RE: Time-varing covariate and renal function as a covariate
Hi Matt and Everyone,
Whether or not "just using weight and CLCR should be enough" depends on whether
you think that people who lost weight because of a drug (the formerly obese)
are physilogically the same (with respect to the drugs in question) as those
who were never obese. Are the formerly-obese maybe even a third group,
different from non-obese and currently-obese?
That said, making a distinction between healthy vs obese is odd. Obesity is a
continuum and there shouldn't be model discontinuity when someone meets some
arbitrary criteria. There shouldn't be choice "obese vs. non-obese", everything
just comes as a smooth function of the covariates. Nature is "smooth" and, if
possible, our models should be too.
Warm regards,
Douglas Eleveld
-----Oorspronkelijk bericht-----
Quoted reply history
Van: [email protected] [mailto:[email protected]] Namens
Matt Hutmacher
Verzonden: September 3, 2013 7:00 PM
Aan: 'Nick Holford'; 'nmusers'
Onderwerp: RE: [NMusers] Time-varing covariate and renal function as a covariate
Hello Nick, Hans
Thanks for the replies and sorry for being so vague. I wanted to get your
opinions about such a scenario without providing information that might "steer"
the dialogue.
Perhaps a hypothetical will help clarify my scientific curiosity. Let's say at
baseline we take measurements of weight (WT), etc. Assume Cockcroft-Gault is
used to predict CLCR. We formulate a model either by Nick's or Hans' method
below to relate WT and CLCR (a function of WT) to CL of the drug. However,
over time, the drug changes WT... in some way the ratio of fat to lean mass is
altered by the drug. Should we expect the same structural relationship to hold
as we would have assumed at baseline (before we knew the drug changes WT)? And
if so, then should we assume the same coefficients (exponents) for CLCR and WT
would hold over time in such a model, such that just adjusting CLCR and WT as
time varying covariates is all that is needed to be predictive? As another
example, let's assume we do a pooled population PK using healthy volunteers and
obese patients. Then, say a drug is administered that reduces WT. Should we
use the same exponent
(coefficient) for healthy volunteers and obese patients? And if the drug
works, should at what point should we treat the obese patients as healthy
volunteers - or would just using WT and CLCR take care of it?.
Best regards,
Matt
-----Original Message-----
From: [email protected] [mailto:[email protected]] On
Behalf Of Nick Holford
Sent: Monday, September 02, 2013 12:16
To: 'nmusers'
Subject: Re: [NMusers] Time-varing covariate and renal function as a covariate
Matt,
Thanks for your interest in this question. Hans and I have differing approaches
for including 'renal function' but I think we agree on 'size'.
Our differences of approach to 'renal function' are not very important for
those who understand the biology and pharmacology. But its different when we
have to talk to statisticians.
While I recognize that you are not typical of statisticians (you know something
about biology and pharmacology) it would help me (and probably
Hans) if you stated more precisely what you mean by 'renal function' and 'size'
and why you think there is a challenge if weight changes over time?
Best wishes,
Nick
On 2/09/2013 9:04 a.m., J.H. Proost wrote:
> Dear Matt,
> I'm not quite sure that I fully understand your question. I would say
> that a changing renal function and a changing weight over time can be
> handled as described earlier by Nick Holford, or by the modified
> approach I suggested. An important point is how to express renal
> function.
> Nick's method implies that 'size' should be excluded from 'renal
> function', so CLCR needs to be normalized / standardized, e.g. using
> CLCR in ml/min/1.73m2. Now, CLCR is a 'pure' measure of the kidney
> function (of course, we know that its precision is rather poor, but
> that is a different topic, interesting as well!). The factor
> WEIGHT^0.75 deals with the factor 'size'. This approach treats CLCR as
> a covariate similar to other covariates, making it more suitable for a
> standardized approach for covariate analysis.
> In the approach proposed by me, CLCR should be the 'individual's renal
> clearance of creatinine', so it should expressed in ml/min (or
> converted to e.g. l/h), and it should not be normalized /
> standardized. Here, CLCR includes both kidney function and size (in
> Nick's view a disadvantage, in my view an advantage), and the renal
> part of the equation does not need further modification to take 'size'
> into account. This approach treats CLCR as a 'special' covariate,
> directly related to the renal clearance of the drug. This may be
> advantageous for clinical purposes, e.g. dose calculation and
> therapeutic drug monitoring.
> In my view, both approaches have advantages and disadvantages.
> best regards,
> Hans Proost
> Johannes H. Proost
> Dept. of Pharmacokinetics, Toxicology and Targeting University Centre
> for Pharmacy Antonius Deusinglaan 1
> 9713 AV Groningen, The Netherlands
> tel. 31-50 363 3292
> fax 31-50 363 3247
> Email: [email protected] <mailto:[email protected]>
>
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