From: Rebecca Wrishko <wrishko@unixg.ubc.ca>
Subject: Covariate Models Using Weight
Date: Wed, 17 Nov 1999 11:54:08 -0800
Further to the discussion and suggestions forwarded by Vladimir Piotrovskij and Nick Holford with respect to implementation of a parameter centered by some median/mean weight, does the distribution of the population weights have to be fairly narrow, that is is a narrow range, to use TVCL=Theta(1)+Theta(2)*(wt-70)? I attempted to implement this suggestion for a small (6) pediatric population with a mean weight of 20kg (11.2, 17, 18.7, 22.2, 25, 33) with an ADVAN3 TRANS3 subroutine under default (Method 0) estimation and was unable to obtain a successful execution due to a negative V value. However, if the mean weight was changed to 12 and the NM-TRAN control stream (below) was executed final parameter estimates were obtained. Does the centering for mean weight strategy require a robust population? Also I believe that the estimates of theta(1)-1.09L/hr, theta(3)-4.09L, theta(5)-3.17L are in the units of /12kg . However, when one wishes to translate to TVCL (with units of /kg) must the theta(1) and theta(2) values be added and then divided by weight given in the parenthetical term or mean weight (ie. 1.09+0.145/12 or 1.09+0.145/20)?
$SUBROUTINES ADVAN3 TRANS3; Two Compartment Linear Model of entire
population
$PK
TVCL=THETA(1)+THETA(2)*(WT-12) ; typical clearance normalized for wt
CL=TVCL*(1+ETA(1)) ; mean clearance
TVV=THETA(3)+THETA(4)*(WT-12) ; typical central volume normalized for wt
V=TVV*(1+ETA(2)) ; mean central volume
TVVSS=V+THETA(5)+THETA(6)*(WT-12) ; typical vss normalized for wt
VSS=TVVSS*(1+ETA(3)) ; mean theta 3
Q=THETA(7)
K=CL/V; reparameterization lines
K12=Q/V
K21=Q/(VSS-V)
S1=V
$THETA (0,0.5)
(0,0.01)
(0,0.5)
(0,0.01)
(0,1)
(0,0.01)
(0,3)
$OMEGA .25 .25 .25 ; fifty percent cv
$SIGMA .04 ; twenty percent cv
$ERROR
Y=F*(1+EPS(1)) ; proportional error term
$ESTIMATION MAXEVAL=850 SIGDIGITS=4
$COVARIANCE
Thank you for your assistance
Rebecca
>Rebecca Wrishko
>Division of Clinical Pharmacy
>Faculty of Pharmaceutical Sciences
>University of British Columbia
>Vancouver, British Columbia, Canada
>Email: wrishko@unixg.ubc.ca
Covariate Models Using Weight
Date: Mon, 22 Nov 1999 17:01:29 -0800 (PST)
From: ABoeckmann <alison@c255.ucsf.edu>
Subject: centering
Rebecca Wrishko <wrishko@unixg.ubc.ca> sent the following question:
> does the distribution of the population weights
> have to be fairly narrow, that is is a narrow range, to use
> TVCL=Theta(1)+Theta(2)*(wt-70)? I attempted to implement this suggestion
> for a small (6) pediatric population with a mean weight of 20kg (11.2, 17,
> 18.7, 22.2, 25, 33) with an ADVAN3 TRANS3 subroutine under default (Method
> 0) estimation and was unable to obtain a successful execution due to a
> negative V value. However, if the mean weight was changed to 12 and the
> NM-TRAN control stream (below) was executed final parameter estimates were
> obtained.
Sounds like she had trouble with
TVV=THETA(3)+THETA(4)*(WT-20)
I suggest that she add the NOABORT option to the Estimation record:
$ESTIMATION MAXEVAL=850 SIGDIGITS=4 NOABORT
Explanation:
Early in the Estimation Step, NONMEM makes rather large changes in thetas. If it makes theta 3 relatively small, and theta 4 relatively large, then for some subjects having WT<20 it may happen that TVV<0. There is no reasonable way to tell NONMEM to bound the thetas so that this cannot happen. Instead, we tell NONMEM to use "PRED error recovery". NONMEM will avoid thetas that give rise to the error condition (THETA recovery)
It is not wise to rely on the NOABORT option if the error messages in PRDERR file persist well into the Estimation Step, because this indicates that the true minimum may lie close to a region in theta space that NONMEM is prevented from visiting. But if the error message appears only once, early in the Estimation Step, NOABORT is a legitimate way of bounding a function of thetas.
She says that when "WT-12" was used, no set of thetas that NONMEM tried gave rise to negative TVV, but the problem is that V was not truly centered. Similar remarks apply to the model for CL.
For more information, see Users Guide Part IV, IV. G (p. 51-52). Note that the "EXIT" statement is effectively coming from PREDPP rather than from her own code, but the effect of NOABORT is the same.
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Other thread subtopics:
Covariate Models Using Weight (Allometric Scaling)
Covariate Models Using CrCL
Predefined Models vs. "Context-Sensitive" Emperical Models