Create an Adverse Events Table
The fourth example produces an Adverse Events table by severity, with treatment groups on separate pages. The report shows statistics for All Adverse Events and System Organ Class/Preferred Term.
Program
Note the following about this example:
- The
libname()function from the libr package makes it easy to load the entire data library. - Functions from the sassy system integrate
nicely with those from the tidyverse.
- The reporter package is
able to wrap treatment groups to separate pages using the
page_wrap property.
- The reporter package is also able to easily handle page breaks, while still respecting the established margins.
library(tidyverse)
library(sassy)
options("logr.autolog" = TRUE,
"logr.notes" = FALSE)
# Get Data ----------------------------------------------------------------
# Get path to temp directory
tmp <- tempdir()
# Get path to sample data
pkg <- system.file("extdata", package = "sassy")
# Open log
lgpth <- log_open(file.path(tmp, "example4.log"))
sep("Prepare Data")
# Create libname for csv data
libname(sdtm, pkg, "csv")
# Load data into workspace
lib_load(sdtm)
sep("Prepare table data")
dat <- sdtm.AE |>
inner_join(select(sdtm.DM, USUBJID, ARM, ARMCD),
c("USUBJID" = "USUBJID"),
keep = FALSE) |>
filter(ARM != "SCREEN FAILURE")
put("Get population counts")
arm_pop <- dat |>
select(USUBJID, ARM) |>
distinct() |>
count(ARM) |>
deframe() |> put()
put ("Create lookup for AE severity")
sevn <- c(MILD = 1, MODERATE = 2, SEVERE = 3) |> put()
put("Subset ADAE for needed rows and columns")
df_sub <- dat |>
mutate(AESEVN = sevn[AESEV]) |>
select(USUBJID, ARM, AESEV, AESEVN, AESOC, AEDECOD) |>
distinct() |>
put()
# Perform Calculations ----------------------------------------------------
put("Create template for needed ARM columns")
col_template <- paste0(c(rep("ARM A_", 3), rep("ARM B_", 3), rep("ARM C_", 3),
rep("ARM D_", 3)), rep(c(1, 2, 3), 3))
put("Identify and count highest severity grade for each subject")
df1 <- df_sub |> arrange(USUBJID, AESOC, AEDECOD, AESEVN) |>
group_by(USUBJID, ARM, AESOC, AEDECOD) |>
mutate(max_sev = ifelse(row_number() == n(), TRUE, FALSE)) |>
filter(max_sev == TRUE) |>
group_by(ARM, AESOC, AEDECOD, AESEVN) |>
summarize(cnt = n()) |>
pivot_wider(names_from = c(ARM, AESEVN),
values_from = cnt,
values_fill = 0) |>
put()
put("Fill in missing columns where there were no events.")
for (nm in col_template) {
if (!nm %in% names(df1))
df1[[nm]] <- 0
}
put(df1)
put("Format counts and percents for each column")
df_events <- df1 |>
transmute(AESOC = AESOC,
AEDECOD = str_to_title(AEDECOD),
`ARM A_1` = fmt_cnt_pct(`ARM A_1`, arm_pop["ARM A"]),
`ARM A_2` = fmt_cnt_pct(`ARM A_2`, arm_pop["ARM A"]),
`ARM A_3` = fmt_cnt_pct(`ARM A_3`, arm_pop["ARM A"]),
`ARM B_1` = fmt_cnt_pct(`ARM B_1`, arm_pop["ARM B"]),
`ARM B_2` = fmt_cnt_pct(`ARM B_2`, arm_pop["ARM B"]),
`ARM B_3` = fmt_cnt_pct(`ARM B_3`, arm_pop["ARM B"]),
`ARM C_1` = fmt_cnt_pct(`ARM C_1`, arm_pop["ARM C"]),
`ARM C_2` = fmt_cnt_pct(`ARM C_2`, arm_pop["ARM C"]),
`ARM C_3` = fmt_cnt_pct(`ARM C_3`, arm_pop["ARM C"]),
`ARM D_1` = fmt_cnt_pct(`ARM D_1`, arm_pop["ARM D"]),
`ARM D_2` = fmt_cnt_pct(`ARM D_2`, arm_pop["ARM D"]),
`ARM D_3` = fmt_cnt_pct(`ARM D_3`, arm_pop["ARM D"])) |>
arrange(AESOC, AEDECOD) |>
ungroup() |>
put()
put("Get counts for All Adverse Events")
df2 <- df_sub |>
select(USUBJID, ARM, AESEVN) |>
arrange(USUBJID, AESEVN) |>
group_by(USUBJID) |>
mutate(max_sev = ifelse(row_number() == n(), TRUE, FALSE)) |>
filter(max_sev == TRUE) |>
group_by(ARM, AESEVN) |>
summarize(cnt = n()) |>
pivot_wider(names_from = c(ARM, AESEVN),
values_from = cnt,
values_fill = 0) |>
ungroup() |>
put()
put("Fill in missing columns where there were no events.")
