Nicolas,
In this case I would not spend too much time on the VPC (hope Nick is
not reading this e-mail :) ). Yes, VPC is a quick and convenient way to
check how good the model describes inter-subject and intra-subject
variability, but there are other ways to assess the same: scatter plot
matrix of random effects(should not show any strong ETA-ETA correlations
unless they are specified in the model), shrinkage of random effects and
residual error(should not be too high), QQ-plots of random effects
versus normal distributions (should indicate approximately normal
distribution and no obvious outliers). If those plots are fine, one can
skip VPC or any other xPC, especially in this case when even
applicability of VPC depends on the assumptions (we need to assume that
dosing scheme was independent of PK which is unlikely to be the case
here: subjects with higher CL are likely to get higher doses in this
design).
Thanks
Leonid
--------------------------------------
Leonid Gibiansky, Ph.D.
President, QuantPharm LLC
web: www.quantpharm.com
e-mail: LGibiansky at quantpharm.com
tel: (301) 767 5566
SIMON Nicolas wrote:
Hi Leonid,
Thanks for your help.
The dataset came from anaesthesia where alfentanyl was delivered depending on
the duration of the surgery and the effect required. The first point depended
of the surgeon ability and the latest of the anaesthesiologist feeling...
Thus I do not see a convenient way to include the dose-adjustment algorithm for the simulation even if I fully agree with your suggestion. Have you an idea?
Best regards
Nicolas
-----Message d'origine-----
De : Leonid Gibiansky [mailto:[email protected]]
Envoyé : mercredi 25 février 2009 20:59
À : SIMON Nicolas
Cc : [email protected]
Objet : [SPAM-APHM] Re: [NMusers] VPC, NPC or PPC?
Importance : Faible
Nicolas
I do not know your design, but usually, when you have as many doses as
patients, it means that the dose is individualized and controlled by the
PK or by the PD effect (e.g., dose up to certain concentration level or
up to a certain sedation level). In this case, one has to be careful
with any type of predictive check unless your simulation algorithm
includes the dose-adjustment scheme used in the actual study. If
simulations do not include the same dose adjustment algorithm as the
actual study, you may have apparent discrepancy of your simulation
results and observed data even if the model is perfect.
On the other hand, if indeed the trial was concentration or effect
controlled, you may include the same dose adjustment scheme into the
simulations, and then use VPC for the entire study.
If you provide more details of the design, it would be easier to come up
with some reasonable VPC algorithm.
PPC can be conducted using nonmem PRIOR subroutine (see Nonmem manual)
with priors for population parameters fixed at final estimates, and
variability of the population parameters fixed at SE of the final model.
Thanks
Leonid
--------------------------------------
Leonid Gibiansky, Ph.D.
President, QuantPharm LLC
web: www.quantpharm.com
e-mail: LGibiansky at quantpharm.com
tel: (301) 767 5566
SIMON Nicolas wrote:
Hi All,
We have a dataset with as many dosing (amount and length of infusion) as
patients. Once the final model was defined, I have performed a vpc.
However, because the dosing are very different between patients, is it
relevant to perform vpc or shall we compute npc or ppc?
Can somebody explain the basic difference between vpc, npc and ppc and
when shall we used one or the other?
Last point, how to obtain ppc?
Best regards
Nicolas
Professeur à la Faculté de Médecine de Marseille
Laboratoire de Pharmacologie Médicale et Clinique
27 Bd Jean Moulin
13385 Marseille cedex
Tél 0491387893 (Hôpital)
Tél 0491324456 (Faculté)
Fax 0491256526
