”

“…Klauenberg et al 5 use Bayesian statistics to estimate uncertainties of concentrations derived from ELISA measurements and the four-parameter logistic (4PL) equation 6 as a calibration model. The authors found results based on a range of measurements to be generally superior to those solely based on point estimates.…”

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“…Sample preparation affects the reliability of PCR [10], the sensitivity and robustness of mass spectrometric analysis [11] and the accuracy of protein-DNA interactions mapped using chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) [12]. Similarly, ELISA measurements can be compromised by technical issues [13], interfering endogenous and exogenous effects [14] or measurement methodology [15], with significant consequences for diagnosis and or clinical decision-making. One consequence of these challenges is many omics assays are insufficiently sensitive or specific to meet clinical needs [16].…”