RE: Time-varing covariate and renal function as a covariate
Dear Matt,
I still don't see the problem you are raising. Both the approach of Nick and my
approach separate weight and CLCR as much as possible, and I don't see why this
should not work in your example. You stated:
> CLCR (a function of WT)
This is not necessarily true. It depends on whether CLCR is normalised (which
should be done that the resulting value is expected to be independent of WT) or
non-normalised (as in my approach, where CLCR is a measure of renal function
including the effect of weight). Also, the word 'function' is not correct here,
since there is no direct relationship at the individual level: it is not true
that eating will result in an increase of CLCR. However, it is true that a big
person is expected to have a higher non-normalized CLCR than a small person.
best regards,
Hans
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] <[email protected]>
Quoted reply history
On 03-09-13, Matt Hutmacher <[email protected]> wrote:
>
> 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]]
> <[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] <[email protected]>>
> >
>
>
>