RE: truncation & simulation
Steven,
While I agree that simulation of a larger number of subjects will result in
a wider range of clearance I have my doubts that that alone would be
sufficient to account for a 50-fold increase in range (5 to 30 vs 1 to 300).
Another contributing factor is that the post hoc estimates will have some
shrinkage because of empirical Bayes estimation (variance of post hoc
estimates of clearance will be smaller than the estimate of omega for
clearance). But again, I doubt that either of these explanations will fully
account for this 50-fold discrepancy. I still think Ron should look more
carefully at how the random effects are being modeled and further assess
whether his model can adequately describe the variability before using this
model in clinical trial simulations.
Ken
Quoted reply history
-----Original Message-----
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On
Behalf Of Troy, Steven
Sent: Tuesday, April 22, 2008 5:00 PM
To: Ron Mathôt
Cc: [email protected]
Subject: RE: [NMusers] truncation & simulation
Dear Ron,
Your original dataset provided clearance estimates for 100 patients, which
were all within the range 5 to 30 L/h. When you simulated 4800 clearance
values (= 2 cross-over observations/subject x 12 subject/trial x 200
trials), I would expect to see a wider range of clearance values in the
simulation dataset than in the original analysis, simply because there are
many more observations in the simulation dataset.
However, arbitrarily truncating clearance to the range of 5 to 30 L/h may
not be wise. Consider the subject whose simulated clearance values are 30
L/h and 32 L/h, a 6.7% difference. If both of these values are truncated to
30 L/h, then there is zero within-patient difference in clearance values
(and zero within-patient difference in AUC), and the truncation procedure
both (1) reduces the mean within-subject treatment difference and (2)
reduces the within-subject treatment variability. Either one of these
effects would arbitrarily increase the statistical power of attaining
bioequivalence.
Statistical power for a bioequivalence test depends on the projected mean
within-subject treatment difference (say <=5%), the projected mean
within-subject variability (estimated in your original population PK
analysis), and the sample size. Instead of truncating clearance values, I
think you should examine the effects of larger sample sizes on the
statistical power; maybe run simulations with 16, 24, 36, and 48 subjects
per study. In reality, very few bioequivalence trials will be successful
with only 12 subjects.
Good luck,
Steve
Steven Troy
Sr. Director,
Clinical Pharmacology and Pharmacokinetics
Shire Pharmaceuticals
-----Original Message-----
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On
Behalf Of Ron Mathôt
Sent: Tuesday, April 22, 2008 3:18 PM
To: [email protected]
Subject: [NMusers] truncation & simulation
Dear NONMEM users,
Currently I am working on the simulation of a bio-equavalence trial. For
the reference compound a population PK model has been derived on basis
of data from 100 patients. Values for between-and within-patient
variability are available for all PK parameters. The simulation
comprises a randomized cross-over study with 12 patients taking the
test and reference compound. Two-hunderd trials are simulated and
summarized. During the simulations I noticed that truncation of the
simulated of PK parameters significantly influences the power of the
study to confirm bio-equivalence. For instance truncation of simulated
oral clearances of both compounds from a range of 1-300 L/hr to 5 - 30
L/hr doubled the number of positive trials (due to decreased within-
patient variability). Post-hoc estimates form the popPK study indicated
that clearance values of the reference compound are all within the
latter range of 5 to 30 L/hr. I expect that oral clearance of the test
compound will not differ more than 5% from the reference compound. In my
opinion simulation of trials with the smallest range will produce more
reliable estimates of the power to detect bio-equivalence.
I would greatly appreciate your comments on this subject.
Best regards,
Ron Mathôt
Department of Hospital Pharmacy and Clincal Pharmacology
Erasmus University Medical Center
Rotterdam
The Netherlands
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