Disposition Table

In metalite.sl: Subject-Level Analysis Using 'metalite'

knitr::opts_chunk$set(
  comment = "#>",
  collapse = TRUE,
  out.width = "100%",
  dpi = 150
)

library(metalite.sl)
library(metalite)
library(dplyr)

Create Disposition Table

The objective of this tutorial is to generate a production-ready Disposition table specification analyses.

This report produces a table that contains counts and percentage of disposition for the participants in population for overall study. To accomplish this using metalite.sl, four essential functions are required:

• prepare_disposition ():subset data for disposition analysis.

• format_disposition(): prepare analysis outdata with proper format.

• rtf_disposition (): transfer output dataset to RTF table.

An example output:

knitr::include_graphics("pdf/disposition.pdf")

Example data

Within metalite.sl, we utilized the ADSL datasets from the metalite package to create an illustrative dataset. The metadata structure remains consistent across all analysis examples within metalite.sl. Additional information can be accessed on the metalite package website.

Build a metadata

adsl <- r2rtf::r2rtf_adsl
adsl$TRTA <- adsl$TRT01A
adsl$TRTA <- factor(adsl$TRTA,
  levels = c("Placebo", "Xanomeline Low Dose", "Xanomeline High Dose"),
  labels = c("Placebo", "Low Dose", "High Dose")
)

# Create a variable EOSSTT indicating the end of end of study status
adsl$EOSSTT <- sample(
  x = c("Participants Ongoing", "Discontinued"),
  size = length(adsl$USUBJID),
  prob = c(0.8, 0.2), replace = TRUE
)
adsl[adsl[["EOSSTT"]] == "Discontinued", "DCSREAS"] <- sample(
  x = c("Adverse Event", "I/E Not Met", "Withdrew Consent", "Lack of Efficacy"),
  size = length(adsl[adsl[["EOSSTT"]] == "Discontinued", "USUBJID"]),
  prob = c(0.7, 0.1, 0.1, 0.1), replace = TRUE
)

# Create a variable EOTSTT1 indicating the end of treatment status part 1
adsl$EOTSTT1 <- ifelse(adsl$DISCONFL == "Y", "Discontinued", "Completed")
adsl$DCTREAS <- ifelse(adsl$EOTSTT1 == "Discontinued", adsl$DCREASCD, NA)
head(adsl)

plan <- plan(
  analysis = "disp", population = "apat",
  observation = "apat", parameter = "disposition;medical-disposition"
)

meta <- meta_adam(
  population = adsl,
  observation = adsl
) |>
  define_plan(plan = plan) |>
  define_population(
    name = "apat",
    group = "TRTA",
    subset = quote(SAFFL == "Y")
  ) |>
  define_parameter(
    name = "disposition",
    var = "EOSSTT",
    label = "Trial Disposition",
    var_lower = "DCSREAS"
  ) |>
  define_parameter(
    name = "medical-disposition",
    var = "EOTSTT1",
    label = "Participant Study Medication Disposition",
    var_lower = "DCTREAS"
  ) |>
  define_analysis(
    name = "disp",
    title = "Disposition of Participant",
    label = "disposition table"
  ) |>
  meta_build()

Click to show the output

meta

Analysis preparation

The function prepare_disposition() is written to prepare data for subject disposition analysis.The function takes four arguments:

Meta is metadata object created by metalite and it contains data from ADSL. Analysis, Population, and Parameter arguments are used to subset and process the meta data. They have default values, which rely on the meta data object.

The function assign default value Analysis to prepare_disposition, Population to the population value associated with the prepare_disposition analysis in meta plan, and parameter to the parameter(s) associated with the prepare_disposition analysis in meta$plan.

However, the user can also manually specify the analysis, population, and parameter values when calling the function, if they want to override the default values.

In the body of the function, it calls another function prepare_sl_summary with the same meta, analysis, population, and parameter arguments. prepare_sl_summary takes the meta data, subsets it based on the analysis, population, and parameter values, and then calculates and returns a summary of the relevant data.

The result of prepare_sl_summary is then returned as the result of prepare_disposition.

The resulting output of the function prepare_disposition() comprises a collection of raw datasets for analysis and reporting.

outdata <- prepare_disposition(meta)

Click to show the output

outdata

• parameter: parameter name

outdata$parameter

• n: number of participants in population

outdata$n

The resulting dataset contains frequently used statistics, with variables indexed according to the order specified in outdata$group.

outdata$group

• char_n: number of participants completed vs not completed in each parameter

outdata$char_n

• char_var : name of parameter

outdata$char_var

• char_prop : proportion of subject with disposition

outdata$char_prop

Format output

Once the raw analysis results are obtained, the format_disposition() function can be employed to prepare the outdata,ensuring its compatibility with production-ready RTF tables.

outdata <- outdata |> format_disposition()

Click to show the output

outdata$tbl

RTF tables

The last step is to prepare the RTF table using rtf_trt_compliance.

outdata$tbl <- outdata$tbl %>%
  mutate(name = ifelse(trimws(name) == "Status Not Recorded", "    Status Not Recorded", name))

outdata |>
  rtf_disposition(
    "Source: [CDISCpilot: adam-adsl]",
    path_outdata = tempfile(fileext = ".Rdata"),
    path_outtable = "outtable/disposition.rtf"
  )

knitr::include_graphics("pdf/disposition.pdf")

metalite.sl documentation built on April 3, 2025, 8:52 p.m.