VPC appropriateness in complex PK --> reasons for lost messages

1 messages 1 people Latest: Sep 21, 2009
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________________________________ From: [email protected] [mailto:[email protected]] On Behalf Of Martin Bergstrand Sent: Monday, September 21, 2009 12:16 PM To: 'nmusers' Subject: FW: [NMusers] VPC appropriateness in complex PK Dear NMusers, For some reason my last message to NMusers got lost in www-space. Since both Leonid and Nick have responded to my initial message I repost this message so that you can follow the discussion (see email below). In addition to this message I would also like to comment on the messages by Diane, Leonid and Nick. Nick and Leonid: I agree that it would be useful if one could also simulate that adaptive design (e.g. dose adaptations) and show the observations on the non transformed scale. However this will in many cases be very hard since dos adaptations are often done not according to a strict algorithm and/or all information supporting the dose alterations is not available. It is to my experience quite commonly written I study protocols that dose adjustments can be done "by the discretion of the investigator". Diane and Leonid: If I understood the SVPC procedure correctly from Diane's presentation it utilizes a principle similar to that behind Numerical Predictive Check (NPC). Most of all SVPC seem to have a striking similarity to the first version of the prediction discrepancies as described by Metré et al (1). The prediction discrepancies have been further developed into the normalised prediction distribution errors (NPDE) (2). From my experience both NPC and NPDE are useful diagnostic tools but not applicable to data from studies with adaptive dos adjustments (correlation between ETAs and design). What is the unique feature with SVPC that sets it apart from the prediction discrepancies and makes it applicable to studies with adaptive dos adjustments? Nick: Regarding this sentence "The empirical PRED-corrected VPC does not give this kind of support for future use of the PK model under an adaptive design scenario". Why is this? If the PC-VPC can verify that you have an acceptable structure model and unbiased parameter estimates you can then simulate any type of adaptive design scenario. Best regards, Martin 1. Prediction discrepancies for the evaluation of ... Mentré F, Escolano S. JPKPD. 2006 2. Computing normalised prediction distribution errors ... Comets E, Brendel K, Mentré F. CMPB. 2008 _____________________________________________ From: Martin Bergstrand [mailto:[email protected]] Sent: den 20 september 2009 19:32 To: 'Leonid Gibiansky'; 'Nick Holford' Cc: 'Dider Heine'; '[email protected]'; 'Wang, Diane' Subject: RE: [NMusers] VPC appropriateness in complex PK Dear Leonid and Nick, You have both written that there is no simulation based diagnostic that can be applied in the case of adaptive designs (unless you can simulate the adaptations). Below I will try to describe why I think that PC-VPCs can be used under these circumstances. The example that Leonid describe is very similar to one of the example in the abstract about PC-VPCs that I referred to previously (see example 3). With this example we demonstrate that PC-VPCs can be used in the presence of adaptive designs such as TDM. The prediction corrected dependent variable in a PC-VPC is unaffected by changes in independent variables included in the model such as dose and covariate effects. It can be seen as if the median in a PC-VPC represent a typical individual with a typical dose and a typical set of covariates. If we look at a prediction interval for a PC-VPC that represent only the variability that is explained by random effects in the model and nothing that comes from fixed effects (dose, covariates and time). For this reason PC-VPCs can be used also in the cases when we do not know the exact algorithm for the adaptations made (e.g. dose adjustments). In a very simple case where we have linear kinetics, no covariates in the model and no binning across the independent variable on the x-axis (e.g. time) PRED correction will be the same a dose normalization of both the observed and simulated data. However the PRED correction can be more universally applied than a dose normalization. PRED correction does not handle all types of adaptive designs that you could think of. For instance The above described feature of PC-VPCs are one of reasons I find it useful. In the cases with adaptive designs PC-VPCs will in my mind replace traditional VPCs whereas in many other cases it will only be a complement to stratified VPCs to better diagnose the random effect components of a model. More about this can be read in the ACoP abstract: Bergstrand M, Hooker AC, Wallin JE, Karlsson MO. Prediction corrected visual predictive checks http://www.go-acop.org/acop2009/posters ACOP. 2009 http://www.go-acop.org/acop2009/posters ACOP. 2009 . Ps. PRED correction does not handle all types of adaptive designs that you could think of. For instance adaptive censoring of data (i.e. study discontinuation) will not be this easily handled. Kind regards, Martin