RE: Right skewness in bootstrap distribution
Dear Felipe,
The distribution obtained from the (nonparametric) bootstrap represents
uncertainty in the population parameters, and the histogram for V1 should not
be interpreted as a distribution of individual parameter values. There are
issues with relying on the nonparametric distribution based on only eight
subjects. The tail to the right may be just due to one or two subjects with a
larger central volume.
Otherwise (disregarding too few subjects in this specific example); there is
nothing wrong with a right-tailing uncertainty distribution. In fact, it may
even be expected when uncertainty is high and parameter is restricted to
positive values. You would obtain a similar uncertainty distribution from the
nonmem covmatrix by estimating (typical) central volume on log scale. This
should not change OFV, but will alter the covmatrix.
It is difficult to comment on whether the Vc estimate is unreasonable or not.
If early observations are well predicted by the model, then what amount is
located in central compartment, and what amount is available in the two
peripheral compartment at these early time points? If you do not understand how
the model may describe the observed data you could output these amounts in a
table and investigate disposition at these early time points. NCA
extrapolations to time zero may not agree, but that to me is mostly a
theoretical issue - it would be pointless to measure concentrations at the same
time as a (bolus) dose.
Best regards
Jakob
Quoted reply history
From: [email protected] [mailto:[email protected]] On
Behalf Of Felipe Hurtado
Sent: 23 April 2013 19:57
To: [email protected]
Subject: [NMusers] Right skewness in bootstrap distribution
Dear NONMEM users,
I am modeling some PK data using a linear 3-compartment model, in which drug
concentrations were measured in two of these compartments simultaneously after
i.v. dose. The model fits the data reasonably well, and all parameters seem
reasonable except for V1 (volume of the central compartment, which occurs to be
the dosing compartment). Estimate for V1 is very small, what does not make
sense considering the average dose given and the mean Cp0 calculated by NCA.
This result suggests drug distribution is restricted to plasma, however it was
observed extensive distribution to tissues. IIV for V1 is relatively small
(19.6%, n=8 subjects). The histogram for V1 (nonparametric bootstrap with 100
replicates) shows a right skewed distribution with the presence of a
subpopulation and broad confidence interval (5th percentile tends to zero).
I tried to solve this by fixing V1 to a reasonable value, running the model to
calculate all other parameters, and then changing the initial estimates to
these parameters in order to recalculate V1, but it turns out to the same small
estimate.
Any suggestions will be appreciated! Thanks in advance.
Felipe