Dear NMusers,
modelling a 2-compartmet model parameterized by CL, V1, VSS and Q, I got to a problem with which I don’t know how to deal with: After choosing my structural and statistic model (combined residual error model) I estimated the covariance matrix by including an OMEGA-BLOCK(4), which reduced the OFV by 15. The correlations between the parameters were all estimated to be minor (< 0.8). But when I model with a BLOCK(2) on VSS and V1, which I would expect to be positively correlated, the correlation is estimated to be -0.99. Additionally, the inclusion of BLOCK(2) does not significantly improve the OFV.
So does it, after all, still make sense to include the BLOCK(2)?
Generally, at which step of model-building would you recommend to test for parameter correlation?
Thanking you in advance,
Hauke
-----------------------------
Hauke Rühs
Apotheker
Pharmazeutisches Institut
- Klinische Pharmazie -
An der Immenburg 4
53121 Bonn
Tel: + 49-(0)228 73-5781
Fax: + 49-(0)228 73-9757
www.klinische-pharmazie.info
OMEGA-Block
Hello Hauke,
as always for these specific questions you need to provide us with the relevant
portions of your control stream and of your output.
Thanks for participating,
Joachim
_________________________________
AstraZeneca R&D Charnwood
Clin. Pharmacology and DMPK
Bakewell Road
Loughborough, LE11 5RH
Tel: +44 1509 644035
[email protected]
--------------------------------------------------------------------------
AstraZeneca UK Limited is a company incorporated in England and Wales with
registered number: 03674842 and a registered office at 15 Stanhope Gate, London
W1K 1LN.
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Quoted reply history
-----Original Message-----
From: [email protected]
[mailto:[email protected]]on Behalf Of Hauke Rühs
Sent: 03 August 2009 15:07
To: [email protected]
Subject: [NMusers] OMEGA-Block
Dear NMusers,
modelling a 2-compartmet model parameterized by CL, V1, VSS and Q, I got
to a problem with which I don’t know how to deal with: After choosing my
structural and statistic model (combined residual error model) I estimated
the covariance matrix by including an OMEGA-BLOCK(4), which reduced the
OFV by 15. The correlations between the parameters were all estimated to
be minor (< 0.8). But when I model with a BLOCK(2) on VSS and V1, which I
would expect to be positively correlated, the correlation is estimated to
be -0.99. Additionally, the inclusion of BLOCK(2) does not significantly
improve the OFV.
So does it, after all, still make sense to include the BLOCK(2)?
Generally, at which step of model-building would you recommend to test for
parameter correlation?
Thanking you in advance,
Hauke
-----------------------------
Hauke Rühs
Apotheker
Pharmazeutisches Institut
- Klinische Pharmazie -
An der Immenburg 4
53121 Bonn
Tel: + 49-(0)228 73-5781
Fax: + 49-(0)228 73-9757
www.klinische-pharmazie.info
Hauke
Several comments:
It is better to parametrized the model in terms of CL, V1, Q, V2. If you believe that VSS is the derived parameters (VSS=V1+V2), then VSS parameterization introduced additional correlation that you do not need.
Usually, random effects on V2 and Q are not defined properly unless you have a very rich data. I would start with the model that has only random effects on CL and V1, then add random effect on V2 or Q (not both!), and only then try to put all effects together. In my experience, random effect on Q could be helpful for rich sampling, but it is unusual to see a dataset where you need both V2 and Q etas. Based on your results (absolute correlation of V1 and VSS) I would guess that random effect on V2 is not needed at all.
One of the helpful diagnostics is to look on correlation of random effect for the problem where this correlation is not explicitly included. If the correlation is real, you will see it on the scatter plot matrix of random effect.
Helpful diagnostic is the OMEGA value. If inclusion of correlations substantially increases variance estimates, you may have an over-parametrized model where extra correlation makes the model less stable.
