Dear all,
I am wondering what your thoughts are on the allometric scaling of clearance of
renally extreted drugs, where we have estimations renal function.
Simply scaling the predicted glomerular filtration rate from, for example, the
Cockroft-gault equation seems inappropriate, since weight is already a part of
the equation. Standardizing this to weight in the Cockroft-gault equation can
be done, a solution has been discussed here:
http://cognigencorp.com/nonmem/current/2013-August/4697.html
However, in the recent years some new equations to calculate glomerular
filtration rate from endogenous markers have emerged. For example the CKD-EPI
CREATININE CYSTATIN C equation
https://www.kidney.org/content/ckd-epi-creatinine-cystatin-equation-2012 . As
the addition of a muscle mass independent endogenous marker like cystatin C is
known to provide better estimations of GFR in, for example, cachectic patients,
it is likely that this equation may outperform to predict renally filtrated
compounds in this patient group. It is rather odd that this CKD-EPI equation
does not contain any measure of body size. The outcome of this equation is a
GFR scaled to a BSA of 1.73m^2.
I am wondering how you would allometrically scale the eGFRs from these CKD EPI
equations to, for example, fat-free mass.
Cheers!
Rob
R. ter Heine, PhD, PharmD
Hospital Pharmacist-Clinical Pharmacologist
Radboudumc, Nijmegen, The Netherlands
Het Radboudumc staat geregistreerd bij de Kamer van Koophandel in het
handelsregister onder nummer 41055629.
The Radboud university medical center is listed in the Commercial Register of
the Chamber of Commerce under file number 41055629.
Allometric scaling of renal clearance with estimated glomerular filtration rate
Dear Rob,
At PMX Benelux, there was an interesting talk about the correlation between
different metrics describing renal function by Stijn Jonckheere.
A part of the work presented was published:
https://academic.oup.com/jac/article/71/9/2538/1750427
This may provide some perspective, or rather complicate things even more,
depending on your viewpoint.
Best regards
Ruben Faelens
Op di 5 dec. 2017 18:24 schreef <[email protected]>:
> Dear all,
>
>
>
> I am wondering what your thoughts are on the allometric scaling of
> clearance of renally extreted drugs, where we have estimations renal
> function.
>
>
>
> Simply scaling the predicted glomerular filtration rate from, for example,
> the Cockroft-gault equation seems inappropriate, since weight is already a
> part of the equation. Standardizing this to weight in the Cockroft-gault
> equation can be done, a solution has been discussed here:
> http://cognigencorp.com/nonmem/current/2013-August/4697.html
>
>
>
> However, in the recent years some new equations to calculate glomerular
> filtration rate from endogenous markers have emerged. For example the
> CKD-EPI CREATININE CYSTATIN C equation
> https://www.kidney.org/content/ckd-epi-creatinine-cystatin-equation-2012
> . As the addition of a muscle mass independent endogenous marker like
> cystatin C is known to provide better estimations of GFR in, for example,
> cachectic patients, it is likely that this equation may outperform to
> predict renally filtrated compounds in this patient group. It is rather odd
> that this CKD-EPI equation does not contain any measure of body size. The
> outcome of this equation is a GFR scaled to a BSA of 1.73m^2.
>
>
>
> I am wondering how you would allometrically scale the eGFRs from these CKD
> EPI equations to, for example, fat-free mass.
>
>
>
> Cheers!
>
> Rob
>
>
>
> R. ter Heine, PhD, PharmD
>
> Hospital Pharmacist-Clinical Pharmacologist
>
> Radboudumc, Nijmegen, The Netherlands
>
>
>
> Het Radboudumc staat geregistreerd bij de Kamer van Koophandel in het
> handelsregister onder nummer 41055629.
> The Radboud university medical center is listed in the Commercial Register
> of the Chamber of Commerce under file number 41055629.
>
Hi Ruben,
Interesting work, Ruben. One may indeed question the validity of glomerular
filtration rate markers like cystatin C (that is only filtrated and not
actively secreted) to predict PK of drugs that undergo active tubular secretion
in patients with decreased renal function. When glomerular filtration rate
drops, the relative contribution of active tubular secretion to renal clearance
increases. To me, it appears logical that creatinine is a better marker for
clearance drugs that are actively secreted, as creatinine also undergoes active
tubular secretion.
Nonetheless, I’m also interested whether other people have considered
allometric scaling of MDRD/CKD-EPI derived GFR’s?
Cheers,
Rob
Van: Ruben Faelens <[email protected]>
Datum: dinsdag 5 december 2017 om 7:13 PM
Aan: "Heine, Rob ter" <[email protected]>
CC: "[email protected]" <[email protected]>
Onderwerp: Re: [NMusers] Allometric scaling of renal clearance with estimated
glomerular filtration rate
Dear Rob,
At PMX Benelux, there was an interesting talk about the correlation between
different metrics describing renal function by Stijn Jonckheere.
A part of the work presented was published:
https://academic.oup.com/jac/article/71/9/2538/1750427
This may provide some perspective, or rather complicate things even more,
depending on your viewpoint.
Best regards
Ruben Faelens
Op di 5 dec. 2017 18:24 schreef
<[email protected]<mailto:[email protected]>>:
Dear all,
I am wondering what your thoughts are on the allometric scaling of clearance of
renally extreted drugs, where we have estimations renal function.
Simply scaling the predicted glomerular filtration rate from, for example, the
Cockroft-gault equation seems inappropriate, since weight is already a part of
the equation. Standardizing this to weight in the Cockroft-gault equation can
be done, a solution has been discussed here:
http://cognigencorp.com/nonmem/current/2013-August/4697.html
However, in the recent years some new equations to calculate glomerular
filtration rate from endogenous markers have emerged. For example the CKD-EPI
CREATININE CYSTATIN C equation
https://www.kidney.org/content/ckd-epi-creatinine-cystatin-equation-2012 . As
the addition of a muscle mass independent endogenous marker like cystatin C is
known to provide better estimations of GFR in, for example, cachectic patients,
it is likely that this equation may outperform to predict renally filtrated
compounds in this patient group. It is rather odd that this CKD-EPI equation
does not contain any measure of body size. The outcome of this equation is a
GFR scaled to a BSA of 1.73m^2.
I am wondering how you would allometrically scale the eGFRs from these CKD EPI
equations to, for example, fat-free mass.
Cheers!
Rob
R. ter Heine, PhD, PharmD
Hospital Pharmacist-Clinical Pharmacologist
Radboudumc, Nijmegen, The Netherlands
Het Radboudumc staat geregistreerd bij de Kamer van Koophandel in het
handelsregister onder nummer 41055629.
The Radboud university medical center is listed in the Commercial Register of
the Chamber of Commerce under file number 41055629.
Het Radboudumc staat geregistreerd bij de Kamer van Koophandel in het
handelsregister onder nummer 41055629.
The Radboud university medical center is listed in the Commercial Register of
the Chamber of Commerce under file number 41055629.
Dear Rob,
A few comments to your message: In a PharmPK thread in 2013, cited by you, Nick Holford explained his approach for using estimates of GFR for dose adjustment, in answer to a message from myself, suggesting an approach suggested long time ago by Dettli and others. This can be written as:
CL_renal_drug = fr * eGFR
where CL_renal_drug is the renal clearance of the drug (in ml/min), fr is the (dimensionless) ratio of renal clearance of the drug (assumed to be drug-specific, but independent of GFR), eGFR is the estimated value for GFR (irrespective of the method, expressed in ml/min, not ml/min/1.73m2).
As far as I know, there is no literature comparing both approaches, so it remains to be determined which approach is 'best'.
You are completely right that it may be questioned whether this holds for drugs that are actively secreted. For the latter, an additional clerance term may be added, using allometric scaling with exponent 0.75.
The CKD-EPI equation does not contain any measure of body size. This is not really surprising, since GFR is expressed in ml/min/1.73m2. This value is scaled for body surface area, which is rather close to allometric scaling with a factor of 0.75. The eGFR expressed in ml/min, which is an estimate of the actual GFR, is affected by weight and height, as expected.
