Below is an example showing a patient profile report. Every organization has their own way of presenting patient profiles. This is an example of a “master and detail” type of report.
Note the following about this example:
library(sassy)
options("logr.notes" = FALSE,
"logr.autolog" = TRUE)
# Get temp location for log and report output
tmp <- tempdir()
lf <- log_open(file.path(tmp, "example8.log"))
# Get data ----------------------------------------------------------------
sep("Get data")
# Get sample data path
pth <- system.file("extdata", package = "sassy")
put("Open data library")
libname(sdtm, pth, "csv")
# Set labels --------------------------------------------------------------
sep("Set labels")
put("DM labels")
labels(sdtm$DM) <- list(ARM = "Treatment Group",
SITEID = "Centre",
SUBJID = "Subject",
SEX = "Sex",
AGE = "Age (yrs)",
RACE = "Race",
BRTHDTC = "Birth Date",
ARMCD = "Treatment Code"
) |> put()
put("AE labels")
labels(sdtm$AE) <- list(AESTDTC = "Event Start Date",
AEENDTC = "Event Stop Date",
AESTDY = "Start",
AEENDY = "End",
AESOC = "System Organ Class",
AESEV = "Severityᵃ",
AESER = "Serious",
AEREL = "Related") |> put()
# Apply formats ----------------------------------------------------------
sep("Apply formats")
sevfmt <- value(condition(x == "MODERATE", "Moderate"),
condition(x == "SEVERE", "Severe"),
condition(x == "MILD", "Mild"))
relfmt <- value(condition(x == "RELATED", "Yes"),
condition(x == "NOT RELATED", "No"),
condition(x == "PROBABLY RELATED", "Probably"),
condition(x == "POSSIBLY RELATED", "Possibly"))
serfmt <- value(condition(x == "N", "No"),
condition(x == "Y", "Yes"))
sexfmt <- value(condition(x == "M", "Male"),
condition(x == "F", "Female"),
condition(TRUE, "Unknown"))
racefmt <- value(condition(x == "WHITE", "White"),
condition(x == "BLACK OR AFRICAN AMERICAN", "Black"),
condition(x == "UNKNOWN", "Unknown"),
condition(x == "ASIAN", "Asian"))
armfmt <- value(condition(x == "ARM A", "Placebo"),
condition(x == "ARM B", "Dose 50mg"),
condition(x == "ARM C", "Dose 100mg"),
condition(x == "ARM D", "Competitor"))
formats(sdtm$DM) <- list(SEX = sexfmt,
RACE = racefmt,
ARM = armfmt)
formats(sdtm$AE) <- list(AESEV = sevfmt,
AEREL = relfmt,
AESER = serfmt)
# Prepare data ------------------------------------------------------------
sep("Prepare data")
put("Select desired columns from DM dataset")
datastep(sdtm$DM,
keep = v(USUBJID, ARM, SITEID, SUBJID, SEX, AGE, RACE, BRTHDTC), {}) -> dm
# Split dm data by subject id
dmlst <- split(dm, factor(dm$USUBJID))
put("Select desired columns from AE dataset")
datastep(sdtm$AE,
keep = v(USUBJID, AESTDTC, AEENDTC, AESTDY,
AEENDY, AESOC, AESEV, AESER, AEREL), {}) -> ae
# Split ae data by subject id
aelst <- split(ae, factor(ae$USUBJID))
# Create report -----------------------------------------------------------
sep("Create report")
# Create report first, outside loop
rpt <- create_report(file.path(tmp, "output/example8.docx"),
font = "Arial", output_type = "DOCX")
# Loop on subjects
for (id in names(dmlst)) {
dm_sub <- dmlst[[id]]
ae_sub <- aelst[[id]]
tb1 <- create_table(dm_sub, width = 8, borders = "outside") |>
titles("Listing 1.1 Subjects Narratives of Adverse Events",
paste0("Subject: ", dm_sub[[1, 1]]), bold = TRUE) |>
define(AGE, align = "left")
if (!is.null(ae_sub)) {
tb2 <- create_table(ae_sub, borders = "outside", width = 8) |>
spanning_header("AESTDY", "AEENDY", label ="Study Day") |>
define(USUBJID, visible = FALSE) |>
define(AESOC, width = 2) |>
define(AESTDY, align = "left") |>
define(AEENDY, align = "left") |>
footnotes("ᵃSeverity: 01=Mild, 02=Moderate, 03=Severe, 04=Life Threatening, 05=Fatal",
