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RE: RES and WRES output with Beal's M3 method

From: Ludden, Thomas <Thomas.Ludden>
Date: Wed, 7 Apr 2010 15:29:48 -0400

Historical perspective.

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.

Tom

-----Original Message-----
From: owner-nmusers
On Behalf Of Sebastien Bihorel
Sent: Wednesday, April 07, 2010 1:57 PM
To: Martin Bergstrand
Cc: 'Sebastien Bihorel'; nmusers
Subject: Re: [NMusers] RES and WRES output with Beal's M3 method

Hi Martin,

Thanks for your reply. I tend to agree with you this should be
considered as a bug.

I tried different options to access to the actual RES and WRES inside
the $ERROR block. The best I could do so far was to access to PRED
values using (COMACT.EQ.1). With this call, I can assign PRED values to
a PPRED variable that I used to compute some residuals PRES (DV-PPRED)
and some weighted residuals PWRES (RES/W) using your defining of W. This

provides some non-zero values for non-BLOQ samples. By checking PRES and

PWRES against RES and WRES for patients without BLOQ samples, it appears

that PWRES is correct as long as I don't include inter-individual
variability in my model (PRES seems to be always correct).

Any idea how the formula for PWRES should be altered?

Sebastien

New code:

$ERROR (ONLY OBSERVATIONS)

;Information needed for BLQF and > BLQF samples
LOQ=5
SIG = THETA(3)

DFLG=0 ;create a dose record flag
IF(AMT.NE.0) DFLG=1
IPRED=F+DFLG
W=IPRED*SIG

IF (COMACT.EQ.1) PPRED=F+DFLG
PRES=DV-PPRED
PWRES=PRES/W

;Computations for samples with DV > LOQ (BLQF=0)
IF (BLQF.LT.0.25) THEN
 F_FLAG=0
 FFLG=0
 IRES=DV-IPRED
 IWRES=IRES/W
 Y=IPRED+W*SIG*EPS(1) ;NOTE: Prediction is a concentration
ENDIF

;Computations for samples with DV <= LOQ (BLQF=1)
IF (BLQF.GE.0.25) THEN
 F_FLAG=1
 FFLG=1
 DUM=(LOQ-IPRED)/(W*SIG)
 IPRED=PHI(DUM)
 Y=IPRED ;NOTE: prediction is a *probability*
ENDIF


Martin Bergstrand wrote:
> Dear Sebastien and NONMEM users,
>
> It is correct that NONMEM doesn't return any RES or WRES for
individuals who
> have at least one observation with F_FLAG=1. It is understandable =
that
> NONMEM can't return residuals for the BQL observations (F_FLAG=1)
since PRED
> is a likelihood in this case and not a prediction (furthermore the
> observation is an interval and can neither be used to calculate a
residual).
> However, I don't understand why it doesn't do so for the observations
for
> which F_FLAG=0? Can this be considered a bug?
>
> You can of course always get out individual residuals (IRES) and
individual
> weighted residuals (IWRES) (below this paragraph you can see my
definition
> of IWRES). What you can do if you really want to get RES and WRES is
to run
> a MAXEVAL=0 run with your final estimates. The BQL data should in =
this
case
> be omitted (or set to a fix value) and all M3 code taken out. Remember
in
> this case that the IRES and IWRES and other EBE dependent variables
will not
> be correct following the MAXEVAL=0 run (i.e. use only the PRED, RES
and WRES
> out of this run and the rest from your original fit with the M3 code).
In
> case you are using the FOCE estimation method you would preferably
want to
> look at conditional weighted residuals (CWRES) rather than WRES.
However I
> have yet not seen any example of a workaround to get these when using
the M3
> method (Obs! CWRES will not be correctly calculated with the =
MAXEVAL=0
> trick).
>
> $ERROR
> IPRED = F
> W = THETA(11) ; SD for additive
> residual error
> ; W = THETA(11) * IPRED ; SD for
proportional
> residual error
> ; W = SQRT(THEATA(11)**2+THETA(12)**2*IPRED**2) ; SD for combined
> residual error
> Y = IPRED + W*EPS(1)
> IRES = DV - IPRED
> IWRES = IRES/W
>
> $SIGMA 1 FIX
>
> If you use Xpose to do your diagnostic plots it can be good to know
that
> Xpose by default omits all rows with WRES=0 (this is done to omit
> information on dosing row from being plotted). You can change this
setting
> in Xpose by using the command inclZeroWRES=TRUE (you should then =
enter
some
> other subset to omit the dose rows e.g. subset="EVID==0").
>
> My favorite type of diagnostics are VPCs (I think I share this with
Prof.
> Nick Holford). VPCs can easily be adopted to handle the presence of
BQL
> data. How to do this with PsN and Xpose is explained in a PAGE poster
from
> 2009
>
(http://www.page-meeting.org/pdf_assets/7002-Poster_PAGE_VPC_090618_fina
l.pd
> f).
>
> Best regards,
>
> Martin Bergstrand, MSc, PhD student
> -----------------------------------------------
> Pharmacometrics Research Group,
> Department of Pharmaceutical Biosciences,
> Uppsala University
> -----------------------------------------------
> martin.bergstrand
> -----------------------------------------------
> Work: +46 18 471 4639
> Mobile: +46 709 994 396
> Fax: +46 18 471 4003
>
>
> -----Original Message-----
> From: owner-nmusers
[mailto:owner-nmusers
> Behalf Of Sebastien Bihorel
> Sent: den 7 april 2010 17:31
> To: nmusers
> Subject: [NMusers] RES and WRES output with Beal's M3 method
>
> Dear NONMEM users,
>
> We have noticed some problems with the table outputs of RES and WRES,
> when we implemented Beal's M3 method as proposed by Ahn and colleagues

> (J Pharmacokinet Pharmacodyn (2008) 35:401-421). While RES and WRES
are
> correctly calculated and reported for patients without BLOQ records,
> these metrics are reported as being 0 for patients with at least one
> BLOQ sample, even for the records that were not flagged as BLOQ. This
> behavior seems to be common to NONMEM 6 and 7.
>
> Does anybody know about an NONMEM option or a workaround that would
> allow the user to access to the actual RES and WRES for the non-BLQ
records?
>
> Any feedback would be greatly appreciated.
>
> Sebastien Bihorel
>
> PS: this is the $ERROR block code we used for a simple proportional RV
model
>
> $ERROR (ONLY OBSERVATIONS)
>
> ;Information needed for BLQF and > BLQF samples
> LOQ=5
> SIG = THETA(3)
>
> DFLG=0 ;create a dose record flag
> IF(AMT.NE.0) DFLG=1
>
> IPRED=F+DFLG
> W=IPRED
>
> ;Computations for samples with DV > LOQ (BLQF=0)
> IF (BLQF.LT.0.25) THEN
> F_FLAG=0
> FFLG=0
> IRES=DV-IPRED
> IWRES=IRES/W
> Y=IPRED+W*SIG*EPS(1) ;NOTE: Prediction is a concentration
> ENDIF
>
> ;Computations for samples with DV <= LOQ (BLQF=1)
> IF (BLQF.GE.0.25) THEN
> F_FLAG=1
> FFLG=1
> DUM=(LOQ-IPRED)/(W*SIG)
> IPRED=PHI(DUM)
> Y=IPRED ;NOTE: prediction is a *probability*
> ENDIF
>
>
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Received on Wed Apr 07 2010 - 15:29:48 EDT

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