Very helpful diagnostic is to compare models (with and without correlations, or with and without extra random effect) by looking on IPRED vs IPRED and PRED vs PRED plots of models under investigation. If they show perfect correlation (coincide with the unit line) you may go with the simplest model (assuming other diagnostics do not tell you otherwise).
Thanks
Leonid
--------------------------------------
Leonid Gibiansky, Ph.D.
President, QuantPharm LLC
web: www.quantpharm.com
e-mail: LGibiansky at quantpharm.com
tel: (301) 767 5566
Hauke Rühs wrote:
> Dear NMusers,
>
> modelling a 2-compartmet model parameterized by CL, V1, VSS and Q, I got to a problem with which I don’t know how to deal with: After choosing my structural and statistic model (combined residual error model) I estimated the covariance matrix by including an OMEGA-BLOCK(4), which reduced the OFV by 15. The correlations between the parameters were all estimated to be minor (< 0.8). But when I model with a BLOCK(2) on VSS and V1, which I would expect to be positively correlated, the correlation is estimated to be -0.99. Additionally, the inclusion of BLOCK(2) does not significantly improve the OFV.
>
> So does it, after all, still make sense to include the BLOCK(2)?
>
> Generally, at which step of model-building would you recommend to test for parameter correlation?
>
> Thanking you in advance,
>
> Hauke
>
> -----------------------------
> Hauke Rühs
>
> Apotheker
> Pharmazeutisches Institut
> - Klinische Pharmazie -
> An der Immenburg 4
>
> 53121 Bonn
>
> Tel: + 49-(0)228 73-5781
> Fax: + 49-(0)228 73-9757
>
> www.klinische-pharmazie.info
Dear Hauke,
thanks for including portions of your control stream and output. Leonid
explained to you the rationale of preferring V1 and V2 over V1 and VSS.
I personally (not a company policy) routinely would use all four etas the way
you did, but with a full set of covariates. I would also take out some of the
correlation by allometricallly (by a size covariate) scaling all volumes and
clearances according to the Holford paradigm (see NMusers on 3/4 rule). A
further trick to make it all work is to logarithmically transform all
concentrations as recommended by Mats Karlsson.
I go through all this trouble in order to capture "all" between patient
variability and to prevent it from spilling over into unexplained (residual)
variability.
I am not bothered too much by warnings and refused covariance steps. I verify
my pivotal models with bootstraps. When it comes to simulations with your final
(validated) model you will reap the fruits of your labor.
Hope that is of some use to you,
Joachim
_________________________________
AstraZeneca R&D Charnwood
Clin. Pharmacology and DMPK
Bakewell Road
Loughborough, LE11 5RH
Tel: +44 1509 644035
[email protected]
--------------------------------------------------------------------------
AstraZeneca UK Limited is a company incorporated in England and Wales with
registered number: 03674842 and a registered office at 15 Stanhope Gate, London
W1K 1LN.
Confidentiality Notice: This message is private and may contain confidential,
proprietary and legally privileged information. If you have received this
message in error, please notify us and remove it from your system and note that
you must not copy, distribute or take any action in reliance on it. Any
unauthorised use or disclosure of the contents of this message is not permitted
and may be unlawful.
Disclaimer: Email messages may be subject to delays, interception, non-delivery
and unauthorised alterations. Therefore, information expressed in this message
is not given or endorsed by AstraZeneca UK Limited unless otherwise notified by
an authorised representative independent of this message. No contractual
relationship is created by this message by any person unless specifically
indicated by agreement in writing other than email.
Monitoring: AstraZeneca UK Limited may monitor email traffic data and content
for the purposes of the prevention and detection of crime, ensuring the
security of our computer systems and checking Compliance with our Code of
Conduct and Policies.
