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Extreme value modelling of laboratory safety data from clinical studies
Author(s) -
Southworth Harry,
Heffernan Janet E.
Publication year - 2012
Publication title -
pharmaceutical statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.421
H-Index - 38
eISSN - 1539-1612
pISSN - 1539-1604
DOI - 10.1002/pst.1510
Subject(s) - extreme value theory , sample size determination , bayesian probability , statistics , data set , computer science , econometrics , mathematics
Most clinical studies collect several safety‐related laboratory variables. Generally, it is the extreme values of these variables that indicate potential safety issues. We illustrate the novel application of extreme value modelling to such data, with the aim of predicting the incidence of severe adverse drug reactions. By applying the methods to a clinical trial data set, we identify a dose–response relationship and use Bayesian techniques to identify a potential safety concern by making predictions from the fitted model, despite the small sample size. Copyright © 2012 John Wiley & Sons, Ltd.