Note that eGFR expressed in ml/min/1.73m2 is used by nephrologists as a measure of renal function, but for estimation of renal clearance and dosing purposes, one should always use eGFR in ml/min. For example, the Dettli approach can be used for any estimate of eGFR, provided that values in ml/min/1.73m2 are converted to ml/min, using the body surface area estimated from weight and height.
best regards,
Johannes H. Proost
Department of Pharmacokinetics, Toxicology and Targeting
University of Groningen
the Netherlands
Op 5-12-2017 om 18:17 schreef [email protected]:
> Dear all,
>
> I am wondering what your thoughts are on the allometric scaling of clearance of renally extreted drugs, where we have estimations renal function.
>
> Simply scaling the predicted glomerular filtration rate from, for example, the Cockroft-gault equation seems inappropriate, since weight is already a part of the equation. Standardizing this to weight in the Cockroft-gault equation can be done, a solution has been discussed here: http://cognigencorp.com/nonmem/current/2013-August/4697.html
>
> However, in the recent years some new equations to calculate glomerular filtration rate from endogenous markers have emerged. For example the CKD-EPI CREATININE CYSTATIN C equation https://www.kidney.org/content/ckd-epi-creatinine-cystatin-equation-2012 . As the addition of a muscle mass independent endogenous marker like cystatin C is known to provide better estimations of GFR in, for example, cachectic patients, it is likely that this equation may outperform to predict renally filtrated compounds in this patient group. It is rather odd that this CKD-EPI equation does not contain any measure of body size. The outcome of this equation is a GFR scaled to a BSA of 1.73m^2.
>
> I am wondering how you would allometrically scale the eGFRs from these CKD EPI equations to, for example, fat-free mass.
>
> Cheers!
>
> Rob
>
> R. ter Heine, PhD, PharmD
>
> Hospital Pharmacist-Clinical Pharmacologist
>
> Radboudumc, Nijmegen, The Netherlands
>
> Het Radboudumc staat geregistreerd bij de Kamer van Koophandel in het handelsregister onder nummer 41055629. The Radboud university medical center is listed in the Commercial Register of the Chamber of Commerce under file number 41055629.
Dear Nick, Hans, Ruben, Max,
Great to hear several approaches and opinions on the use of glomerular
filtration approximations in PK modeling and scaling to body size. Thank you!
I have a hard time ignoring the CKD-EPI equations (with or without cystatin C),
as they are well established and proven better predictors for GFR, when
compared to the Cockroft-Gault. In general, sample sizes of pharmacokinetic
studies are smaller than those where the CKD-EPI and MDRD equations were
developed. I am not convinced that developing a new creatinine/cystatin c
equation for GFR for each PK analysis is the right approach. Then again, I also
have a hard time scaling to BSA, as in, for example, obese patients this is
likely a poor body size descriptor to scale renal function.
Also, depending on the population and drug one may choose one equation above
another. For example: if a drug is completely filtrated (no active secretion),
a cystatin C based equation is likely better explain variability in clearance
of completely filtrated drugs (e.g. carboplatin). Another example: in cachectic
patients one may argue that there is not enough muscle mass (and thus serum
creatinine) to provide accurate GFR estimations and then creatinine-independent
equations may provide better equations.
Thinking about this the last couple of days and with your feedback, I am
inclined to choose the equation based on population (e.g. cachectic or not?)
and drug (e.g. filtration/active secretion) and, if the equation scales renal
function to BSA, convert it to scaling to FFM. Nonetheless, open to any other
suggestion or discuss cons and pro's anytime!
Sincerely,
Rob
-----Oorspronkelijk bericht-----
Quoted reply history
Van: [email protected] [mailto:[email protected]] Namens
Nick Holford
Verzonden: woensdag 6 december 2017 20:06
Aan: [email protected]
Onderwerp: Re: [FORGED] [NMusers] Allometric scaling of renal clearance with
estimated glomerular filtration rate
Hi Rob,
Thanks for bringing this up again. I don't think much has changed since I wrote
this in 2013
( http://cognigencorp.com/nonmem/current/2013-August/4697.html)
1. Theory Based Allometry or Surface Area
"Note that using surface area as a form of size standardization forglomerular
filtration rate has no theoretical nor experimental support when compared to
theory based allometry (Rhodin et al. 2009). So I donot agree with
standardizing CLCR to 1.73 m^2. I know this is frequently done but in fact this
is just based on tradition and an out of datetheory of scaling based on surface
area (see Anderson & Holford 2008)."
There is no biological or experimental support for using surface area to scale
renal function markers such as GFR and CLcr. In contrast, there is strong
biological based theory and experimental support for using theory based
allometry (see Holford & Anderson 2017 for a recent review).
2. Mechanism Based Models for CLcr
I also wrote in 2013:
"The MDRD method of predicting glomerular filtration rate is astatistical
absurdity which does not include any measurement of size for its prediction. I
would certainly not recommend using it for anyscientific purpose. "
This applies equally well to the CKD-EPI method. Let me explain why it is a
absurdity generated by a naive statistician using CLcr as an example.
CLcr can be calculated from the creatinine excretion rate (CER) and the serum
creatiniine. This is based on the definition of clearance and is true without
any assumptions.
CLcr=CER/Scr
If we then assume Scr is at steady state then CER will be equal to creatinine
production rate (CPR) and we can use this:
CLcr=CPR/Scr
All rational models for predicting CLcr without measurement of CER use models
to predict CPR e.g.
CPR=(140-Age)*Weight/72 use Cockcroft & Gault to predict CPR in males then
CLcr=CPR/Scr is Cockcroft & Gault CLcr ml/min
Dividing CPR by Scr gives the CLcr. This can be written equivalently but less
clearly:
CLcr=CPR*Scr^-1
The empirical models such as MDRD and CKI-EPI (see below) involve the absurdity
of estimating the known exponent for Scr of -1. These estimates must be wrong
based on the theory I have outlined above (unless the estimate is exactly -1).
The reported estimates are -1.209 for CKI-EPI and -1.154 for MDRD.
In addition, and more importantly,they have no direct measure of body size
which seriously limits the value outside the typical weight distribution and
they are only applicable to adults. GFR can be described from premature
neonates to adults using theory based allometry and maturation based on
post-menstrual age so GFR predicttions should try to follow the concepts used
there (Rhodin 2008).
So what to do?
First -- don't use MDRD or CKI-EPI unless you are sure you are applying them to
a population similar to that used to develop these empirical predictions. You
could add allometric scaling to the eGFR by assuming the 1.72m^2 value is
equivalent to 70 kg with a fat free mass (FFM) of
56.1 kg. Then scaling the eGFR by (WT/70)^(3/4) or (FFM/56.1)^(3/4).
I use the Schwartz (1992) equations for neonates, children and teenagers then
the Matthews (2004) equation for adults. I am working on an integrated method
for CPR prediction which was presented as a work in progress at PAGE this year.
Watch this space...
Best wishes,
Nick
MDRD
eGFR =175 x (SCr)^-1.154 x (age)-0.203 x 0.742 [if female] x
1.212 [if Black]
CKI-EPI
eGFR = 141 x min(SCr/k, 1)^alpha x max(SCr /kappa, 1)^-1.209 x 0.993^Age
x 1.018 [if female] x 1.159 [if Black]
kappa = 0.7 (females) or 0.9 (males)
alpha = -0.329 (females) or -0.411 (males)
eGFR (estimated glomerular filtration rate) = mL/min/1.73 m2; SCr (standardized
serum creatinine) = mg/dL
Holford NHG, Anderson BJ. Allometric size: The scientific theory and
extension to normal fat mass. Eur J Pharm Sci. 2017;109(Supplement):S59-S64.
Rhodin MM, Anderson BJ, Peters AM, Coulthard MG, Wilkins B, Cole M,
Chatelut E, Grubb A, Veal GJ, Keir MJ, Holford NH
Human renal function maturation – a quantitative description using
weight and postmenstrual age. Pediatr Nephrol. 2008
Schwartz GJ. Does kL/PCr estimate GFR, or does GFR determine k? Pediatr
Nephrol. 1992;6(6):512-5.