Quoted reply history
-----Original Message-----
From: [email protected]
[mailto:[email protected]]on Behalf Of Hauke Rühs
Sent: 03 August 2009 17:06
To: [email protected]
Subject: Re: [NMusers] OMEGA-Block
Dear NMusers,
thank you for your responses. I parameterized the model by VSS, because
the estimation of the parameter became much better, in terms of
varability, compared to parameterization by V1 and V2.
This is the excerpt from my control stream and output file:
$PK
CL = THETA(1) * EXP(ETA(1))
Q = THETA(2) * EXP(ETA(2))
V1 = THETA(3)* EXP(ETA(3))
VSS = THETA(4) * EXP(ETA(4))
V2=VSS-V1
$OMEGA
0.1 ; OMCL
0.5 ;OMQ
$OMEGA BLOCK(2)
0.05 ;OMV1
0.01 0.05 ;OMVSS
OMEGA - COV MATRIX FOR RANDOM EFFECTS - ETAS ********
ETA1 ETA2 ETA3 ETA4
ETA1
+ 4.08E-02
ETA2
+ 0.00E+00 4.56E-01
ETA3
+ 0.00E+00 0.00E+00 2.62E-01
ETA4
+ 0.00E+00 0.00E+00 -4.34E-02 7.20E-03
Best regards
Hauke
Am 03.08.2009, 16:37 Uhr, schrieb Grevel, Joachim
<[email protected]>:
> Hello Hauke,
>
> as always for these specific questions you need to provide us with the
> relevant portions of your control stream and of your output.
>
> Thanks for participating,
>
> Joachim
> _________________________________
> AstraZeneca R&D Charnwood
> Clin. Pharmacology and DMPK
> Bakewell Road
> Loughborough, LE11 5RH
> Tel: +44 1509 644035
> [email protected]
>
>
>
> --------------------------------------------------------------------------
> AstraZeneca UK Limited is a company incorporated in England and Wales
> with registered number: 03674842 and a registered office at 15 Stanhope
> Gate, London W1K 1LN.
> Confidentiality Notice: This message is private and may contain
> confidential, proprietary and legally privileged information. If you
> have received this message in error, please notify us and remove it from
> your system and note that you must not copy, distribute or take any
> action in reliance on it. Any unauthorised use or disclosure of the
> contents of this message is not permitted and may be unlawful.
> Disclaimer: Email messages may be subject to delays, interception,
> non-delivery and unauthorised alterations. Therefore, information
> expressed in this message is not given or endorsed by AstraZeneca UK
> Limited unless otherwise notified by an authorised representative
> independent of this message. No contractual relationship is created by
> this message by any person unless specifically indicated by agreement in
> writing other than email.
> Monitoring: AstraZeneca UK Limited may monitor email traffic data and
> content for the purposes of the prevention and detection of crime,
> ensuring the security of our computer systems and checking Compliance
> with our Code of Conduct and Policies.
> -----Original Message-----
> From: [email protected]
> [mailto:[email protected]]on Behalf Of Hauke Rühs
> Sent: 03 August 2009 15:07
> To: [email protected]
> Subject: [NMusers] OMEGA-Block
>
>
>
> Dear NMusers,
>
> modelling a 2-compartmet model parameterized by CL, V1, VSS and Q, I got
> to a problem with which I don’t know how to deal with: After choosing my
> structural and statistic model (combined residual error model) I
> estimated
> the covariance matrix by including an OMEGA-BLOCK(4), which reduced the
> OFV by 15. The correlations between the parameters were all estimated to
> be minor (< 0.8). But when I model with a BLOCK(2) on VSS and V1, which I
> would expect to be positively correlated, the correlation is estimated to
> be -0.99. Additionally, the inclusion of BLOCK(2) does not significantly
> improve the OFV.
> So does it, after all, still make sense to include the BLOCK(2)?
> Generally, at which step of model-building would you recommend to test
> for
> parameter correlation?
