Baseline correction examples [Regulatives / Guidelines]

posted by Helmut Homepage – Vienna, Austria, 2015-09-18 19:28 (3114 d 06:53 ago) – Posting: # 15432
Views: 18,983

Hi Lucas,

❝ Two questions though:

❝ 1. Do you know a example of a endogenous substance that has a constant (or nearly constant enough) baseline level in the first example of yours?


I’m too lazy to browse the FDA’s product specific guidances, but you will find examples.
If you have evidence that the BL is stable over the day you may subtract average predose levels – measured in each period. This is what my example is based upon. The EMA’s GL states:

The exact method for baseline correction should be pre-specified and justified in the study protocol. In gen­er­al, the standard subtractive baseline correction method, […] subtraction of the mean of in­di­vi­du­al endogenous pre-dose concentrations […]

Which mean? Though often applied I hope not the arithmetic one. The geometric would be better but what if at least of the values is BQL? I always use the median and never got any requests.
BTW, be aware of softwares’ interpretation of non-numerics like "BQL". Example: 5.0, 7.0, "BQL"

                  Excel  PHX/WNL   R
arithmetic mean    6.0     6.0    NA
geometric mean     5.9     5.9    Error
median             6.0     6.0    "7.0"

Excel ignores the "BQL" and works with the numbers only. Same in PHX/WNL but we get the information that 2 values are used and 1 is missing. R essentially gives up.

❝ 2. I see that you only considered one baseline profile. We wouldn't have to measure the baseline level before each period of the study because we ate assuming that the cycle is the same through time. Right? But what about feminine hormones produced in a 28-day cycle?


Hey funny – coincidentally this afternoon I was working on this post and missed yours. ;-) In a 2-period study likely I would sample a complete baseline prior to each period myself. However, if there are more periods you would end up with an extreme blood volume. Agencies’ standard phrase “improve the analytical method” sometimes is not realistic.

If I switch the amplitudes of my other example (flucations within the day lower than within the 28-days cycle) I got:

method     1     2      1     2 
period       AUCt         Cmax   
  1      +3.24 -0.10  +1.59 -0.08
  2      -0.74 -2.28  -0.22 -0.55
  3      -3.20 -3.22  -1.59 -0.25
  4      -0.74 -2.28  +0.22 +0.21

No method is “perfect”. What about performing such a study in postmenopausal women?

❝ I've also seen a lot of what you've described in the last graph, our triangulation points (or embedded concentrations) that we've discussed. :-D


Don’t remind me, please. :cool:


PS. Too bad that GL’s don’t allow modeling… Should be an easy task to estimate parameters even for composite sinusoidal baselines. We need three for the circadian rhythm and four for the one with a lower frequency. Try this:

a <- c( 3.5,  1.5, 1)     # parameters for circadian rhythm
b <- c(15  , 10  , 0, 28) # parameters for 28-days cycle
t  <- -24:(27*24)
BL <- a[1]+a[2]*sin(pi/180*(t+a[3])/24*360) +
      b[1]+b[2]*sin(pi/180*(t+b[3])/24*360/b[4])
plot(t/24, BL, type="l", ylim=c(0, sum(c(a[1:2], b[1:2]))), xlab="days")
abline(v=0, lty=3)

If you have data of a study with one full baseline profile and predose concentrations in the other periods, give it a try in Phoenix!

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