Matthews I, Kirkpatrick C, Holford N. Quantitative justification for
target concentration intervention -- parameter variability and
predictive performance using population pharmacokinetic models for
aminoglycosides. Br J Clin Pharmacol. 2004;58(1):8-19.
Holford N, Sherwin CM. Scaling renal function in neonates and infants to
describe the pharmacodynamics of antibiotic nephrotoxicity. PAGE 26
Abstr 7208 [wwwpage-meetingorg/?abstract=7208]. 2017.
On 06-Dec-17 23:52, [email protected] wrote:
>
> Hi Ruben,
>
> Interesting work, Ruben. One may indeed question the validity of
> glomerular filtration rate markers like cystatin C (that is only
> filtrated and not actively secreted) to predict PK of drugs that
> undergo active tubular secretion in patients with decreased renal
> function. When glomerular filtration rate drops, the relative
> contribution of active tubular secretion to renal clearance increases.
> To me, it appears logical that creatinine is a better marker for
> clearance drugs that are actively secreted, as creatinine also
> undergoes active tubular secretion.
>
> Nonetheless, I’m also interested whether other people have considered
> allometric scaling of MDRD/CKD-EPI derived GFR’s?
>
> Cheers,
>
> Rob
>
> *Van: *Ruben Faelens <[email protected]>
> *Datum: *dinsdag 5 december 2017 om 7:13 PM
> *Aan: *"Heine, Rob ter" <[email protected]>
> *CC: *"[email protected]" <[email protected]>
> *Onderwerp: *Re: [NMusers] Allometric scaling of renal clearance with
> estimated glomerular filtration rate
>
> Dear Rob,
>
> At PMX Benelux, there was an interesting talk about the correlation
> between different metrics describing renal function by Stijn Jonckheere.
> A part of the work presented was published:
> https://academic.oup.com/jac/article/71/9/2538/1750427
> https://academic.oup.com/jac/article/71/9/2538/1750427
>
> This may provide some perspective, or rather complicate things even
> more, depending on your viewpoint.
>
> Best regards
> Ruben Faelens
>
On 06-Dec-17 06:17, [email protected] wrote:
>
> Dear all,
>
> I am wondering what your thoughts are on the allometric scaling of
> clearance of renally extreted drugs, where we have estimations renal
> function.
>
> Simply scaling the predicted glomerular filtration rate from, for
> example, the Cockroft-gault equation seems inappropriate, since weight
> is already a part of the equation. Standardizing this to weight in the
> Cockroft-gault equation can be done, a solution has been discussed
> here: http://cognigencorp.com/nonmem/current/2013-August/4697.html
>
> However, in the recent years some new equations to calculate
> glomerular filtration rate from endogenous markers have emerged. For
> example the CKD-EPI CREATININE CYSTATIN C equation
> https://www.kidney.org/content/ckd-epi-creatinine-cystatin-equation-2012
> . As the addition of a muscle mass independent endogenous marker like
> cystatin C is known to provide better estimations of GFR in, for
> example, cachectic patients, it is likely that this equation may
> outperform to predict renally filtrated compounds in this patient
> group. It is rather odd that this CKD-EPI equation does not contain
> any measure of body size. The outcome of this equation is a GFR scaled
> to a BSA of 1.73m^2.
>
> I am wondering how you would allometrically scale the eGFRs from these
> CKD EPI equations to, for example, fat-free mass.
>
> Cheers!
>
> Rob
>
> R. ter Heine, PhD, PharmD
>
> Hospital Pharmacist-Clinical Pharmacologist
>
> Radboudumc, Nijmegen, The Netherlands
>
> Het Radboudumc staat geregistreerd bij de Kamer van Koophandel in het
> handelsregister onder nummer 41055629.
> The Radboud university medical center is listed in the Commercial
> Register of the Chamber of Commerce under file number 41055629.
>
--
Nick Holford, Professor Clinical Pharmacology
Dept Pharmacology & Clinical Pharmacology, Bldg 503 Room 302A
University of Auckland,85 Park Rd,Private Bag 92019,Auckland,New Zealand
office:+64(9)923-6730 mobile:NZ+64(21)46 23 53 FR+33(6)62 32 46 72
email:[email protected]
http://holford.fmhs.auckland.ac.nz/
http://orcid.org/0000-0002-4031-2514
Read the question, answer the question, attempt all questions
Het Radboudumc staat geregistreerd bij de Kamer van Koophandel in het
handelsregister onder nummer 41055629.
The Radboud university medical center is listed in the Commercial Register of
the Chamber of Commerce under file number 41055629.
Dear Rob,
Why do you want to use a model to predict the value of a covariate to add into
your model? Apart from glomerular filtration rate, what other situations would
you do this?
Unless I was trying to do some fancy separation of renal and non-renal
clearance, I would simply ignore the fact there is a model to predict
glomerular fltration, and include its component parts e.g.
CL = THETA * (WT/70)**0.75 * FCREAT * FAGE
where FCREAT and FAGE are covariate functions for creatinine (e.g. (SECR/median
value)**THETA ) and age.
Some examples of not using a model to predict GFR still gave an acceptable
model of CL (what we were interested in):
Creatinie e.g.
Hennig S. Population pharmacokinetics of tobramycin in patients with and
without cystic fibrosis. Clin Pharmacokinet. 2013 Apr;52(4):289-301
Cystatin C example:
De Cock PA. Augmented renal clearance implies a need for increased
amoxicillin-clavulanic acid dosing in critically ill children. Antimicrob
Agents Chemother. 2015 Nov;59(11):7027-35.
BW,
Joe
Joseph F Standing
MRC Fellow, UCL Institute of Child Health
Antimicrobial Pharmacist, Great Ormond Street Hospital
Honorary Senior Lecturer, St George's University of London
Tel: +44(0)207 905 2370
Mobile: +44(0)7970 572435
Quoted reply history
________________________________________
From: [email protected] [[email protected]] on behalf of
[email protected] [[email protected]]
Sent: 07 December 2017 11:56
To: [email protected]
Cc: [email protected]; [email protected]; [email protected];
[email protected]
Subject: RE: [NMusers] Allometric scaling of renal clearance with estimated
glomerular filtration rate
Dear Nick, Hans, Ruben, Max,
Great to hear several approaches and opinions on the use of glomerular
filtration approximations in PK modeling and scaling to body size. Thank you!
I have a hard time ignoring the CKD-EPI equations (with or without cystatin C),
as they are well established and proven better predictors for GFR, when
compared to the Cockroft-Gault. In general, sample sizes of pharmacokinetic
studies are smaller than those where the CKD-EPI and MDRD equations were
developed. I am not convinced that developing a new creatinine/cystatin c
equation for GFR for each PK analysis is the right approach. Then again, I also
have a hard time scaling to BSA, as in, for example, obese patients this is
likely a poor body size descriptor to scale renal function.
Also, depending on the population and drug one may choose one equation above
another. For example: if a drug is completely filtrated (no active secretion),
a cystatin C based equation is likely better explain variability in clearance
of completely filtrated drugs (e.g. carboplatin). Another example: in cachectic
patients one may argue that there is not enough muscle mass (and thus serum
creatinine) to provide accurate GFR estimations and then creatinine-independent
equations may provide better equations.
Thinking about this the last couple of days and with your feedback, I am
inclined to choose the equation based on population (e.g. cachectic or not?)
and drug (e.g. filtration/active secretion) and, if the equation scales renal
function to BSA, convert it to scaling to FFM. Nonetheless, open to any other
suggestion or discuss cons and pro's anytime!
