Rational of using IOV
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 won't be able to draw
relevant information from IOV: a blood sample obtained in a patient on a
certain occasion won't inform you on your patient's 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
Quoted reply history
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)