>
> Thanking you in advance,
>
> Hauke
>
> -----------------------------
> Hauke Rühs
>
> Apotheker
> Pharmazeutisches Institut
> - Klinische Pharmazie -
> An der Immenburg 4
>
> 53121 Bonn
>
> Tel: + 49-(0)228 73-5781
> Fax: + 49-(0)228 73-9757
>
> www.klinische-pharmazie.info
>
>
Dear Samer,
I parameterized the model by CL, Q , V1 and V2 and by CL,Q, V1 and Vss respectively. Correlation was not included at this time. The latter model lead to a lower OFV (~5), which is why I choosed to go on with this paramerization. Both models show correlation between the volumes V1 and V2 or V1 and VSS respectively in the scatter plot matrix of random effect, when no correlation is included into the model. So is it better to go with parameterization CL, Q, V1 and V2, even though I have correlation in both cases?
Hauke
Am 03.08.2009, 18:42 Uhr, schrieb Samer Mouksassi < [email protected] >:
> What do you mean by much better ?
> OFV ? BSV % etc..
> Can you please in clude a brief comparison on both cases
>
> Samer
>
Quoted reply history
> -----Original Message-----
>
> From: [email protected] [ mailto: [email protected] ] On Behalf Of Hauke Rühs
>
> Sent: 2009-08-03 12:06
> To: [email protected]
> Subject: Re: [NMusers] OMEGA-Block
>
> Dear NMusers,
>
> thank you for your responses. I parameterized the model by VSS, because
> the estimation of the parameter became much better, in terms of
> varability, compared to parameterization by V1 and V2.
> This is the excerpt from my control stream and output file:
>
> $PK
> CL = THETA(1) * EXP(ETA(1))
> Q = THETA(2) * EXP(ETA(2))
> V1 = THETA(3)* EXP(ETA(3))
> VSS = THETA(4) * EXP(ETA(4))
> V2=VSS-V1
>
> $OMEGA
> 0.1 ; OMCL
> 0.5 ;OMQ
> $OMEGA BLOCK(2)
> 0.05 ;OMV1
> 0.01 0.05 ;OMVSS
>
> OMEGA - COV MATRIX FOR RANDOM EFFECTS - ETAS ********
>
> ETA1 ETA2 ETA3 ETA4
>
> ETA1
> + 4.08E-02
>
> ETA2
> + 0.00E+00 4.56E-01
>
> ETA3
> + 0.00E+00 0.00E+00 2.62E-01
>
> ETA4
> + 0.00E+00 0.00E+00 -4.34E-02 7.20E-03
>
> Best regards
>
> Hauke
>
> Am 03.08.2009, 16:37 Uhr, schrieb Grevel, Joachim
> <[email protected]>:
>
> > Hello Hauke,
> >
> > as always for these specific questions you need to provide us with the
> > relevant portions of your control stream and of your output.
> >
> > Thanks for participating,
> >
> > Joachim
> > _________________________________
> > AstraZeneca R&D Charnwood
> > Clin. Pharmacology and DMPK
> > Bakewell Road
> > Loughborough, LE11 5RH
> > Tel: +44 1509 644035
> > [email protected]
> >
> > --------------------------------------------------------------------------
> > AstraZeneca UK Limited is a company incorporated in England and Wales
> > with registered number: 03674842 and a registered office at 15 Stanhope
> > Gate, London W1K 1LN.
> > Confidentiality Notice: This message is private and may contain
> > confidential, proprietary and legally privileged information. If you
> > have received this message in error, please notify us and remove it from
> > your system and note that you must not copy, distribute or take any
> > action in reliance on it. Any unauthorised use or disclosure of the
> > contents of this message is not permitted and may be unlawful.
> > Disclaimer: Email messages may be subject to delays, interception,
> > non-delivery and unauthorised alterations. Therefore, information
> > expressed in this message is not given or endorsed by AstraZeneca UK
> > Limited unless otherwise notified by an authorised representative
> > independent of this message. No contractual relationship is created by
> > this message by any person unless specifically indicated by agreement in
> > writing other than email.
