RE: Plcebo Corrected PK/PD

From: "Gobburu, Jogarao V" GOBBURUJ@cder.fda.gov Subject: RE: [NMusers] Plcebo Corrected PK/PD Date: Wed, March 2, 2005 1:47 pm Dear Manoj, The answer really depends on the experimental design and the modeling objective. In principle, I agree with Bill's statements. Unfortunately, we deal with designs that might not allow anything better than subtracting mean placebo responses. If you are dealing with data from a fixed-dose, parallel trial, then the only way to adjust for placebo effect is by subtracting the mean of the groups (placebo vs. trt). You could use population mean or typical placebo responses for determining the drug effect. Even if the placebo response has a rhythm to it, if you determine the drug effect by time (instead of modeling the placebo response) your analysis would be equivalent to modeling all data simultaneously (provided all you are interested in is the drug effect size+?variance). What you will lose is the ability to simulate the placebo effects for future trials. There are some other advantages such as handling missing data and unbalanced observations. You seem to be concerned about the variability in the placebo group. If you do not have a cross-over design, you simply cannot estimate the true variability in the drug effect. You are stuck to using population means or typical values for placebo effect. No modeling can help you with it. As a general practice you should always account for placebo effects. You should have a reason to exclude placebo data (e.g.: no signal over the trial duration). Most primary endpoints have placebo effects, while several biomarkers might not have a placebo effect. Placebo data allows you to estimate the intercept of the exposure-response model and duration of effect (I am sure you already know this). Hope this is helpful. Regards, Joga