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Re: M3 method - WRES, and CWRES

From: Matthew Fidler <matthew.fidler>
Date: Sat, 5 Sep 2020 10:17:53 -0500

Thank you Bob,

The NPDE 2.0 manual discusses the methods that NPDE uses to handle BLQ,
including replacing values with pred, ipred, or lloq, or simulating from a
uniform random value while calculating the NPDE (cdf method). The NONMEM
manual doesn't mention the method used. My guess is the cdf method.

I realize that no one has answered Mu'taz's question.

As far as if the CWRES is appropriate for BLQ data, the CWRES method uses
the FOCEi approximation to calculate residuals. However with M3/M4 and
other methods the likelihood for these points is not the FOCEi objective
function but the M3/M4 likelihood so anything you do here with CWRES
doesn't follow or add to the likelihood observed during minimization.
Therefore in my opinion, there will be bias of some sort here.


Best Regards,

Matt.

On Thu, Sep 3, 2020 at 3:06 PM Bauer, Robert <Robert.Bauer
wrote:

> Matt:
>
> The NPDE and NPD systems in NONMEM are described in the nm744.pdf manual =
(
> https://nonmem.iconplc.com/nonmem744 ), pages 70-75, and follow along the
> work of Comet, Brendel, Ngyuen, Mentre, etc. The NPDE R package is not
> used within NONMEM.
>
>
>
>
>
> Robert J. Bauer, Ph.D.
>
> Senior Director
>
> Pharmacometrics R&D
>
> ICON Early Phase
>
> 820 W. Diamond Avenue
>
> Suite 100
>
> Gaithersburg, MD 20878
>
> Office: (215) 616-6428
>
> Mobile: (925) 286-0769
>
> Robert.Bauer
>
> www.iconplc.com
>
>
>
> *From:* owner-nmusers
> Behalf Of *Matthew Fidler
> *Sent:* Thursday, September 3, 2020 6:08 AM
> *To:* Jeroen Elassaiss-Schaap (PD-value B.V.) <jeroen
> *Cc:* Bill Denney <wdenney
> jaber038
> *Subject:* Re: [NMusers] M3 method - WRES, and CWRES
>
>
>
> Hi everyone,
>
>
>
> As an aside, nlmixr's upcoming release (that supports censoring) simulate=
s
> a value using a truncated normal based on the ipred, variance at that poi=
nt
> and the censoring column to produce an observation. This observation is
> used to calculate RES, WRES, CWRES. It is flagged so you can see which
> values use this approach. In theory, since this is simulated from the
> IPRED/truncated the CWRES would be likely follow the distribution closer.
>
>
>
> I'm unsure if the new NONMEM uses this approach.
>
>
>
> Another question from my end is the NPDE: There are many methods to
> handle BLQ values with NPDE R package, does anyone know which NONMEM uses=
?
> Or do you need to use the NPDE package to get these values from NONMEM?
>
>
>
> Matt.
>
>
>
>
>
>
>
> On Wed, Sep 2, 2020 at 2:09 AM Jeroen Elassaiss-Schaap (PD-value B.V.) <
> jeroen
>
> Hi Mutaz, Bill,
>
> It might be useful to use NPDEs, as discussed in
> https://www.cognigen.com/nmusers/2019-February/7376.html; the whole
> thread is worthwhile reading. NPDEs can be calculated also for BQL values=
.
>
> Bill -thanks for pointing to excellent post of Matt! I would take as most
> important point that CWRES for non-BQL values, calculated with a model wi=
th
> influential BQL, are biased because the influence of the BQL values is no=
t
> accounted for. (if a certain prediction for a measurable concentration is
> changed by 10% because of the M3 method, that will turn up as a similar
> bias in CWRES). The NPDEs as referenced to in the above discussion
> (Nguyen2012 JPKPD 0.1007/s10928-012-9264-2) do not suffer from that
> drawback as one can see the complete profile (cf Fig 8 of Nguyen2012).
>
> Hope this helps,
>
> Jeroen
>
> http://pd-value.com
>
> jeroen
>
>
>
> +31 6 23118438
>
> -- More value out of your data!
>
> On 2/9/20 2:32 am, Bill Denney wrote:
>
> Hi Mutaz,
>
>
>
> Matt Hutmacher described it well here:
> https://www.cognigen.com/nmusers/2010-April/2448.html
>
>
>
> A very brief summary of his excellent post is that subjects with a
> combination of censored (BLQ) an uncensored (above the LLOQ and below the
> ULOQ) will be biased in their reporting of CWRES because you cannot
> calculate CWRES for BLQ values. (I say this before looking up what MDVRE=
S
> does.)
>
>
>
> My guess that Bob or someone else can confirm is that the bias is
> anticipated to be relatively small compared to the value of being able to
> compare CWRES values the other observations for a subject. It does not
> definitively mean that the results are unbiased (see Matt’s Tmax =
example),
> but generally, the CWRES values previously omitted are more useful than
> excluding them from calculation.
>
>
>
> Thanks,
>
>
>
> Bill
>
>
>
> *From:* owner-nmusers
> Behalf Of *Mu'taz Jaber
> *Sent:* Tuesday, September 1, 2020 7:25 PM
> *To:* nmusers
> *Subject:* [NMusers] M3 method - WRES, and CWRES
>
>
>
> All,
>
>
>
> Back in April 2010, Sebastian Bihorel and Martin Bergstrand initiated a
> discussion regarding using the M3 and M4 methods for handling BQL data an=
d
> how it seemed to be a bug that NONMEM wouldn't compute WRES for the entir=
e
> set of subject data records whenever a BQL was included (
> https://www.cognigen.com/nmusers/2010-April/2445.html). Tom Ludden
> responded with the following post (
> https://www.cognigen.com/nmusers/2010-April/2447.html):
>
>
>
> This issue was discussed with Stuart Beal. He believed that weighted
>
> residuals would be incorrect for an individual that had both continuous
>
> dependent variables and a likelihood in the calculation of their
>
> contribution to the objective function value, as is the case with his M3
>
> or M4 BQL methods The code for both RES and WRES are intentionally
>
> bypassed in these cases.
>
>
>
> Since then, we now have easy functionality with the F_FLAG=1 condition =
of
> the M3/M4 code in $ERROR to tack on MDVRES=1 that allows the calculatio=
n of
> WRES and CWRES to be available in output tables.
>
>
>
> My questions are: Is Stuart Beal's original concern still valid? Do thes=
e
> NONMEM updates give us appropriate WRES and CWRES for plotting purposes f=
or
> individuals whose records contain BQL data?
>
>
>
> Thank you,
>
>
>
> Mutaz Jaber
>
> PhD student
>
> University of Minnesota
>
>
>
> -------------------------------------------------------
>
> *Mutaz M. Jaber, PharmD.*
>
> PhD student, Pharmacometrics
>
> Experimental and Clinical Pharmacology
>
> University of Minnesota
>
> 717 Delaware St SE; Room 468
>
> Minneapolis, MN 55414
>
> Email: jaber038
>
> Phone: +1 651-706-5202
>
>
>
> *~ Stay curious*
>
>
>
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Received on Sat Sep 05 2020 - 11:17:53 EDT

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