> > Monitoring: AstraZeneca UK Limited may monitor email traffic data and
> > content for the purposes of the prevention and detection of crime,
> > ensuring the security of our computer systems and checking Compliance
> > with our Code of Conduct and Policies.
> > -----Original Message-----
> > From: [email protected]
> > [mailto:[email protected]]on Behalf Of Hauke Rühs
> > Sent: 03 August 2009 15:07
> > To: [email protected]
> > Subject: [NMusers] OMEGA-Block
> >
> > Dear NMusers,
> >
> > modelling a 2-compartmet model parameterized by CL, V1, VSS and Q, I got
> > to a problem with which I don't know how to deal with: After choosing my
> > structural and statistic model (combined residual error model) I
> > estimated
> > the covariance matrix by including an OMEGA-BLOCK(4), which reduced the
> > OFV by 15. The correlations between the parameters were all estimated to
> >
> > be minor (< 0.8). But when I model with a BLOCK(2) on VSS and V1, which I would expect to be positively correlated, the correlation is estimated to
> >
> > be -0.99. Additionally, the inclusion of BLOCK(2) does not significantly
> > improve the OFV.
> > So does it, after all, still make sense to include the BLOCK(2)?
> > Generally, at which step of model-building would you recommend to test
> > for
> > parameter correlation?
> >
> > Thanking you in advance,
> >
> > Hauke
> >
> > -----------------------------
> > Hauke Rühs
> >
> > Apotheker
> > Pharmazeutisches Institut
> > - Klinische Pharmazie -
> > An der Immenburg 4
> >
> > 53121 Bonn
> >
> > Tel: + 49-(0)228 73-5781
> > Fax: + 49-(0)228 73-9757
> >
> > www.klinische-pharmazie.info
--
Erstellt mit Operas revolutionärem E-Mail-Modul: http://www.opera.com/mail/
Hi Hauke, Joachim,
For a two-compartment linear problem, I would really worry about non-convergence, warnings, and refused covariance step. The problem was discussed to death on this list, and the transcript can be found in the archive, so I will not repeat all the arguments, but the main idea is that non-convergence (especially for this simple problem) may indicate over-parameterization, when the data cannot support the model. Often, too many ETAs are to blame for this.
Objective function difference of 5 is almost negligible. I would go with the more mechanistic model, model with lower variance estimates, model with lower standard errors, model with better diagnostic plots, and disregard OF difference of 5 units.
I am not sure that bootstrap may verify the model for simulations. It may reveal correlation of parameter estimates, provide confidence intervals on the parameter estimates, but I am not sure how it can characterize the predictive power of the model. VPC could be an important test if one plans to use the model for simulations. Extra ETAs (e.g., full OMEGA matrix with ETAs on all parameters) often lead to over-estimation of the actual inter-subject variability, and this can be seen on VPC plots.
Thanks
Leonid
--------------------------------------
Leonid Gibiansky, Ph.D.
President, QuantPharm LLC
web: www.quantpharm.com
e-mail: LGibiansky at quantpharm.com
tel: (301) 767 5566
Grevel, Joachim wrote:
> Dear Hauke,
>
> thanks for including portions of your control stream and output. Leonid explained to you the rationale of preferring V1 and V2 over V1 and VSS. I personally (not a company policy) routinely would use all four etas the way you did, but with a full set of covariates. I would also take out some of the correlation by allometricallly (by a size covariate) scaling all volumes and clearances according to the Holford paradigm (see NMusers on 3/4 rule). A further trick to make it all work is to logarithmically transform all concentrations as recommended by Mats Karlsson. I go through all this trouble in order to capture "all" between patient variability and to prevent it from spilling over into unexplained (residual) variability.
>
> I am not bothered too much by warnings and refused covariance steps. I verify
> my pivotal models with bootstraps. When it comes to simulations with your final
> (validated) model you will reap the fruits of your labor.
