RE: Is it reasonable to add covarite to PD parameters kin or kout?
Li,
It's worth pointing out that the typical IDR formulation assumes proportional
effect on response. That is, if the drug effect is inhibition of synthesis
(e.g Imax=0.5), a subject with baseline 100 will go to 50 and a subject with
baseline 1000 will go to 500. If your data is suggesting that a subject with
baseline 100 goes to 50 and a subject with baseline 1000 goes to 950, the
proportional response formulation is probably a mismatch.
Introduction of baseline as a covariate (in this case, with a large negative
coefficient?) would align the model with data, but you may instead look at
parameterizing the drug effect component of the model differently.
Warm Regards,
Mike
Quoted reply history
From: [email protected] [mailto:[email protected]] On
Behalf Of Mats Karlsson
Sent: Tuesday, July 28, 2015 3:15 AM
To: Peiming Ma; Mark Sale; Zhao,Li; [email protected]
Subject: [NMusers] RE: Is it reasonable to add covarite to PD parameters kin or
kout?
Hi,
There are both pros and cons of using baseline observations as a covariate. We
presented four different options for how to handle baseline and investigated
estimation properties in the paper below. What we didn't look at, because it is
a very bad idea, is to use an baseline observation both as a covariate and
dependent variable.
Approaches to handling pharmacodynamic baseline responses.
Dansirikul C, Silber HE, Karlsson MO.
J Pharmacokinet Pharmacodyn. 2008 Jun;35(3):269-83.
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Faculty of Pharmacy
Uppsala University
Box 591
75124 Uppsala
Phone: +46 18 4714105
Fax + 46 18 4714003
http://www.farmbio.uu.se/research/researchgroups/pharmacometrics/
From: [email protected]<mailto:[email protected]>
[mailto:[email protected]] On Behalf Of Peiming Ma
Sent: Tuesday, July 28, 2015 3:31 AM
To: Mark Sale; Zhao,Li; [email protected]<mailto:[email protected]>
Subject: [NMusers] RE: Is it reasonable to add covarite to PD parameters kin or
kout?
Dear Mark and Li,
I think there is nothing wrong with using baseline as a covariate. Baseline
observations contain more information than just some pre-treatment observations
and thus have a lot of explanatory power; this is the reason they appear
significant more often than not. Comparisons after treatments should try to use
all information before treatments (thus including baselines).
Statisticians habitually use baselines as covariates in their ANCOVA models for
obviously good reasons.
Regards,
Peiming
From: [email protected]<mailto:[email protected]>
[mailto:[email protected]] On Behalf Of Mark Sale
Sent: Tuesday, July 28, 2015 3:34 AM
To: Zhao,Li; [email protected]<mailto:[email protected]>
Subject: [NMusers] RE: Is it reasonable to add covarite to PD parameters kin or
kout?
Li,
I'm going to go out on a limb (since I haven't seen your data or understand the
biology) and suggest that the baseline value is not a covariate, but is just
another observation (presumably with drug concentration = 0). The baseline
value is sort of by definition a function of kin. So, you might look for
predictors of Kin (age? Disease stage?) rather than using the observed value to
predict the parameters (which then predict the observed value). Also note that
covariates are, by definition, measured without error, and a baseline value is
likely measure with error (the same error as any other observation?).
Mark
From: [email protected]<mailto:[email protected]>
[mailto:[email protected]] On Behalf Of Zhao,Li
Sent: Monday, July 27, 2015 2:39 PM
To: [email protected]<mailto:[email protected]>
Subject: [NMusers] Is it reasonable to add covarite to PD parameters kin or
kout?
Dear NMusers,
Right now I am doing covarite analysis for an indirect response model.
I tested a few potential covarites and found it's STATISTICALLY significant if
I add observed baseline value to kin.
But I am not sure if it makes sense to add the baseline value as a covarite to
kin.
Could you please help me if you have had similar experiences before?
Thank you very much!