Towards Bayesian Evaluation of Seroprevalence Studies

Bayes’ Theorem represents a mathematical formalization of the common sense. What we know about the world today is what we knew yesterday plus what the data told us. The lack of understanding of this concept is the source of many errors and wrong judgements in the current COVID-19 pandemic. In this contribution, we show how to use the framework of Bayesian inference to produce a reasonable estimate of seroprevalence from studies that use a single binary test. Bayes’ Theorem sometimes produces results that seem counter-intuitive at first sight. It is important to realize that the reality may be different from its image represented by test results. The extent to which these two worlds differ depends on the performance of the test (i.e., its sensitivity and specificity), and the prevalence of the tested condition

Parametric and Nonparametric Population Pharmacokinetic Models to Assess Probability of Target Attainment of Imipenem Concentrations in Critically Ill Patients

Population pharmacokinetic modeling and simulation (M&S) are used to improve antibiotic dosing. Little is known about the differences in parametric and nonparametric M&S. Our objectives were to compare (1) the external validation of parametric and nonparametric models of imipenem in critically ill patients and (2) the probability of target attainment (PTA) calculations using simulations of both models. The M&S software used was NONMEM 7.2 (parametric) and Pmetrics 1.5.2 (nonparametric). The external predictive performance of both models was adequate for eGFRs ≥ 78 mL/min but insufficient for lower eGFRs, indicating that the models (developed using a population with eGFR ≥ 60 mL/min) could not be extrapolated to lower eGFRs. Simulations were performed for three dosing regimens and three eGFRs (90, 120, 150 mL/min). Fifty percent of the PTA results were similar for both models, while for the other 50% the nonparametric model resulted in lower MICs. This was explained by a higher estimated between-subject variability of the nonparametric model. Simulations indicated that 1000 mg q6h is suitable to reach MICs of 2 mg/L for eGFRs of 90-120 mL/min. For MICs of 4 mg/L and for higher eGFRs, dosing recommendations are missing due to largely different PTA values per model. The consequences of the different modeling approaches in clinical practice should be further investigated