>
> Hope that is of some use to you,
>
> Joachim
> _________________________________
> AstraZeneca R&D Charnwood
> Clin. Pharmacology and DMPK
> Bakewell Road
> Loughborough, LE11 5RH
> Tel: +44 1509 644035
> [email protected]
>
> --------------------------------------------------------------------------
> AstraZeneca UK Limited is a company incorporated in England and Wales with
> registered number: 03674842 and a registered office at 15 Stanhope Gate, London
> W1K 1LN.
> Confidentiality Notice: This message is private and may contain confidential,
> proprietary and legally privileged information. If you have received this
> message in error, please notify us and remove it from your system and note that
> you must not copy, distribute or take any action in reliance on it. Any
> unauthorised use or disclosure of the contents of this message is not permitted
> and may be unlawful.
> Disclaimer: Email messages may be subject to delays, interception, non-delivery
> and unauthorised alterations. Therefore, information expressed in this message
> is not given or endorsed by AstraZeneca UK Limited unless otherwise notified by
> an authorised representative independent of this message. No contractual
> relationship is created by this message by any person unless specifically
> indicated by agreement in writing other than email.
> Monitoring: AstraZeneca UK Limited may monitor email traffic data and content
> for the purposes of the prevention and detection of crime, ensuring the
> security of our computer systems and checking Compliance with our Code of
> Conduct and Policies.
Quoted reply history
> -----Original Message-----
> From: [email protected]
> [mailto:[email protected]]on Behalf Of Hauke Rühs
> Sent: 03 August 2009 17:06
> To: [email protected]
> Subject: Re: [NMusers] OMEGA-Block
>
> Dear NMusers,
>
> thank you for your responses. I parameterized the model by VSS, because the estimation of the parameter became much better, in terms of varability, compared to parameterization by V1 and V2.
>
> This is the excerpt from my control stream and output file:
>
> $PK
> CL = THETA(1) * EXP(ETA(1))
> Q = THETA(2) * EXP(ETA(2))
> V1 = THETA(3)* EXP(ETA(3))
> VSS = THETA(4) * EXP(ETA(4))
> V2=VSS-V1
>
> $OMEGA
> 0.1 ; OMCL
> 0.5 ;OMQ
> $OMEGA BLOCK(2)
> 0.05 ;OMV1
> 0.01 0.05 ;OMVSS
>
> OMEGA - COV MATRIX FOR RANDOM EFFECTS - ETAS ********
>
> ETA1 ETA2 ETA3 ETA4
>
> ETA1
> + 4.08E-02
>
> ETA2
> + 0.00E+00 4.56E-01
>
> ETA3
> + 0.00E+00 0.00E+00 2.62E-01
>
> ETA4
> + 0.00E+00 0.00E+00 -4.34E-02 7.20E-03
>
> Best regards
>
> Hauke
>
> Am 03.08.2009, 16:37 Uhr, schrieb Grevel, Joachim < [email protected] >:
>
> > Hello Hauke,
> >
> > as always for these specific questions you need to provide us with the relevant portions of your control stream and of your output.
> >
> > Thanks for participating,
> >
> > Joachim
> > _________________________________
> > AstraZeneca R&D Charnwood
> > Clin. Pharmacology and DMPK
> > Bakewell Road
> > Loughborough, LE11 5RH
> > Tel: +44 1509 644035
> > [email protected]
> >
> > --------------------------------------------------------------------------
> >
> > AstraZeneca UK Limited is a company incorporated in England and Wales with registered number: 03674842 and a registered office at 15 Stanhope Gate, London W1K 1LN. Confidentiality Notice: This message is private and may contain confidential, proprietary and legally privileged information. If you have received this message in error, please notify us and remove it from your system and note that you must not copy, distribute or take any action in reliance on it. Any unauthorised use or disclosure of the contents of this message is not permitted and may be unlawful. Disclaimer: Email messages may be subject to delays, interception, non-delivery and unauthorised alterations. Therefore, information expressed in this message is not given or endorsed by AstraZeneca UK Limited unless otherwise notified by an authorised representative independent of this message. No contractual relationship is created by this message by any person unless specifically indicated by agreement in writing other than email. Monitoring: AstraZeneca UK Limited may monitor email traffic data and content for the purposes of the prevention and detection of crime, ensuring the security of our computer systems and checking Compliance with our Code of Conduct and Policies.
