RE: Rational of using IOV
Dear Thierry,
The article below nicely describes the importance of incorporating IOV since
it otherwise might lead to a falsely optimistic impression of the potential
value of TDM.
Karlsson MO, Sheiner LB. The importance of modeling interoccasion
variability in population
pharmacokinetic analyses. J Pharmacokinet Biopharm. 1993 Dec;21(6):735-50.
Best regards,
Ulrika
Ulrika Simonsson, PhD
Assoc Prof of Pharmacometrics
Uppsala Pharmacometrics
Department of Pharmaceutical Biosciences
Uppsala University
BMC, Box 591, 751 24 Uppsala
Sweden
Quoted reply history
From: [email protected] [mailto:[email protected]] On
Behalf Of Buclin Thierry
Sent: den 1 november 2010 14:35
To: [email protected]
Subject: RE: [NMusers] Rational of using IOV
Dear James,
I always thought that intra-individual variability (IIV) classically
represented the immovable limit on the gains to be expected from TDM IOV
being indeed used only in a minority of population PK analyses. Both intra-
and inter-occasion variability actually represent nuisance. We agree on the
point that specifying an IOV term in a model will decrease the residual IIV.
But wouldnt this precisely give a falsely favorable impression about
potential gains from a TDM program? Am I wrong to think so?
Kind regards
Thierry
De : James G Wright [mailto:[email protected]]
Envoyé : lundi, 1 novembre 2010 14:04
À : Buclin Thierry
Objet : Re: [NMusers] Rational of using IOV
Dear Thierry,
I hope you are well. I think you are right to highlight the importance of
IOV for TDM, but I would argue it is very important to include it in the
model. This is because IOV places an immovable limit on the gains from TDM.
The classic error is to develop a TDM strategy mistakenly lumping IOV with
IIV, and drastically over-estimating the utility of TDM.
Best regards, James
On 01/11/2010 11:55, Buclin Thierry wrote:
Hi Nicolas
My short answer would be another question: what is the aim of your analysis
?
IOV is fine to split variability into inter-individual,
intra-individual-inter-occasion and intra-individual-intra-occasion random
components. This is excellent for data description, and can bring
interesting insight into the mechanisms explaining variability. But if you
want to use your results for prediction, e.g. to devise a TDM program, you
wont be able to draw relevant information from IOV: a blood sample obtained
in a patient on a certain occasion wont inform you on your patients
behavior on another occasion; in this situation, a model merely
distinguishing inter-individual and intra-individual variability components
is easier to exploit. Thus, there may be good reasons not to use IOV even
when it would be possible.
Kind regards
Thierry
Thierry Buclin, MD, PD,
Division of Clinical Pharmacology and Toxicology
University Hospital of Lausanne (CHUV)
Lausanne - SWITZERLAND
tel +41 21 314 42 61
fax +41 21 314 42 66
On 1/11/2010 10:53 a.m., Nicolas SIMON wrote:
Dear colleagues,
could someone give me an advice about the rational of using IOV in a
particular circumstance?
We have data from a clin trial with 3 occasions for each patient. It was a
chemotherapy and the patients have received up to 7 cures. The issue is that
the 3 occasions differ from one patient to another.
Patient X may have be seen on cure 3, 5 and 7 while patient X+1 was seen on
cure 2, 5 and 6 or whatever...
It seems to me that combining the 1st occ of all patients is meaningless (as
for 2nd and 3rd).
Shall we use as many occasions as cures (7 in our dataset)? In that case,
how many patients by occ is relevant as a minimum? For certain occ we may
have few patients. Combining cures is hazardous and has no clinical
justification.
Best regards
Nicolas
Pr Nicolas SIMON
Universite de la Mediterranee (Aix-Marseille II)
--
James G Wright PhD,
Scientist, Wright Dose Ltd
Tel: UK (0)772 5636914