for (nm in col_template) {
if (!nm %in% names(df2))
df2[[nm]] <- 0
}
put(df2)
put("Format counts and percents for all adverse events.")
df_all <- df2 |>
transmute(AESOC = "All System Organ Classes",
AEDECOD = "All Adverse Events",
`ARM A_1` = fmt_cnt_pct(`ARM A_1`, arm_pop["ARM A"]),
`ARM A_2` = fmt_cnt_pct(`ARM A_2`, arm_pop["ARM A"]),
`ARM A_3` = fmt_cnt_pct(`ARM A_3`, arm_pop["ARM A"]),
`ARM B_1` = fmt_cnt_pct(`ARM B_1`, arm_pop["ARM B"]),
`ARM B_2` = fmt_cnt_pct(`ARM B_2`, arm_pop["ARM B"]),
`ARM B_3` = fmt_cnt_pct(`ARM B_3`, arm_pop["ARM B"]),
`ARM C_1` = fmt_cnt_pct(`ARM C_1`, arm_pop["ARM C"]),
`ARM C_2` = fmt_cnt_pct(`ARM C_2`, arm_pop["ARM C"]),
`ARM C_3` = fmt_cnt_pct(`ARM C_3`, arm_pop["ARM C"]),
`ARM D_1` = fmt_cnt_pct(`ARM D_1`, arm_pop["ARM D"]),
`ARM D_2` = fmt_cnt_pct(`ARM D_2`, arm_pop["ARM D"]),
`ARM D_3` = fmt_cnt_pct(`ARM D_3`, arm_pop["ARM D"])) |>
put()
# Final Data --------------------------------------------------------------
sep("Create final data frame")
final <- bind_rows(df_all, df_events) |> put()
# Print Report ----------------------------------------------------------
sep("Create and print report")
put("Create table object")
tbl <- create_table(final, first_row_blank = TRUE, width = 9) |>
column_defaults(from = `ARM A_1`, to = `ARM D_3`, width = 1) |>
spanning_header("ARM A_1", "ARM A_3", label = "ARM A", n = arm_pop["ARM A"]) |>
spanning_header("ARM B_1", "ARM B_3", label = "ARM B", n = arm_pop["ARM B"]) |>
spanning_header("ARM C_1", "ARM C_3", label = "ARM C", n = arm_pop["ARM C"]) |>
spanning_header("ARM D_1", "ARM D_3", label = "ARM D", n = arm_pop["ARM D"]) |>
stub(vars = c("AESOC", "AEDECOD"), label = "System Organ Class\n Preferred Term", width = 5) |>
define(AESOC, blank_after = TRUE, label_row = TRUE) |>
define(AEDECOD, indent = .25) |>
define(`ARM A_1`, align = "center", label = "Mild") |>
define(`ARM A_2`, align = "center", label = "Moderate") |>
define(`ARM A_3`, align = "center", label = "Severe") |>
define(`ARM B_1`, align = "center", label = "Mild", page_wrap = TRUE) |>
define(`ARM B_2`, align = "center", label = "Moderate") |>
define(`ARM B_3`, align = "center", label = "Severe") |>
define(`ARM C_1`, align = "center", label = "Mild", page_wrap = TRUE) |>
define(`ARM C_2`, align = "center", label = "Moderate") |>
define(`ARM C_3`, align = "center", label = "Severe") |>
define(`ARM D_1`, align = "center", label = "Mild", page_wrap = TRUE) |>
define(`ARM D_2`, align = "center", label = "Moderate") |>
define(`ARM D_3`, align = "center", label = "Severe")
pth <- file.path(tmp, "output/example4.rtf")
put("Create report object")
rpt <- create_report(pth, output_type = "RTF",
font = "Arial") |>
options_fixed(font_size = 10) |>
page_header("Sponsor: Company", "Study: ABC") |>
titles("Table 5.0", "Adverse Events by Maximum Severity",
bold = TRUE, font_size = 12) |>
add_content(tbl) |>
footnotes("Program: AE_Table.R",
"Note: Adverse events were coded using MedDRA Version 9.1") |>
page_footer(Sys.time(), "Confidential", "Page [pg] of [tpg]")
put("Print report")
