Bioequivalence and Bioavailability Forum • Graphing Mean PK profile

Graphing Mean PK profile [🇷 for BE/BA]

posted by Helmut – Vienna, Austria, 2019-04-24 15:50 (2048 d 03:43 ago) – Posting: # 20225
Views: 15,026

Hi roman_max,

❝ ❝ The sponsor should re-consider this idea. Box-plots are nonparametric. For log-normal distributed data (which we likely have) the median is an estimate of the geometric mean. If we want to go this way, the arithmetic mean is not a good idea.

❝

❝ Agree, but if it is easier for Sponsor to view and "understand" data, no problem.

Any kind of plot is problematic. Given, some guidelines require them (e.g., the Canadian guidance). We should be aware that such a plot gives just an impression and is not related with the assessment of BE.
I once received a deficiency letter asking for a clarification why in plots of geometric mean profiles the highest concentrations and their time points didn’t agree with the reported C_max/t_max. Well, C at any given time point has nothing to do with the individual C_max-values and their geometric mean. Oh, dear!
There’s another obstacle. How to deal with BQLs? If you set them to NA (in R) or keep them as a character-code (Phoenix/WinNonlin) you open Pandora’s box. Let’s have a look at the 16 h time point of my example:

loc.stat <- function(x, type, na.rm) {

  non.numerics    <- which(is.na(suppressWarnings(as.numeric(x))))

  x[non.numerics] <- NA

  x <- as.numeric(x)

  switch(type,

         arith.mean = round(mean(x, na.rm=na.rm), 2),

         median     = round(median(x, na.rm=na.rm), 2),

         geom.mean  = round(exp(mean(log(x), na.rm=na.rm)), 2),

         harm.mean  = round(length(x)/sum(1/x, na.rm=na.rm), 2))

}

C <- c(rep("BQL", 2), 9.87, rep("BQL", 2), 15.4, 13.0, 35.2,

       rep("BQL", 4), 9.91, 9.43, rep("BQL", 2), 16.6, rep("BQL", 4),

       5.69, 21.2, 10.4)

df <- data.frame(statistic=c(rep("arith.mean", 2), rep("median", 2),

                 rep("geom.mean", 2), rep("harm.mean", 2)),

                 na.rm=rep(c(FALSE, TRUE), 4),

                 location=NA, stringsAsFactors=FALSE)

for (j in 1:nrow(df)) {

  df$location[j] <- loc.stat(C, df$statistic[j], df$na.rm[j])

}

print(df, row.names=FALSE)



  statistic na.rm location

 arith.mean FALSE       NA

 arith.mean  TRUE    14.67

     median FALSE       NA

     median  TRUE    11.70

  geom.mean FALSE       NA

  geom.mean  TRUE    12.98

  harm.mean FALSE       NA

  harm.mean  TRUE    27.98 # not meaningful, only for completeness

Some people set all BQLs to zero in order to calculate the arithmetic mean. Others set the first BQL after t_max to LLOQ/2, and, and, and… There will always be a bias.

—
Dif-tor heh smusma 🖖🏼 Довге життя Україна!
Helmut Schütz

The quality of responses received is directly proportional to the quality of the question asked. 🚮
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Complete thread:

Graphing Mean PK profile roman_max 2019-04-23 16:01 [🇷 for BE/BA]
- Graphing Mean PK profile Shuanghe 2019-04-23 18:31
  - Graphing Mean PK profile roman_max 2019-04-24 12:29
- Graphing Mean PK profile Helmut 2019-04-23 22:23
  - Graphing Mean PK profile nobody 2019-04-24 11:23
    - Graphing Mean PK profile Helmut 2019-04-24 11:49
      - Graphing Mean PK profile nobody 2019-04-24 11:53
        
        Graphing Mean PK profile Helmut 2019-04-24 12:32
        
        Graphing Mean PK profile nobody 2019-04-24 12:49
  - Graphing Mean PK profile roman_max 2019-04-24 12:36
    - Graphing Mean PK profileHelmut 2019-04-24 13:50
      - Graphing Mean PK profile nobody 2019-04-24 14:15
        
        Graphing Mean PK profile Helmut 2019-04-24 14:41
        
        Pasta Ohlbe 2019-04-25 12:47
        
        Pasta nobody 2019-04-25 14:36
        Spaghetti Viennese Helmut 2019-04-25 14:39
        
        Spaghetti Viennese nobody 2019-04-25 15:08
        
        OT: Blume/Mutschler Helmut 2019-04-25 15:32
        
        OT: Blume/Mutschler nobody 2019-04-25 15:43
  - A lie is a lie is a lie ... d_labes 2019-04-25 19:59