Sincerely,
Rob
-----Oorspronkelijk bericht-----
Van: [email protected] [mailto:[email protected]] Namens
Nick Holford
Verzonden: woensdag 6 december 2017 20:06
Aan: [email protected]
Onderwerp: Re: [FORGED] [NMusers] Allometric scaling of renal clearance with
estimated glomerular filtration rate
Hi Rob,
Thanks for bringing this up again. I don't think much has changed since I wrote
this in 2013
( http://cognigencorp.com/nonmem/current/2013-August/4697.html)
1. Theory Based Allometry or Surface Area
"Note that using surface area as a form of size standardization forglomerular
filtration rate has no theoretical nor experimental support when compared to
theory based allometry (Rhodin et al. 2009). So I donot agree with
standardizing CLCR to 1.73 m^2. I know this is frequently done but in fact this
is just based on tradition and an out of datetheory of scaling based on surface
area (see Anderson & Holford 2008)."
There is no biological or experimental support for using surface area to scale
renal function markers such as GFR and CLcr. In contrast, there is strong
biological based theory and experimental support for using theory based
allometry (see Holford & Anderson 2017 for a recent review).
2. Mechanism Based Models for CLcr
I also wrote in 2013:
"The MDRD method of predicting glomerular filtration rate is astatistical
absurdity which does not include any measurement of size for its prediction. I
would certainly not recommend using it for anyscientific purpose. "
This applies equally well to the CKD-EPI method. Let me explain why it is a
absurdity generated by a naive statistician using CLcr as an example.
CLcr can be calculated from the creatinine excretion rate (CER) and the serum
creatiniine. This is based on the definition of clearance and is true without
any assumptions.
CLcr=CER/Scr
If we then assume Scr is at steady state then CER will be equal to creatinine
production rate (CPR) and we can use this:
CLcr=CPR/Scr
All rational models for predicting CLcr without measurement of CER use models
to predict CPR e.g.
CPR=(140-Age)*Weight/72 use Cockcroft & Gault to predict CPR in males then
CLcr=CPR/Scr is Cockcroft & Gault CLcr ml/min
Dividing CPR by Scr gives the CLcr. This can be written equivalently but less
clearly:
CLcr=CPR*Scr^-1
The empirical models such as MDRD and CKI-EPI (see below) involve the absurdity
of estimating the known exponent for Scr of -1. These estimates must be wrong
based on the theory I have outlined above (unless the estimate is exactly -1).
The reported estimates are -1.209 for CKI-EPI and -1.154 for MDRD.
In addition, and more importantly,they have no direct measure of body size
which seriously limits the value outside the typical weight distribution and
they are only applicable to adults. GFR can be described from premature
neonates to adults using theory based allometry and maturation based on
post-menstrual age so GFR predicttions should try to follow the concepts used
there (Rhodin 2008).
So what to do?
First -- don't use MDRD or CKI-EPI unless you are sure you are applying them to
a population similar to that used to develop these empirical predictions. You
could add allometric scaling to the eGFR by assuming the 1.72m^2 value is
equivalent to 70 kg with a fat free mass (FFM) of
56.1 kg. Then scaling the eGFR by (WT/70)^(3/4) or (FFM/56.1)^(3/4).
I use the Schwartz (1992) equations for neonates, children and teenagers then
the Matthews (2004) equation for adults. I am working on an integrated method
for CPR prediction which was presented as a work in progress at PAGE this year.
Watch this space...
Best wishes,
Nick
MDRD
eGFR =175 x (SCr)^-1.154 x (age)-0.203 x 0.742 [if female] x
1.212 [if Black]
CKI-EPI
eGFR = 141 x min(SCr/k, 1)^alpha x max(SCr /kappa, 1)^-1.209 x 0.993^Age
x 1.018 [if female] x 1.159 [if Black]
kappa = 0.7 (females) or 0.9 (males)
alpha = -0.329 (females) or -0.411 (males)
eGFR (estimated glomerular filtration rate) = mL/min/1.73 m2; SCr (standardized
serum creatinine) = mg/dL
Holford NHG, Anderson BJ. Allometric size: The scientific theory and
extension to normal fat mass. Eur J Pharm Sci. 2017;109(Supplement):S59-S64.
Rhodin MM, Anderson BJ, Peters AM, Coulthard MG, Wilkins B, Cole M,
Chatelut E, Grubb A, Veal GJ, Keir MJ, Holford NH
Human renal function maturation – a quantitative description using
weight and postmenstrual age. Pediatr Nephrol. 2008
Schwartz GJ. Does kL/PCr estimate GFR, or does GFR determine k? Pediatr
Nephrol. 1992;6(6):512-5.
Matthews I, Kirkpatrick C, Holford N. Quantitative justification for
target concentration intervention -- parameter variability and
predictive performance using population pharmacokinetic models for
aminoglycosides. Br J Clin Pharmacol. 2004;58(1):8-19.
Holford N, Sherwin CM. Scaling renal function in neonates and infants to
describe the pharmacodynamics of antibiotic nephrotoxicity. PAGE 26
Abstr 7208 [wwwpage-meetingorg/?abstract=7208]. 2017.
On 06-Dec-17 23:52, [email protected] wrote:
>
> Hi Ruben,
>
> Interesting work, Ruben. One may indeed question the validity of
> glomerular filtration rate markers like cystatin C (that is only
> filtrated and not actively secreted) to predict PK of drugs that
> undergo active tubular secretion in patients with decreased renal
> function. When glomerular filtration rate drops, the relative
> contribution of active tubular secretion to renal clearance increases.
> To me, it appears logical that creatinine is a better marker for
> clearance drugs that are actively secreted, as creatinine also
> undergoes active tubular secretion.
>
> Nonetheless, I’m also interested whether other people have considered
> allometric scaling of MDRD/CKD-EPI derived GFR’s?
>
> Cheers,
>
> Rob
>
> *Van: *Ruben Faelens <[email protected]>
> *Datum: *dinsdag 5 december 2017 om 7:13 PM
> *Aan: *"Heine, Rob ter" <[email protected]>
> *CC: *"[email protected]" <[email protected]>
> *Onderwerp: *Re: [NMusers] Allometric scaling of renal clearance with
> estimated glomerular filtration rate
>
> Dear Rob,
>
> At PMX Benelux, there was an interesting talk about the correlation
> between different metrics describing renal function by Stijn Jonckheere.
> A part of the work presented was published:
> https://academic.oup.com/jac/article/71/9/2538/1750427
> https://academic.oup.com/jac/article/71/9/2538/1750427
>
> This may provide some perspective, or rather complicate things even
> more, depending on your viewpoint.
>
> Best regards
> Ruben Faelens
>
On 06-Dec-17 06:17, [email protected] wrote:
>
> Dear all,
>
> I am wondering what your thoughts are on the allometric scaling of
> clearance of renally extreted drugs, where we have estimations renal
> function.
>
> Simply scaling the predicted glomerular filtration rate from, for
> example, the Cockroft-gault equation seems inappropriate, since weight
> is already a part of the equation. Standardizing this to weight in the
> Cockroft-gault equation can be done, a solution has been discussed
> here: http://cognigencorp.com/nonmem/current/2013-August/4697.html
>
> However, in the recent years some new equations to calculate
> glomerular filtration rate from endogenous markers have emerged. For
> example the CKD-EPI CREATININE CYSTATIN C equation
> https://www.kidney.org/content/ckd-epi-creatinine-cystatin-equation-2012
> . As the addition of a muscle mass independent endogenous marker like
> cystatin C is known to provide better estimations of GFR in, for
> example, cachectic patients, it is likely that this equation may
> outperform to predict renally filtrated compounds in this patient
> group. It is rather odd that this CKD-EPI equation does not contain
> any measure of body size. The outcome of this equation is a GFR scaled
> to a BSA of 1.73m^2.
>
> I am wondering how you would allometrically scale the eGFRs from these
> CKD EPI equations to, for example, fat-free mass.
>
> Cheers!
>
> Rob
>
> R. ter Heine, PhD, PharmD
>
> Hospital Pharmacist-Clinical Pharmacologist
>
> Radboudumc, Nijmegen, The Netherlands
>
> Het Radboudumc staat geregistreerd bij de Kamer van Koophandel in het
> handelsregister onder nummer 41055629.
> The Radboud university medical center is listed in the Commercial
> Register of the Chamber of Commerce under file number 41055629.
