RE: [NMusers] pcVPC or NPDE

From: Martin Bergstrand <martin.bergstrand_at_farmbio.uu.se>
Date: Mon, 14 Sep 2015 13:42:29 +0000

Dear Chenyan and Devin,

Chenyan: Nice of you quote me ;) I still stand by the old quote. In my opinion the advantage with the pcVPC is that it is easy to diagnose if the model accurately predicts both the central trend as well as the variability of the data. The NPDEs on the other hand usually makes for a faster diagnostic that do not require any binning of the data for a rough interpretation. For you own interpretation I recommend you use both types of diagnostics (possibly with different x-axis variables, time, dose etc.) and for a publication you should use whatever you think will be easiest for the audience to interpret.

Devin: The posterior predictive check (PPC) you suggest will only be appropriate if you have a model that also predicts the dose alteration decisions (TDM). With TDM dosing a PPC with the actual dosing history will result in an over prediction of the variability just like VPCs has been demonstrated to do.

Bergstrand M, Hooker AC, Wallin JE, Karlsson MO. Prediction-corrected visual predictive checks for diagnosing nonlinear mixed-effects models. AAPS J. 2011 Jun;13(2):143-51. doi: 10.1208/s12248-011-9255-z.

Best regards,
Martin

From: owner-nmusers_at_globomaxnm.com [mailto:owner-nmusers_at_globomaxnm.com] On Behalf Of Devin Pastoor
Sent: den 11 september 2015 16:46
To: ZhaoChenyan; nmusers_at_globomaxnm.com
Cc: zjiao_at_fudan.edu.cn
Subject: Re: [NMusers] pcVPC or NPDE

Dear Chenyan,

Appropriateness is largely a matter of what the ultimate purpose of the model is, and neither metric will be 'better' in all cases. Extrapolating into a new population may require different evaluation diagnostics than using a model to optimize the dose the observed population.

Given you only have trough samples, using a posterior predictive check on trough levels or equivalence criteria such as proposed in:

1.
Jadhav, P. R. & Gobburu, J. V. S. A new equivalence based metric for predictive check to qualify mixed-effects models. AAPS J 7, E523–E531 (2005).

would likely work well.

Devin Pastoor
Clinical Research Scientist, PhD student
Center for Translational Medicine
University of Maryland, School of Pharmacy

On Fri, Sep 11, 2015 at 10:38 AM ZhaoChenyan <zhaochenyanvictory_at_hotmail.com<mailto:zhaochenyanvictory_at_hotmail.com>> wrote:
Dear all:

I'm now having a set of TDM data, only troughs (C0 ) available.
I intend to evaluated the appropriateness of the constructed model.
My question is whether to use pcVPC or NPDE as a diagnostic tool in such a case?
Which one is better?
Or to use them both, as suggested by Bergstrand et al.: "The best practice most likely lies in using a wide toolbox of diagnostics, rather than one single universal test to decide whether a model is fit for purpose or not."




Thank you in advance.



Yours,

Chenyan Zhao

Email: zhaochenyanvictory_at_hotmail.com<http://hotmail.com>

Mobile: +86 13917430219


Received on Mon Sep 14 2015 - 09:42:29 EDT

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