Last updated 16 June 2024
All models use both between
subject variability (BSV) and between occasion variability (BOV) for Bayesian
estimation of the individual parameters. An occasion is defined by the dosing
interval associated with any dose which has response observations (e.g.
medicine concentrations) measured before the next dose.
Two methods are available
for choosing how to predict the dose using these sources of variability. The
first method uses both BSV and BOV to predict the parameters used to calculate
the target dose. The second method uses just BSV. This is equivalent to averaging
the BOV random effects. The second method may give a more stable dose
prediction but any real changes that might have occurred from occasion to
occasion are not shown. A simulation study has shown the potential benefits of
using the averaging method (Abrantes, Jönsson et al. 2019).
It is the user’s choice to
decide which method to use depending on what is known about the patient status
and how it might have changed from occasion to occasion. Being able to see the
dose prediction changes with dose occasion may help to identify non-random
influences such as drug interactions which are not part of the model.
When BSV and BOV are used
to estimate parameters then the area under the concentration time curve (AUC)
after each dose is calculated using the occasion specific clearance. If BSV
alone is used then the AUC is calculated using the
clearance averaged across all occasions. For future predictions of clearance
(for example when predicting cumulative AUC) the BSV alone method is used to
calculate the AUC contribution from each dose.
NextDose models with “_AVG”
in the name use BSV alone to predict doses. NextDose models whose name does not
include “_AVG” use both BSV and BOV to predict doses. Some models, e.g. for
warfarin, do not have BOV affecting the parameters used to predict the target dose so the dose predictions are the same with both methods.
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Developed by Sam Holford & Nick Holford 2012-2024
Abrantes JA, Jönsson S,
Karlsson MO, Nielsen EI. Handling interoccasion
variability in model-based dose individualization using therapeutic drug
monitoring data. Br J Clin Pharmacol.
2019;85(6):1326-36