>
--
Nick Holford, Professor Clinical Pharmacology
Dept Pharmacology & Clinical Pharmacology, Bldg 503 Room 302A
University of Auckland,85 Park Rd,Private Bag 92019,Auckland,New Zealand
office:+64(9)923-6730 mobile:NZ+64(21)46 23 53 FR+33(6)62 32 46 72
email:[email protected]
http://holford.fmhs.auckland.ac.nz/
http://orcid.org/0000-0002-4031-2514
Read the question, answer the question, attempt all questions
Het Radboudumc staat geregistreerd bij de Kamer van Koophandel in het
handelsregister onder nummer 41055629.
The Radboud university medical center is listed in the Commercial Register of
the Chamber of Commerce under file number 41055629.
********************************************************************************************************************
This message may contain confidential information. If you are not the intended
recipient please inform the
sender that you have received the message in error before deleting it.
Please do not disclose, copy or distribute information in this e-mail or take
any action in relation to its contents. To do so is strictly prohibited and may
be unlawful. Thank you for your co-operation.
NHSmail is the secure email and directory service available for all NHS staff
in England and Scotland. NHSmail is approved for exchanging patient data and
other sensitive information with NHSmail and other accredited email services.
For more information and to find out how you can switch,
https://portal.nhs.net/help/joiningnhsmail
Dear Joe,
Quoted reply history
On 08-Dec-17 02:00, STANDING, Joseph (GREAT ORMOND STREET HOSPITAL FOR CHILDREN NHS FOUNDATION TRUST) wrote:
> Dear Rob,
>
> Why do you want to use a model to predict the value of a covariate to add into
> your model? Apart from glomerular filtration rate, what other situations would
> you do this?
I'm not sure what you are trying to say here. What model for GFR are you thinking about as the only example? I could mention using a model for FFM based on covariates of WT, HT and SEX as an example but I don't know if this is what you mean.
> Unless I was trying to do some fancy separation of renal and non-renal
> clearance,
Unless you want to assume that the drug is completely eliminated renally then there should always be a "fancy separation" of renal and non-renal clearance. I don't know of any clear cut case where I could assume a drug can only be eliminated by the kidneys.
> I would simply ignore the fact there is a model to predict glomerular
> fltration, and include its component parts e.g.
>
> CL = THETA * (WT/70)**0.75 * FCREAT * FAGE
>
> where FCREAT and FAGE are covariate functions for creatinine (e.g. (SECR/median
> value)**THETA ) and age.
No explicit assumption of the pathway of elimination but just an empirical functions of SCR. This can include the bizarre MDRD and CKD-EPI functions which include skin colour as a covariate. I consider this kind of empiricism when there are mechanistic alternatives to be bad science.
> Some examples of not using a model to predict GFR still gave an acceptable
> model of CL (what we were interested in):
>
> Creatinie e.g.
> Hennig S. Population pharmacokinetics of tobramycin in patients with and
> without cystic fibrosis. Clin Pharmacokinet. 2013 Apr;52(4):289-301
>
> Cystatin C example:
> De Cock PA. Augmented renal clearance implies a need for increased
> amoxicillin-clavulanic acid dosing in critically ill children. Antimicrob
> Agents Chemother. 2015 Nov;59(11):7027-35.
Just because a model can provide a local fit to the data does not mean it has good properties for generalization / extrapolation. Incorporating biological mechanism and sensible extrapolation properties should be used whenever possible.
Best wishes,
Nick
> BW,
>
> Joe
>
> Joseph F Standing
> MRC Fellow, UCL Institute of Child Health
> Antimicrobial Pharmacist, Great Ormond Street Hospital
> Honorary Senior Lecturer, St George's University of London
> Tel: +44(0)207 905 2370
> Mobile: +44(0)7970 572435
> ________________________________________
> From: [email protected] [[email protected]] on behalf of
> [email protected] [[email protected]]
> Sent: 07 December 2017 11:56
> To: [email protected]
> Cc: [email protected]; [email protected]; [email protected];
> [email protected]
> Subject: RE: [NMusers] Allometric scaling of renal clearance with estimated
> glomerular filtration rate
>
> Dear Nick, Hans, Ruben, Max,
>
> Great to hear several approaches and opinions on the use of glomerular
> filtration approximations in PK modeling and scaling to body size. Thank you!
>
> I have a hard time ignoring the CKD-EPI equations (with or without cystatin C),
> as they are well established and proven better predictors for GFR, when
> compared to the Cockroft-Gault. In general, sample sizes of pharmacokinetic
> studies are smaller than those where the CKD-EPI and MDRD equations were
> developed. I am not convinced that developing a new creatinine/cystatin c
> equation for GFR for each PK analysis is the right approach. Then again, I also
> have a hard time scaling to BSA, as in, for example, obese patients this is
> likely a poor body size descriptor to scale renal function.
>
> Also, depending on the population and drug one may choose one equation above
> another. For example: if a drug is completely filtrated (no active secretion),
> a cystatin C based equation is likely better explain variability in clearance
> of completely filtrated drugs (e.g. carboplatin). Another example: in cachectic
> patients one may argue that there is not enough muscle mass (and thus serum
> creatinine) to provide accurate GFR estimations and then creatinine-independent
> equations may provide better equations.
>
> Thinking about this the last couple of days and with your feedback, I am
> inclined to choose the equation based on population (e.g. cachectic or not?)
> and drug (e.g. filtration/active secretion) and, if the equation scales renal
> function to BSA, convert it to scaling to FFM. Nonetheless, open to any other
> suggestion or discuss cons and pro's anytime!
>
> Sincerely,
> Rob
>
> -----Oorspronkelijk bericht-----
> Van: [email protected] [mailto:[email protected]] Namens
> Nick Holford
> Verzonden: woensdag 6 december 2017 20:06
> Aan: [email protected]
> Onderwerp: Re: [FORGED] [NMusers] Allometric scaling of renal clearance with
> estimated glomerular filtration rate
>
> Hi Rob,
>
> Thanks for bringing this up again. I don't think much has changed since I wrote
> this in 2013
> ( http://cognigencorp.com/nonmem/current/2013-August/4697.html)
>
> 1. Theory Based Allometry or Surface Area
>
> "Note that using surface area as a form of size standardization forglomerular filtration
> rate has no theoretical nor experimental support when compared to theory based allometry
> (Rhodin et al. 2009). So I donot agree with standardizing CLCR to 1.73 m^2. I know this is
> frequently done but in fact this is just based on tradition and an out of datetheory of
> scaling based on surface area (see Anderson & Holford 2008)."
>
> There is no biological or experimental support for using surface area to scale
> renal function markers such as GFR and CLcr. In contrast, there is strong
> biological based theory and experimental support for using theory based allometry
> (see Holford & Anderson 2017 for a recent review).
>
> 2. Mechanism Based Models for CLcr
>
> I also wrote in 2013:
>
> "The MDRD method of predicting glomerular filtration rate is astatistical absurdity
> which does not include any measurement of size for its prediction. I would certainly not
> recommend using it for anyscientific purpose."
>
> This applies equally well to the CKD-EPI method. Let me explain why it is a
> absurdity generated by a naive statistician using CLcr as an example.
>
> CLcr can be calculated from the creatinine excretion rate (CER) and the serum
> creatiniine. This is based on the definition of clearance and is true without
> any assumptions.
> CLcr=CER/Scr
> If we then assume Scr is at steady state then CER will be equal to creatinine
> production rate (CPR) and we can use this:
> CLcr=CPR/Scr
> All rational models for predicting CLcr without measurement of CER use models
> to predict CPR e.g.
>
> CPR=(140-Age)*Weight/72 use Cockcroft & Gault to predict CPR in males then
> CLcr=CPR/Scr is Cockcroft & Gault CLcr ml/min
>
> Dividing CPR by Scr gives the CLcr. This can be written equivalently but less
> clearly:
> CLcr=CPR*Scr^-1
>
> The empirical models such as MDRD and CKI-EPI (see below) involve the absurdity
> of estimating the known exponent for Scr of -1. These estimates must be wrong
> based on the theory I have outlined above (unless the estimate is exactly -1).
