Correction for bias introduced by truncation in pharmacokinetic studies of environmental contaminants

Pharmacokinetic studies of biomarkers for environmental contaminantsin humans are generally restricted to a few measurements per subjecttaken after the initial exposure. Subjects are selected for inclusion in the study if their measured body burden is above a threshold determined by the distribution of the biomarker in a control population.Such selection procedures introduce bias in the ordinary weighted least squares estimate of the decay rate lambda caused by the truncation. We show that if the data are conditioned to lie above a line with slope - lambda on the log scale then the weighted least squares estimate of lambda is unbiased. We give an iterative estimation algorithm that produces this unbiased estimate with commercially available software for fitting a repeated measures linear model. The estimate and its efficiency are discussed in the context of a pharmacokinetic studyof 2,3,7,8-tetrachlorodibenzo-p-dioxin. Unbiasedness and efficiency are demonstrated with a simulation. [ABSTRACT FROM AUTHOR]