write_report(rpt) |> put()
# Clean Up ----------------------------------------------------------------
# Remove library from workspace
lib_unload(sdtm)
# Close log
log_close()
# View files
# file.show(pth)
# file.show(lgpth)Output
Here are the first four pages of the output report:
Log
Here is part of the log from the above example:
=========================================================================
Log Path: C:/Users/dbosa/AppData/Local/Temp/RtmpKC93lu/log/example4.log
Working Directory: C:/packages/Testing
User Name: dbosa
R Version: 4.0.5 (2021-03-31)
Machine: SOCRATES x86-64
Operating System: Windows 10 x64 build 19041
Log Start Time: 2021-06-27 11:30:01
=========================================================================
=========================================================================
Prepare Data
=========================================================================
# library 'sdtm': 4 items
- attributes: csv not loaded
- path: C:/Users/dbosa/Documents/R/win-library/4.0/sassy/extdata
- items:
Name Extension Rows Cols Size LastModified
1 AE csv 150 27 88.1 Kb 2021-04-04 11:55:58
2 DM csv 87 24 45.2 Kb 2021-04-04 11:55:58
3 SV csv 685 10 69.9 Kb 2021-04-04 11:55:58
4 VS csv 3358 17 467 Kb 2021-04-04 11:55:58
lib_load: library 'sdtm' loaded
=========================================================================
Prepare table data
=========================================================================
select: dropped 21 variables (STUDYID, DOMAIN, SUBJID, RFSTDTC, RFENDTC, …)
inner_join: added 2 columns (ARM, ARMCD)
> rows only in x ( 0)
> rows only in y ( 30)
> matched rows 150
> =====
> rows total 150
filter: removed 5 rows (3%), 145 rows remaining
Get population counts
select: dropped 27 variables (STUDYID, DOMAIN, AESEQ, AETERM, AELLT, …)
distinct: removed 90 rows (62%), 55 rows remaining
count: now 4 rows and 2 columns, ungrouped
ARM A ARM B ARM C ARM D
14 14 14 13
Create lookup for AE severity
MILD MODERATE SEVERE
1 2 3
Subset ADAE for needed rows and columns
mutate: new variable 'AESEVN' (double) with 3 unique values and 0% NA
select: dropped 24 variables (STUDYID, DOMAIN, AESEQ, AETERM, AELLT, …)
distinct: removed 18 rows (12%), 127 rows remaining
# A tibble: 127 x 6
USUBJID ARM AESEV AESEVN AESOC AEDECOD
<chr> <chr> <chr> <dbl> <chr> <chr>
1 ABC-01-049 ARM D MODERATE 2 Investigations BLOOD GLUCOSE INCREASED
2 ABC-01-049 ARM D MODERATE 2 Investigations BLOOD TRIGLYCERIDES INCREASED
3 ABC-01-049 ARM D MILD 1 Nervous system disorders HEADACHE
4 ABC-01-049 ARM D MODERATE 2 Investigations LABORATORY TEST ABNORMAL
5 ABC-01-049 ARM D MILD 1 Musculoskeletal and connective tissue disorders MUSCULOSKELETAL DISCOMFORT
6 ABC-01-050 ARM B MILD 1 Skin and subcutaneous tissue disorders RASH
7 ABC-01-050 ARM B MILD 1 Respiratory, thoracic and mediastinal disorders UPPER RESPIRATORY TRACT CONGEST~
8 ABC-01-051 ARM A MILD 1 Nervous system disorders HEADACHE
9 ABC-01-051 ARM A MILD 1 General disorders and administration site cond~ INFLUENZA LIKE ILLNESS