> The reported estimates are -1.209 for CKI-EPI and -1.154 for MDRD.
>
> In addition, and more importantly,they have no direct measure of body size
> which seriously limits the value outside the typical weight distribution and
> they are only applicable to adults. GFR can be described from premature
> neonates to adults using theory based allometry and maturation based on
> post-menstrual age so GFR predicttions should try to follow the concepts used
> there (Rhodin 2008).
>
> So what to do?
>
> First -- don't use MDRD or CKI-EPI unless you are sure you are applying them to
> a population similar to that used to develop these empirical predictions. You
> could add allometric scaling to the eGFR by assuming the 1.72m^2 value is
> equivalent to 70 kg with a fat free mass (FFM) of
> 56.1 kg. Then scaling the eGFR by (WT/70)^(3/4) or (FFM/56.1)^(3/4).
>
> I use the Schwartz (1992) equations for neonates, children and teenagers then
> the Matthews (2004) equation for adults. I am working on an integrated method
> for CPR prediction which was presented as a work in progress at PAGE this year.
> Watch this space...
>
> Best wishes,
>
> Nick
>
> MDRD
> eGFR =175 x (SCr)^-1.154 x (age)-0.203 x 0.742 [if female] x
> 1.212 [if Black]
>
> CKI-EPI
> eGFR = 141 x min(SCr/k, 1)^alpha x max(SCr /kappa, 1)^-1.209 x
> 0.993^Age x 1.018 [if female] x 1.159 [if Black]
> kappa = 0.7 (females) or 0.9 (males)
> alpha = -0.329 (females) or -0.411 (males)
>
> eGFR (estimated glomerular filtration rate) = mL/min/1.73 m2; SCr (standardized
> serum creatinine) = mg/dL
>
> Holford NHG, Anderson BJ. Allometric size: The scientific theory and
> extension to normal fat mass. Eur J Pharm Sci. 2017;109(Supplement):S59-S64.
>
> Rhodin MM, Anderson BJ, Peters AM, Coulthard MG, Wilkins B, Cole M,
> Chatelut E, Grubb A, Veal GJ, Keir MJ, Holford NH
> Human renal function maturation – a quantitative description using
> weight and postmenstrual age. Pediatr Nephrol. 2008
>
> Schwartz GJ. Does kL/PCr estimate GFR, or does GFR determine k? Pediatr
> Nephrol. 1992;6(6):512-5.
>
> Matthews I, Kirkpatrick C, Holford N. Quantitative justification for
> target concentration intervention -- parameter variability and
> predictive performance using population pharmacokinetic models for
> aminoglycosides. Br J Clin Pharmacol. 2004;58(1):8-19.
>
> Holford N, Sherwin CM. Scaling renal function in neonates and infants to
> describe the pharmacodynamics of antibiotic nephrotoxicity. PAGE 26
> Abstr 7208 [wwwpage-meetingorg/?abstract=7208]. 2017.
>
> On 06-Dec-17 23:52, [email protected] wrote:
>
> > Hi Ruben,
> >
> > Interesting work, Ruben. One may indeed question the validity of
> > glomerular filtration rate markers like cystatin C (that is only
> > filtrated and not actively secreted) to predict PK of drugs that
> > undergo active tubular secretion in patients with decreased renal
> > function. When glomerular filtration rate drops, the relative
> > contribution of active tubular secretion to renal clearance increases.
> > To me, it appears logical that creatinine is a better marker for
> > clearance drugs that are actively secreted, as creatinine also
> > undergoes active tubular secretion.
> >
> > Nonetheless, I’m also interested whether other people have considered
> > allometric scaling of MDRD/CKD-EPI derived GFR’s?
> >
> > Cheers,
> >
> > Rob
> >
> > *Van: *Ruben Faelens <[email protected]>
> > *Datum: *dinsdag 5 december 2017 om 7:13 PM
> > *Aan: *"Heine, Rob ter" <[email protected]>
> > *CC: *"[email protected]" <[email protected]>
> > *Onderwerp: *Re: [NMusers] Allometric scaling of renal clearance with
> > estimated glomerular filtration rate
> >
> > Dear Rob,
> >
> > At PMX Benelux, there was an interesting talk about the correlation
> > between different metrics describing renal function by Stijn Jonckheere.
> > A part of the work presented was published:
> > https://academic.oup.com/jac/article/71/9/2538/1750427
> > https://academic.oup.com/jac/article/71/9/2538/1750427
> >
> > This may provide some perspective, or rather complicate things even
> > more, depending on your viewpoint.
> >
> > Best regards
> > Ruben Faelens
>
> On 06-Dec-17 06:17, [email protected] wrote:
>
> > Dear all,
> >
> > I am wondering what your thoughts are on the allometric scaling of
> > clearance of renally extreted drugs, where we have estimations renal
> > function.
> >
> > Simply scaling the predicted glomerular filtration rate from, for
> > example, the Cockroft-gault equation seems inappropriate, since weight
> > is already a part of the equation. Standardizing this to weight in the
> > Cockroft-gault equation can be done, a solution has been discussed
> > here: http://cognigencorp.com/nonmem/current/2013-August/4697.html
> >
> > However, in the recent years some new equations to calculate
> > glomerular filtration rate from endogenous markers have emerged. For
> > example the CKD-EPI CREATININE CYSTATIN C equation
> > https://www.kidney.org/content/ckd-epi-creatinine-cystatin-equation-2012
> > . As the addition of a muscle mass independent endogenous marker like
> > cystatin C is known to provide better estimations of GFR in, for
> > example, cachectic patients, it is likely that this equation may
> > outperform to predict renally filtrated compounds in this patient
> > group. It is rather odd that this CKD-EPI equation does not contain
> > any measure of body size. The outcome of this equation is a GFR scaled
> > to a BSA of 1.73m^2.
> >
> > I am wondering how you would allometrically scale the eGFRs from these
> > CKD EPI equations to, for example, fat-free mass.
> >
> > Cheers!
> >
> > Rob
> >
> > R. ter Heine, PhD, PharmD
> >
> > Hospital Pharmacist-Clinical Pharmacologist
> >
> > Radboudumc, Nijmegen, The Netherlands
> >
> > Het Radboudumc staat geregistreerd bij de Kamer van Koophandel in het
> > handelsregister onder nummer 41055629.
> > The Radboud university medical center is listed in the Commercial
> > Register of the Chamber of Commerce under file number 41055629.
>
> --
> Nick Holford, Professor Clinical Pharmacology
> Dept Pharmacology & Clinical Pharmacology, Bldg 503 Room 302A
> University of Auckland,85 Park Rd,Private Bag 92019,Auckland,New Zealand
> office:+64(9)923-6730 mobile:NZ+64(21)46 23 53 FR+33(6)62 32 46 72
> email:[email protected]
> http://holford.fmhs.auckland.ac.nz/
> http://orcid.org/0000-0002-4031-2514
> Read the question, answer the question, attempt all questions
>
> Het Radboudumc staat geregistreerd bij de Kamer van Koophandel in het
> handelsregister onder nummer 41055629.
> The Radboud university medical center is listed in the Commercial Register of
> the Chamber of Commerce under file number 41055629.
>
> ********************************************************************************************************************
>
> This message may contain confidential information. If you are not the intended
> recipient please inform the
> sender that you have received the message in error before deleting it.
> Please do not disclose, copy or distribute information in this e-mail or take
> any action in relation to its contents. To do so is strictly prohibited and may
> be unlawful. Thank you for your co-operation.
>
> NHSmail is the secure email and directory service available for all NHS staff
> in England and Scotland. NHSmail is approved for exchanging patient data and
> other sensitive information with NHSmail and other accredited email services.
