Multivariate extreme value modelling of laboratory safety data from clinical studies.
Generally, in the interpretation of clinical safety laboratory data, it is extreme values that indicate potential safety issues. We illustrate the application of multivariate extreme value modelling to such data. Applying the methods to a clinical trial dataset, we find unexpected extremal relationships that have potentially important implications for the interpretation of such data.
AstraZeneca, Clinical Information Science, FE2 A/2, Parklands, Alderley Park, Macclesfield, Cheshire, UK. harry.southworth@astrazeneca.com
Harry
H
Southworth
Janet E
JE
Heffernan
D019411:Clinical Laboratory Techniques; D002986:Clinical Trials as Topic / Q000379:methods*; D003627:Data Interpretation, Statistical; D064420:Drug-Related Side Effects and Adverse Reactions; D006801:Humans; D015233:Models, Statistical; D015999:Multivariate Analysis