10 ABC-01-051 ARM A MILD 1 Respiratory, thoracic and mediastinal disorders LOWER RESPIRATORY TRACT INFLAMM~
# ... with 117 more rows
Create template for needed ARM columns
Identify and count highest severity grade for each subject
group_by: 4 grouping variables (USUBJID, ARM, AESOC, AEDECOD)
mutate (grouped): new variable 'max_sev' (logical) with 2 unique values and 0% NA
filter (grouped): removed one row (1%), 126 rows remaining
group_by: 4 grouping variables (ARM, AESOC, AEDECOD, AESEVN)
summarize: now 101 rows and 5 columns, 3 group variables remaining (ARM, AESOC, AEDECOD)
pivot_wider: reorganized (ARM, AESEVN, cnt) into (ARM A_2, ARM A_1, ARM B_1, ARM B_2, ARM B_3, …) [was 101x5, now 73x11]
...
=========================================================================
Create final data frame
=========================================================================
# A tibble: 74 x 14
AESOC AEDECOD `ARM A_1` `ARM A_2` `ARM A_3` `ARM B_1` `ARM B_2` `ARM B_3` `ARM C_1` `ARM C_2` `ARM C_3` `ARM D_1`
<chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
1 All ~ All Ad~ 6 ( 42.9~ 8 ( 57.1~ 0 ( 0.0~ 8 ( 57.1~ 4 ( 28.6~ 2 ( 14.3~ 8 ( 57.1~ 6 ( 42.9~ 0 ( 0.0~ 7 ( 53.8~
2 Bloo~ Neutro~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~ 1 ( 7.1~ 0 ( 0.0~ 0 ( 0.0~
3 Card~ Palpit~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~ 1 ( 7.7~
4 Card~ Sinus ~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~ 1 ( 7.7~
5 Cong~ Dermoi~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~ 1 ( 7.1~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~
6 Ear ~ Vertigo 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~ 1 ( 7.1~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~
7 Endo~ Parath~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~ 1 ( 7.1~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~
8 Gast~ Diarrh~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~ 1 ( 7.1~ 1 ( 7.1~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~
9 Gast~ Food P~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~ 1 ( 7.1~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~
10 Gast~ Tootha~ 0 ( 0.0~ 1 ( 7.1~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~ 0 ( 0.0~ 2 ( 15.4~
# ... with 64 more rows, and 2 more variables: ARM D_2 <chr>, ARM D_3 <chr>
=========================================================================
Create and print report
=========================================================================
Create table object
Create report object
Print report
# A report specification: 16 pages
- file_path: 'C:\Users\dbosa\AppData\Local\Temp\RtmpKC93lu/output/example4.rtf'
- output_type: RTF
- units: inches
- orientation: landscape
- margins: top 0.5 bottom 0.5 left 1 right 1
- line size/count: 107/47
- page_header: left=Sponsor: Company right=Study: ABC
- title 1: 'Table 5.0'
- title 2: 'Adverse Events by Maximum Severity'
- footnote 1: 'Program: AE_Table.R'
- footnote 2: 'Note: Adverse events were coded using MedDRA Version 9.1'
- page_footer: left=2021-06-27 11:30:02 center=Confidential right=Page [pg] of [tpg]