>
> For more information and to find out how you can switch,
> https://portal.nhs.net/help/joiningnhsmail
--
Nick Holford, Professor Clinical Pharmacology
Dept Pharmacology & Clinical Pharmacology, Bldg 503 Room 302A
University of Auckland,85 Park Rd,Private Bag 92019,Auckland,New Zealand
office:+64(9)923-6730 mobile:NZ+64(21)46 23 53 FR+33(6)62 32 46 72
email: [email protected]
http://holford.fmhs.auckland.ac.nz/
http://orcid.org/0000-0002-4031-2514
Read the question, answer the question, attempt all questions
Dear Nick,
I was trying to point out that using a model, in this case a model for GFR, to
predict the value of a covariate in a PK model may not be necessary. I don't
know if it would be worse than unnecessary e.g. cause bias, since covariates
enter the model assumed to be measured without error.
Regarding your comment on local fit not implying generalisability, in one of
the examples I cited, Dr Henning's tobramycin model, was built with data on 732
patients and 5,605 PK samples! Ideally I suppose one would want to prove
generalisability by prdicting external data however, so here is an example of
using SECR and allometric/age scaling (no redress to model-predicted
covariates) which beat 11 other published models at predicting a prospectively
collected external dataset representing the population we were interested in:
Germovsek E et al. Development and Evaluation of a Gentamicin Pharmacokinetic
Model That Facilitates Opportunistic Gentamicin Therapeutic Drug Monitoring in
Neonates and Infants. Antimicrob Agents Chemother. 2016 Jul 22;60(8):4869-77.
BW,
Joe
Joseph F Standing
MRC Fellow, UCL Institute of Child Health
Antimicrobial Pharmacist, Great Ormond Street Hospital
Honorary Senior Lecturer, St George's University of London
Tel: +44(0)207 905 2370
Mobile: +44(0)7970 572435
Quoted reply history
________________________________________
From: Nick Holford [[email protected]]
Sent: 07 December 2017 20:58
To: STANDING, Joseph (GREAT ORMOND STREET HOSPITAL FOR CHILDREN NHS FOUNDATION
TRUST); [email protected]; [email protected]
Cc: [email protected]; [email protected]; [email protected]
Subject: Re: [NMusers] Allometric scaling of renal clearance with estimated
glomerular filtration rate
Dear Joe,
On 08-Dec-17 02:00, STANDING, Joseph (GREAT ORMOND STREET HOSPITAL FOR CHILDREN
NHS FOUNDATION TRUST) wrote:
Dear Rob,
Why do you want to use a model to predict the value of a covariate to add into
your model? Apart from glomerular filtration rate, what other situations would
you do this?
I'm not sure what you are trying to say here. What model for GFR are you
thinking about as the only example?
I could mention using a model for FFM based on covariates of WT, HT and SEX as
an example but I don't know if this is what you mean.
Unless I was trying to do some fancy separation of renal and non-renal
clearance,
Unless you want to assume that the drug is completely eliminated renally then
there should always be a "fancy separation" of renal and non-renal clearance. I
don't know of any clear cut case where I could assume a drug can only be
eliminated by the kidneys.
I would simply ignore the fact there is a model to predict glomerular
fltration, and include its component parts e.g.
CL = THETA * (WT/70)**0.75 * FCREAT * FAGE
where FCREAT and FAGE are covariate functions for creatinine (e.g. (SECR/median
value)**THETA ) and age.
No explicit assumption of the pathway of elimination but just an empirical
functions of SCR. This can include the bizarre MDRD and CKD-EPI functions
which include skin colour as a covariate. I consider this kind of empiricism
when there are mechanistic alternatives to be bad science.
Some examples of not using a model to predict GFR still gave an acceptable
model of CL (what we were interested in):
Creatinie e.g.
Hennig S. Population pharmacokinetics of tobramycin in patients with and
without cystic fibrosis. Clin Pharmacokinet. 2013 Apr;52(4):289-301
Cystatin C example:
De Cock PA. Augmented renal clearance implies a need for increased
amoxicillin-clavulanic acid dosing in critically ill children. Antimicrob
Agents Chemother. 2015 Nov;59(11):7027-35.
Just because a model can provide a local fit to the data does not mean it has
good properties for generalization / extrapolation. Incorporating biological
mechanism and sensible extrapolation properties should be used whenever
possible.
Best wishes,
Nick
BW,
Joe
Joseph F Standing
MRC Fellow, UCL Institute of Child Health
Antimicrobial Pharmacist, Great Ormond Street Hospital
Honorary Senior Lecturer, St George's University of London
Tel: +44(0)207 905 2370
Mobile: +44(0)7970 572435
________________________________________
From: [email protected]<mailto:[email protected]>
[[email protected]<mailto:[email protected]>] on behalf
of [email protected]<mailto:[email protected]>
[[email protected]<mailto:[email protected]>]
Sent: 07 December 2017 11:56
To: [email protected]<mailto:[email protected]>
Cc: [email protected]<mailto:[email protected]>;
[email protected]<mailto:[email protected]>;
[email protected]<mailto:[email protected]>;
[email protected]<mailto:[email protected]>
Subject: RE: [NMusers] Allometric scaling of renal clearance with estimated
glomerular filtration rate
Dear Nick, Hans, Ruben, Max,
Great to hear several approaches and opinions on the use of glomerular
filtration approximations in PK modeling and scaling to body size. Thank you!
I have a hard time ignoring the CKD-EPI equations (with or without cystatin C),
as they are well established and proven better predictors for GFR, when
compared to the Cockroft-Gault. In general, sample sizes of pharmacokinetic
studies are smaller than those where the CKD-EPI and MDRD equations were
developed. I am not convinced that developing a new creatinine/cystatin c
equation for GFR for each PK analysis is the right approach. Then again, I also
have a hard time scaling to BSA, as in, for example, obese patients this is
likely a poor body size descriptor to scale renal function.
Also, depending on the population and drug one may choose one equation above
another. For example: if a drug is completely filtrated (no active secretion),
a cystatin C based equation is likely better explain variability in clearance
of completely filtrated drugs (e.g. carboplatin). Another example: in cachectic
patients one may argue that there is not enough muscle mass (and thus serum
creatinine) to provide accurate GFR estimations and then creatinine-independent
equations may provide better equations.
Thinking about this the last couple of days and with your feedback, I am
inclined to choose the equation based on population (e.g. cachectic or not?)
and drug (e.g. filtration/active secretion) and, if the equation scales renal
function to BSA, convert it to scaling to FFM. Nonetheless, open to any other
suggestion or discuss cons and pro's anytime!
Sincerely,
Rob
-----Oorspronkelijk bericht-----
Van: [email protected]<mailto:[email protected]>
[mailto:[email protected]] Namens Nick Holford
Verzonden: woensdag 6 december 2017 20:06
Aan: [email protected]<mailto:[email protected]>
Onderwerp: Re: [FORGED] [NMusers] Allometric scaling of renal clearance with
estimated glomerular filtration rate
Hi Rob,
Thanks for bringing this up again. I don't think much has changed since I wrote
this in 2013
( http://cognigencorp.com/nonmem/current/2013-August/4697.html)
1. Theory Based Allometry or Surface Area
"Note that using surface area as a form of size standardization forglomerular
filtration rate has no theoretical nor experimental support when compared to
theory based allometry (Rhodin et al. 2009). So I donot agree with
standardizing CLCR to 1.73 m^2. I know this is frequently done but in fact this
is just based on tradition and an out of datetheory of scaling based on surface
area (see Anderson & Holford 2008)."
There is no biological or experimental support for using surface area to scale
renal function markers such as GFR and CLcr. In contrast, there is strong
biological based theory and experimental support for using theory based
allometry (see Holford & Anderson 2017 for a recent review).
2. Mechanism Based Models for CLcr
I also wrote in 2013:
"The MDRD method of predicting glomerular filtration rate is astatistical
absurdity which does not include any measurement of size for its prediction. I
would certainly not recommend using it for anyscientific purpose. "
This applies equally well to the CKD-EPI method. Let me explain why it is a
absurdity generated by a naive statistician using CLcr as an example.
CLcr can be calculated from the creatinine excretion rate (CER) and the serum
creatiniine. This is based on the definition of clearance and is true without
any assumptions.