> >
> > -----Original Message-----
> > From: [email protected]
> > [mailto:[email protected]]on Behalf Of Hauke Rühs
> > Sent: 03 August 2009 15:07
> > To: [email protected]
> > Subject: [NMusers] OMEGA-Block
> >
> > Dear NMusers,
> >
> > modelling a 2-compartmet model parameterized by CL, V1, VSS and Q, I got
> > to a problem with which I don’t know how to deal with: After choosing my
> >
> > structural and statistic model (combined residual error model) I estimated
> >
> > the covariance matrix by including an OMEGA-BLOCK(4), which reduced the
> > OFV by 15. The correlations between the parameters were all estimated to
> > be minor (< 0.8). But when I model with a BLOCK(2) on VSS and V1, which I
> > would expect to be positively correlated, the correlation is estimated to
> > be -0.99. Additionally, the inclusion of BLOCK(2) does not significantly
> > improve the OFV.
> > So does it, after all, still make sense to include the BLOCK(2)?
> >
> > Generally, at which step of model-building would you recommend to test for
> >
> > parameter correlation?
> >
> > Thanking you in advance,
> >
> > Hauke
> >
> > -----------------------------
> > Hauke Rühs
> >
> > Apotheker
> > Pharmazeutisches Institut
> > - Klinische Pharmazie -
> > An der Immenburg 4
> >
> > 53121 Bonn
> >
> > Tel: + 49-(0)228 73-5781
> > Fax: + 49-(0)228 73-9757
> >
> > www.klinische-pharmazie.info
Dear Grevel,
could you kindly point out the reference where this statment comes from: "A
further trick to make it all work is to logarithmically transform all
concentrations as recommended by Mats Karlsson."
thanks
Quoted reply history
________________________________
From: "Grevel, Joachim" <[email protected]>
To: [email protected]
Sent: Tuesday, August 4, 2009 3:21:57 AM
Subject: RE: [NMusers] OMEGA-Block
Dear Hauke,
thanks for including portions of your control stream and output. Leonid
explained to you the rationale of preferring V1 and V2 over V1 and VSS.
I personally (not a company policy) routinely would use all four etas the way
you did, but with a full set of covariates. I would also take out some of the
correlation by allometricallly (by a size covariate) scaling all volumes and
clearances according to the Holford paradigm (see NMusers on 3/4 rule). A
further trick to make it all work is to logarithmically transform all
concentrations as recommended by Mats Karlsson.
I go through all this trouble in order to capture "all" between patient
variability and to prevent it from spilling over into unexplained (residual)
variability.
I am not bothered too much by warnings and refused covariance steps. I verify
my pivotal models with bootstraps. When it comes to simulations with your final
(validated) model you will reap the fruits of your labor.
Hope that is of some use to you,
Joachim
_________________________________
AstraZeneca R&D Charnwood
Clin. Pharmacology and DMPK
Bakewell Road
Loughborough, LE11 5RH
Tel: +44 1509 644035
[email protected]
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-----Original Message-----
From: [email protected]
[mailto:[email protected]]on Behalf Of Hauke Rühs
Sent: 03 August 2009 17:06
To: [email protected]
Subject: Re: [NMusers] OMEGA-Block
Dear NMusers,
thank you for your responses. I parameterized the model by VSS, because
the estimation of the parameter became much better, in terms of
varability, compared to parameterization by V1 and V2.