paste0("ᵇAction Taken: 01=None, 02=Investigational product dose altered, ",
"03=Medication taken, 04=Hospitalized, 05=Removed from study, ",
"06=Investigational product discontinued, 07=Transfusion performed,",
"88=Other"))
}
# Append table content
rpt <- rpt |> add_content(tb1, page_break = FALSE) |>
add_content(tb2)
}
put("Write out report")
res <- write_report(rpt)
# Clean Up ----------------------------------------------------------------
sep("Clean up")
log_close()
# View log
# file.show(lf)
# View report
# file.show(res$modified_path)
Here is most of the log from the above program:
=========================================================================
Log Path: C:/Users/dbosa/AppData/Local/Temp/Rtmp6lCP5X/log/example8.log
Program Path: C:/packages/Testing/procs/ProcsPatientProfile.R
Working Directory: C:/packages/Testing/procs
User Name: dbosa
R Version: 4.3.1 (2023-06-16 ucrt)
Machine: SOCRATES x86-64
Operating System: Windows 10 x64 build 22621
Base Packages: stats graphics grDevices utils datasets methods base Other
Packages: tidylog_1.0.2 ggplot2_3.4.2 patchwork_1.1.3 procs_1.0.3
reporter_1.4.1 libr_1.2.8 fmtr_1.5.9 logr_1.3.4 common_1.0.8 sassy_1.2.0
Log Start Time: 2023-09-06 21:24:18.59308
=========================================================================
=========================================================================
Get data
=========================================================================
# library 'sdtm': 7 items
- attributes: csv not loaded
- path: C:/Users/dbosa/AppData/Local/R/win-library/4.3/sassy/extdata
- items:
Name Extension Rows Cols Size LastModified
1 AE csv 150 27 88.5 Kb 2023-09-06 21:14:37
2 DM csv 87 24 45.5 Kb 2023-09-06 21:14:37
3 DS csv 174 9 34.1 Kb 2023-09-06 21:14:37
4 EX csv 84 11 26.4 Kb 2023-09-06 21:14:37
5 IE csv 2 14 13.4 Kb 2023-09-06 21:14:37
6 SV csv 685 10 70.3 Kb 2023-09-06 21:14:37
7 VS csv 3358 17 467.4 Kb 2023-09-06 21:14:37
=========================================================================
Set labels
=========================================================================
DM labels
$ARM
[1] "Treatment Group"
$SITEID
[1] "Centre"
$SUBJID
[1] "Subject"
$SEX
[1] "Sex"
$AGE
[1] "Age (yrs)"
$RACE
[1] "Race"
$BRTHDTC
[1] "Birth Date"
$ARMCD
[1] "Treatment Code"
AE labels
$AESTDTC
[1] "Event Start Date"
$AEENDTC
[1] "Event Stop Date"
$AESTDY
[1] "Start"
$AEENDY
[1] "End"
$AESOC
[1] "System Organ Class"
$AESEV
[1] "Severityᵃ"
$AESER
[1] "Serious"
$AEREL
[1] "Related"
=========================================================================
Apply formats
=========================================================================
# A user-defined format: 3 conditions
Name Type Expression Label Order
1 obj U x == "MODERATE" Moderate NA
2 obj U x == "SEVERE" Severe NA
3 obj U x == "MILD" Mild NA
# A user-defined format: 4 conditions
Name Type Expression Label Order
1 obj U x == "RELATED" Yes NA
2 obj U x == "NOT RELATED" No NA
3 obj U x == "PROBABLY RELATED" Probably NA
4 obj U x == "POSSIBLY RELATED" Possibly NA
# A user-defined format: 2 conditions
Name Type Expression Label Order
1 obj U x == "N" No NA
2 obj U x == "Y" Yes NA
# A user-defined format: 3 conditions
Name Type Expression Label Order
1 obj U x == "M" Male NA
2 obj U x == "F" Female NA
3 obj U TRUE Unknown NA
# A user-defined format: 4 conditions
Name Type Expression Label Order
1 obj U x == "WHITE" White NA
2 obj U x == "BLACK OR AFRICAN AMERICAN" Black NA
3 obj U x == "UNKNOWN" Unknown NA
4 obj U x == "ASIAN" Asian NA
# A user-defined format: 4 conditions
Name Type Expression Label Order
1 obj U x == "ARM A" Placebo NA
2 obj U x == "ARM B" Dose 50mg NA
3 obj U x == "ARM C" Dose 100mg NA
