In ggPMXdevelopment/ggPMX: 'ggplot2' Based Tool to Facilitate Diagnostic Plots for NLME Models

knitr::opts_chunk$set(echo = TRUE)
library(ggPMX)

Introduction

Censoring occurs when the value of a measurement or observation is only partially known.

• The lower limit of detection LLOD is the lowest quantity of a substance that can be distinguished from its absence.

• A measuring device can also have an upper limit of quantification ULOQ such that any value above this limit cannot be measured and reported.

We usually distinguish between three types of censoring:

• left
• right
• interval.

MONOLIX Censored observations

To define that a measurement is censored, the observation data set should include a CENSORING column ( default to CENS ) and put :

• 1 for lower limit.
• -1 for upper limit

Optionally, data set can contain have a limit column ( default to LIMIT) column to set the other limit.

Censored data appear in a different color (red by default).

There are two options regarding the way censored data can be displayed:

• a. BLOQ (limit of quantification) values or ULOQ (upper limit of quantification (the points at y=84)):

• b. BLQ data can also be displayed as Simulated BLQ data. In that case, the model is used to predict the censored values:

Explain that NPDE are based on simulated, DV vs PRED are based on observed.

pmx_bloq

Within ggPMX, to define a bloq we use pmx_bloq function.

str(pmx_bloq(),1)

This will create a pmxBLOQ object that defines the censoring and column definition and some graphical parameters. In the following ,we will show the use of it through some examples.

PK data below a lower limit of quantification

Left censored data

mlx_file <- "/home/agstudy/Downloads/2.2.censored_data/censoring1log_project.mlxtran"
ctr <- pmx_mlxtran(file_name=mlx_file)

ctr %>% pmx_plot_individual(
  is.draft = FALSE,
  facets=list(ncol=3,nrow=2),
  bloq=pmx_bloq()
)
ctr %>% pmx_plot_iwres_time(bloq=pmx_bloq(color="blue"))
ctr %>% pmx_plot_dv_ipred(bloq=pmx_bloq(color="white"))

Interval censored data

mlx_file <- "/home/agstudy/Downloads/2.2.censored_data/censoring1_project.mlxtran"
ctr <- pmx_mlxtran(file_name=mlx_file)

ctr %>% pmx_plot_individual(
  is.draft = FALSE,
  facets=list(ncol=3,nrow=2),
  bloq=pmx_bloq()
)

PK data below a lower limit of quantification or below a limit of detection

mlx_file <- "/home/agstudy/Downloads/2.2.censored_data/censoring2_project.mlxtran"
ctr <- pmx_mlxtran(file_name=mlx_file)

ctr %>% pmx_plot_individual(
  is.draft = FALSE,
  facets=list(ncol=3,nrow=2),
  bloq=pmx_bloq()
)

PK data below a lower limit of quantification and PD data above an upper limit of quantification

mlx_file <- "/home/agstudy/Downloads/2.2.censored_data/censoring3_project.mlxtran"
ctr <- pmx_mlxtran(file_name=mlx_file,endpoint="2")

ctr %>% pmx_plot_individual(
  is.draft = FALSE,
  facets=list(ncol=3,nrow=2),
  bloq=pmx_bloq()
)

Combination of interval censored PK and PD data

Pk data

mlx_file <- "/home/agstudy/Downloads/2.2.censored_data/censoring4_project.mlxtran"
ctr <- pmx_mlxtran(file_name=mlx_file,endpoint="1")

ctr %>% pmx_plot_individual(
  is.draft = FALSE,
  facets=list(ncol=3,nrow=2),
  bloq=pmx_bloq()
)

PD data

mlx_file <- "/home/agstudy/Downloads/2.2.censored_data/censoring4_project.mlxtran"
ctr <- pmx_mlxtran(file_name=mlx_file,endpoint="2")

ctr %>% pmx_plot_individual(
  is.draft = FALSE,
  facets=list(ncol=3,nrow=2),
  bloq=pmx_bloq()
)

ggPMXdevelopment/ggPMX documentation built on Dec. 11, 2023, 5:24 a.m.