CLcr=CER/Scr
If we then assume Scr is at steady state then CER will be equal to creatinine
production rate (CPR) and we can use this:
CLcr=CPR/Scr
All rational models for predicting CLcr without measurement of CER use models
to predict CPR e.g.
CPR=(140-Age)*Weight/72 use Cockcroft & Gault to predict CPR in males then
CLcr=CPR/Scr is Cockcroft & Gault CLcr ml/min
Dividing CPR by Scr gives the CLcr. This can be written equivalently but less
clearly:
CLcr=CPR*Scr^-1
The empirical models such as MDRD and CKI-EPI (see below) involve the absurdity
of estimating the known exponent for Scr of -1. These estimates must be wrong
based on the theory I have outlined above (unless the estimate is exactly -1).
The reported estimates are -1.209 for CKI-EPI and -1.154 for MDRD.
In addition, and more importantly,they have no direct measure of body size
which seriously limits the value outside the typical weight distribution and
they are only applicable to adults. GFR can be described from premature
neonates to adults using theory based allometry and maturation based on
post-menstrual age so GFR predicttions should try to follow the concepts used
there (Rhodin 2008).
So what to do?
First -- don't use MDRD or CKI-EPI unless you are sure you are applying them to
a population similar to that used to develop these empirical predictions. You
could add allometric scaling to the eGFR by assuming the 1.72m^2 value is
equivalent to 70 kg with a fat free mass (FFM) of
56.1 kg. Then scaling the eGFR by (WT/70)^(3/4) or (FFM/56.1)^(3/4).
I use the Schwartz (1992) equations for neonates, children and teenagers then
the Matthews (2004) equation for adults. I am working on an integrated method
for CPR prediction which was presented as a work in progress at PAGE this year.
Watch this space...
Best wishes,
Nick
MDRD
eGFR =175 x (SCr)^-1.154 x (age)-0.203 x 0.742 [if female] x
1.212 [if Black]
CKI-EPI
eGFR = 141 x min(SCr/k, 1)^alpha x max(SCr /kappa, 1)^-1.209 x 0.993^Age
x 1.018 [if female] x 1.159 [if Black]
kappa = 0.7 (females) or 0.9 (males)
alpha = -0.329 (females) or -0.411 (males)
eGFR (estimated glomerular filtration rate) = mL/min/1.73 m2; SCr (standardized
serum creatinine) = mg/dL
Holford NHG, Anderson BJ. Allometric size: The scientific theory and
extension to normal fat mass. Eur J Pharm Sci. 2017;109(Supplement):S59-S64.
Rhodin MM, Anderson BJ, Peters AM, Coulthard MG, Wilkins B, Cole M,
Chatelut E, Grubb A, Veal GJ, Keir MJ, Holford NH
Human renal function maturation – a quantitative description using
weight and postmenstrual age. Pediatr Nephrol. 2008
Schwartz GJ. Does kL/PCr estimate GFR, or does GFR determine k? Pediatr
Nephrol. 1992;6(6):512-5.
Matthews I, Kirkpatrick C, Holford N. Quantitative justification for
target concentration intervention -- parameter variability and
predictive performance using population pharmacokinetic models for
aminoglycosides. Br J Clin Pharmacol. 2004;58(1):8-19.
Holford N, Sherwin CM. Scaling renal function in neonates and infants to
describe the pharmacodynamics of antibiotic nephrotoxicity. PAGE 26
Abstr 7208 [wwwpage-meetingorg/?abstract=7208]. 2017.
On 06-Dec-17 23:52, [email protected]<mailto:[email protected]>
wrote:
Hi Ruben,
Interesting work, Ruben. One may indeed question the validity of
glomerular filtration rate markers like cystatin C (that is only
filtrated and not actively secreted) to predict PK of drugs that
undergo active tubular secretion in patients with decreased renal
function. When glomerular filtration rate drops, the relative
contribution of active tubular secretion to renal clearance increases.
To me, it appears logical that creatinine is a better marker for
clearance drugs that are actively secreted, as creatinine also
undergoes active tubular secretion.
Nonetheless, I’m also interested whether other people have considered
allometric scaling of MDRD/CKD-EPI derived GFR’s?
Cheers,
Rob
*Van: *Ruben Faelens <[email protected]><mailto:[email protected]>
*Datum: *dinsdag 5 december 2017 om 7:13 PM
*Aan: *"Heine, Rob ter"
<[email protected]><mailto:[email protected]>
*CC: *"[email protected]"<mailto:[email protected]>
<[email protected]><mailto:[email protected]>
*Onderwerp: *Re: [NMusers] Allometric scaling of renal clearance with
estimated glomerular filtration rate
Dear Rob,
At PMX Benelux, there was an interesting talk about the correlation
between different metrics describing renal function by Stijn Jonckheere.
A part of the work presented was published:
https://academic.oup.com/jac/article/71/9/2538/1750427
https://academic.oup.com/jac/article/71/9/2538/1750427 https://academic.oup.com/jac/article/71/9/2538/1750427
This may provide some perspective, or rather complicate things even
more, depending on your viewpoint.
Best regards
Ruben Faelens
On 06-Dec-17 06:17, [email protected]<mailto:[email protected]>
wrote:
Dear all,
I am wondering what your thoughts are on the allometric scaling of
clearance of renally extreted drugs, where we have estimations renal
function.
Simply scaling the predicted glomerular filtration rate from, for
example, the Cockroft-gault equation seems inappropriate, since weight
is already a part of the equation. Standardizing this to weight in the
Cockroft-gault equation can be done, a solution has been discussed
here: http://cognigencorp.com/nonmem/current/2013-August/4697.html
However, in the recent years some new equations to calculate
glomerular filtration rate from endogenous markers have emerged. For
example the CKD-EPI CREATININE CYSTATIN C equation
https://www.kidney.org/content/ckd-epi-creatinine-cystatin-equation-2012
. As the addition of a muscle mass independent endogenous marker like
cystatin C is known to provide better estimations of GFR in, for
example, cachectic patients, it is likely that this equation may
outperform to predict renally filtrated compounds in this patient
group. It is rather odd that this CKD-EPI equation does not contain
any measure of body size. The outcome of this equation is a GFR scaled
to a BSA of 1.73m^2.
I am wondering how you would allometrically scale the eGFRs from these
CKD EPI equations to, for example, fat-free mass.
Cheers!
Rob
R. ter Heine, PhD, PharmD
Hospital Pharmacist-Clinical Pharmacologist
Radboudumc, Nijmegen, The Netherlands
Het Radboudumc staat geregistreerd bij de Kamer van Koophandel in het
handelsregister onder nummer 41055629.
The Radboud university medical center is listed in the Commercial
Register of the Chamber of Commerce under file number 41055629.
--
Nick Holford, Professor Clinical Pharmacology
Dept Pharmacology & Clinical Pharmacology, Bldg 503 Room 302A
University of Auckland,85 Park Rd,Private Bag 92019,Auckland,New Zealand
office:+64(9)923-6730 mobile:NZ+64(21)46 23 53 FR+33(6)62 32 46 72
email:[email protected]<mailto:email:[email protected]>
http://holford.fmhs.auckland.ac.nz/
http://orcid.org/0000-0002-4031-2514
Read the question, answer the question, attempt all questions
Het Radboudumc staat geregistreerd bij de Kamer van Koophandel in het
handelsregister onder nummer 41055629.
The Radboud university medical center is listed in the Commercial Register of
the Chamber of Commerce under file number 41055629.
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Nick Holford, Professor Clinical Pharmacology
Dept Pharmacology & Clinical Pharmacology, Bldg 503 Room 302A
University of Auckland,85 Park Rd,Private Bag 92019,Auckland,New Zealand
office:+64(9)923-6730 mobile:NZ+64(21)46 23 53 FR+33(6)62 32 46 72
email: [email protected]<mailto:[email protected]>
http://holford.fmhs.auckland.ac.nz/
http://orcid.org/0000-0002-4031-2514
Read the question, answer the question, attempt all questions
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any action in relation to its contents. To do so is strictly prohibited and may
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