RE: BOV

From: Nick Holford Date: September 21, 2004 technical Source: cognigencorp.com
From: "Nick Holford" n.holford@auckland.ac.nz Subject: RE: [NMusers] BOV Date: Tue, September 21, 2004 3:47 pm Ken, I don't agree with your assertion that the model would necessarily be overparameterized if one estimated a different BOV for each occasion. The way I interpret Pravin's formulae for occasion specific '%CV of Pi' is that it computes the occasion specific total variability estimated by averaging across all subjects for any given occasion. The replication of each occasion comes from having several subjects for each occasion. Consider this 'thought experiment': A constant rate infusion of a drug is given to a group of subjects. Concentrations are measured on each occasion at a time when steady state for that occasion can be assumed. Clearance (CLi,n) is readily calculated on each occasion (n) for each subject (i) from the infusion rate and the measured Css. Assume there is no systematic change in clearance from occasion to occasion. For simplicity let us also assume that CL is normally distributed between and within subjects. We can estimate the mean subject specific clearance by averaging the CLi,n estimates over all occasions for each subject (CLAVGi). The SD of all the estimates of CLAVGi is BSV. Now we calculate the SD of all CLi,n estimates on a specific occasion -- call this PPVn for occasion n. It is the sum of the between subject and occasion specific (within subject) variability. This corresponds to the '%CV of Pi' defined by Pravin if one ignores the '%' and '*100'. The occasion specific BOVn can now be calculated from SQRT(PPVn^2 - BSV^2). Thus I would conclude it is possible to estimate BOV separately for each occasion given an adequate design for estimation of the parameter in each subject on each occasion. The BLOCK(x) SAME construction is a helpful NONMEM option when one wishes to assume that BOV is the same for all occasions. It is not a requirement that one use this when estimating BOV. Indeed one might consider that it should be a SOP to explicitly test if the SAME assumption is supported by the data when estimating BOV. Nick -- Nick Holford, Dept Pharmacology & Clinical Pharmacology University of Auckland, 85 Park Rd, Private Bag 92019, Auckland, New Zealand email:n.holford@auckland.ac.nz tel:+64(9)373-7599x86730 fax:373-7556 http://www.health.auckland.ac.nz/pharmacology/staff/nholford/
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