4 obj U x == "ARM D" Competitor NA
=========================================================================
Prepare data
=========================================================================
Select desired columns from DM dataset
datastep: columns decreased from 24 to 8
# A tibble: 87 × 8
USUBJID ARM SITEID SUBJID SEX AGE RACE BRTHDTC
<chr> <chr> <chr> <chr> <chr> <dbl> <chr> <date>
1 ABC-01-049 ARM D 01 049 M 39 WHITE 1966-11-12
2 ABC-01-050 ARM B 01 050 M 47 WHITE 1958-12-19
3 ABC-01-051 ARM A 01 051 M 34 WHITE 1972-05-02
4 ABC-01-052 ARM C 01 052 F 45 WHITE 1961-06-27
5 ABC-01-053 ARM B 01 053 F 26 WHITE 1980-04-07
6 ABC-01-054 ARM D 01 054 M 44 WHITE 1962-09-13
7 ABC-01-055 ARM C 01 055 F 47 BLACK OR AFRICAN AMERICAN 1959-06-11
8 ABC-01-056 ARM A 01 056 M 31 WHITE 1975-05-02
9 ABC-01-113 ARM D 01 113 M 74 WHITE 1932-02-08
10 ABC-01-114 ARM B 01 114 F 72 WHITE 1934-07-09
# ℹ 77 more rows
# ℹ Use `print(n = ...)` to see more rows
Select desired columns from AE dataset
datastep: columns decreased from 27 to 9
# A tibble: 150 × 9
USUBJID AESTDTC AEENDTC AESTDY AEENDY AESOC AESEV AESER AEREL
<chr> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr> <chr>
1 ABC-01-049 2006-12-28 2007-03-13 52 127 Investigations MODE… N NOT …
2 ABC-01-049 2006-12-28 2007-03-13 52 127 Investigations MODE… N NOT …
3 ABC-01-049 2007 2007 NA NA Nervous system diso… MILD N NOT …
4 ABC-01-049 2007-01-11 2007-03-13 66 127 Investigations MODE… N NOT …
5 ABC-01-049 2007 2007 NA NA Musculoskeletal and… MILD N NOT …
6 ABC-01-050 2006-11-08 2006-11-15 7 14 Skin and subcutaneo… MILD N NOT …
7 ABC-01-050 2006-12-17 2006-12-17 46 46 Respiratory, thorac… MILD N NOT …
8 ABC-01-051 2007-01-01 2007-01-01 61 61 Nervous system diso… MILD N NOT …
9 ABC-01-051 2007-03-06 2007-03-09 125 128 Nervous system diso… MILD N NOT …
10 ABC-01-051 2007-11-12 2007-11-14 376 378 Nervous system diso… MILD N NOT …
# ℹ 140 more rows
# ℹ Use `print(n = ...)` to see more rows
=========================================================================
Create report
=========================================================================
Write out report
# A report specification: 87 pages
- file_path: 'C:\Users\dbosa\AppData\Local\Temp\Rtmp6lCP5X/output/example8.docx'
- output_type: DOCX
- units: inches
- orientation: landscape
- margins: top 0.5 bottom 0.5 left 1 right 1
- line size/count: 9/42
- content:
# A table specification:
- data: tibble 'dm_sub' 1 rows 8 cols
- show_cols: all
- use_attributes: all
- width: 8
- title 1: 'Listing 1.1 Subjects Narratives of Adverse Events'
- title 2: 'Subject: ABC-01-049'
- define: AGE align='left'
# A table specification:
- data: tibble 'ae_sub' 5 rows 9 cols
- show_cols: all
- use_attributes: all
- width: 8
- footnote 1: 'ᵃSeverity: 01=Mild, 02=Moderate, 03=Severe, 04=Life Threatening, 05=Fatal'
- footnote 2: 'ᵇAction Taken: 01=None, 02=Investigational product dose altered, 03=Medication taken, 04=Hospitalized, 05=Removed from study, 06=Investigational product discontinued, 07=Transfusion performed,88=Other'
- spanning_header: from='AESTDY' to='AEENDY' 'Study Day' level=1
- define: USUBJID visible='FALSE'
- define: AESOC width=2
- define: AESTDY align='left'
- define: AEENDY align='left'
...
=========================================================================
Clean up
=========================================================================
=========================================================================
Log End Time: 2023-09-06 21:24:25.764916
Log Elapsed Time: 0 00:00:07
=========================================================================
Next: Example 9: Forest Plot