- content:
# A table specification:
- data: tibble 'final' 74 rows 14 cols
- show_cols: all
- use_attributes: all
- width: 9
- spanning_header: from='ARM A_1' to='ARM A_3' 'ARM A' level=1
- spanning_header: from='ARM B_1' to='ARM B_3' 'ARM B' level=1
- spanning_header: from='ARM C_1' to='ARM C_3' 'ARM C' level=1
- spanning_header: from='ARM D_1' to='ARM D_3' 'ARM D' level=1
- stub: AESOC AEDECOD 'System Organ Class
Preferred Term' width=5 align='left'
- define: AESOC dedupe='TRUE'
- define: AEDECOD
- define: ARM A_1 'Mild' align='center'
- define: ARM A_2 'Moderate' align='center'
- define: ARM A_3 'Severe' align='center'
- define: ARM B_1 'Mild' align='center' page_wrap='TRUE'
- define: ARM B_2 'Moderate' align='center'
- define: ARM B_3 'Severe' align='center'
- define: ARM C_1 'Mild' align='center' page_wrap='TRUE'
- define: ARM C_2 'Moderate' align='center'
- define: ARM C_3 'Severe' align='center'
- define: ARM D_1 'Mild' align='center' page_wrap='TRUE'
- define: ARM D_2 'Moderate' align='center'
- define: ARM D_3 'Severe' align='center'
# A report specification: 16 pages
- file_path: 'C:\Users\dbosa\AppData\Local\Temp\RtmpKC93lu/output/example4.rtf'
- output_type: RTF
- units: inches
- orientation: landscape
- margins: top 0.5 bottom 0.5 left 1 right 1
- line size/count: 107/47
- page_header: left=Sponsor: Company right=Study: ABC
- title 1: 'Table 5.0'
- title 2: 'Adverse Events by Maximum Severity'
- footnote 1: 'Program: AE_Table.R'
- footnote 2: 'Note: Adverse events were coded using MedDRA Version 9.1'
- page_footer: left=2021-06-27 11:30:02 center=Confidential right=Page [pg] of [tpg]
- content:
# A table specification:
- data: tibble 'final' 74 rows 14 cols
- show_cols: all
- use_attributes: all
- width: 9
- spanning_header: from='ARM A_1' to='ARM A_3' 'ARM A' level=1
- spanning_header: from='ARM B_1' to='ARM B_3' 'ARM B' level=1
- spanning_header: from='ARM C_1' to='ARM C_3' 'ARM C' level=1
- spanning_header: from='ARM D_1' to='ARM D_3' 'ARM D' level=1
- stub: AESOC AEDECOD 'System Organ Class
Preferred Term' width=5 align='left'
- define: AESOC dedupe='TRUE'
- define: AEDECOD
- define: ARM A_1 'Mild' align='center'
- define: ARM A_2 'Moderate' align='center'
- define: ARM A_3 'Severe' align='center'
- define: ARM B_1 'Mild' align='center' page_wrap='TRUE'
- define: ARM B_2 'Moderate' align='center'
- define: ARM B_3 'Severe' align='center'
- define: ARM C_1 'Mild' align='center' page_wrap='TRUE'
- define: ARM C_2 'Moderate' align='center'
- define: ARM C_3 'Severe' align='center'
- define: ARM D_1 'Mild' align='center' page_wrap='TRUE'
- define: ARM D_2 'Moderate' align='center'
- define: ARM D_3 'Severe' align='center'
lib_sync: synchronized data in library 'sdtm'
lib_unload: library 'sdtm' unloaded
=========================================================================
Log End Time: 2021-06-27 11:30:04
Log Elapsed Time: 0 00:00:03
=========================================================================
Next: Example 5: VS Table