This is the excerpt from my control stream and output file:
$PK
CL = THETA(1) * EXP(ETA(1))
Q = THETA(2) * EXP(ETA(2))
V1 = THETA(3)* EXP(ETA(3))
VSS = THETA(4) * EXP(ETA(4))
V2=VSS-V1
$OMEGA
0.1 ; OMCL
0.5 ;OMQ
$OMEGA BLOCK(2)
0.05 ;OMV1
0.01 0.05 ;OMVSS
OMEGA - COV MATRIX FOR RANDOM EFFECTS - ETAS ********
ETA1 ETA2 ETA3 ETA4
ETA1
+ 4.08E-02
ETA2
+ 0.00E+00 4.56E-01
ETA3
+ 0.00E+00 0.00E+00 2.62E-01
ETA4
+ 0.00E+00 0.00E+00 -4.34E-02 7.20E-03
Best regards
Hauke
Am 03.08.2009, 16:37 Uhr, schrieb Grevel, Joachim
<[email protected]>:
> Hello Hauke,
>
> as always for these specific questions you need to provide us with the
> relevant portions of your control stream and of your output.
>
> Thanks for participating,
>
> Joachim
> _________________________________
> AstraZeneca R&D Charnwood
> Clin. Pharmacology and DMPK
> Bakewell Road
> Loughborough, LE11 5RH
> Tel: +44 1509 644035
> [email protected]
>
>
>
> --------------------------------------------------------------------------
> AstraZeneca UK Limited is a company incorporated in England and Wales
> with registered number: 03674842 and a registered office at 15 Stanhope
> Gate, London W1K 1LN.
> Confidentiality Notice: This message is private and may contain
> confidential, proprietary and legally privileged information. If you
> have received this message in error, please notify us and remove it from
> your system and note that you must not copy, distribute or take any
> action in reliance on it. Any unauthorised use or disclosure of the
> contents of this message is not permitted and may be unlawful.
> Disclaimer: Email messages may be subject to delays, interception,
> non-delivery and unauthorised alterations. Therefore, information
> expressed in this message is not given or endorsed by AstraZeneca UK
> Limited unless otherwise notified by an authorised representative
> independent of this message. No contractual relationship is created by
> this message by any person unless specifically indicated by agreement in
> writing other than email.
> Monitoring: AstraZeneca UK Limited may monitor email traffic data and
> content for the purposes of the prevention and detection of crime,
> ensuring the security of our computer systems and checking Compliance
> with our Code of Conduct and Policies.
> -----Original Message-----
> From: [email protected]
> [mailto:[email protected]]on Behalf Of Hauke Rühs
> Sent: 03 August 2009 15:07
> To: [email protected]
> Subject: [NMusers] OMEGA-Block
>
>
>
> Dear NMusers,
>
> modelling a 2-compartmet model parameterized by CL, V1, VSS and Q, I got
> to a problem with which I don’t know how to deal with: After choosing my
> structural and statistic model (combined residual error model) I
> estimated
> the covariance matrix by including an OMEGA-BLOCK(4), which reduced the
> OFV by 15. The correlations between the parameters were all estimated to
> be minor (< 0.8). But when I model with a BLOCK(2) on VSS and V1, which I
> would expect to be positively correlated, the correlation is estimated to
> be -0.99. Additionally, the inclusion of BLOCK(2) does not significantly
> improve the OFV.
> So does it, after all, still make sense to include the BLOCK(2)?
> Generally, at which step of model-building would you recommend to test
> for
> parameter correlation?
>
> Thanking you in advance,
>
> Hauke
>
> -----------------------------
> Hauke Rühs
>
> Apotheker
> Pharmazeutisches Institut
> - Klinische Pharmazie -
> An der Immenburg 4
>
> 53121 Bonn
>
> Tel: + 49-(0)228 73-5781
> Fax: + 49-(0)228 73-9757
>
> www.klinische-pharmazie.info
>
>