Create a shift table ready to be used with tabulator().
The function is transforming a dataset representing some 'Laboratory Tests Results' structured as CDISC clinical trial data sets format to a dataset representing the shift table.
Shift tables are tables used in clinical trial analysis. They show the progression of change from the baseline, with the progression often being along time; the number of subjects is displayed in different range (e.g. low, normal, or high) at baseline and at selected time points or intervals.
Usage
shift_table(
x,
cn_visit = "VISIT",
cn_visit_num = "VISITNUM",
cn_grade = "LBNRIND",
cn_usubjid = "USUBJID",
cn_lab_cat = NA_character_,
cn_is_baseline = "LBBLFL",
baseline_identifier = "Y",
cn_treatment = NA_character_,
grade_levels = c("LOW", "NORMAL", "HIGH"),
grade_labels = c("Low", "Normal", "High")
)Arguments
- x
Laboratory Tests Results data frame.
- cn_visit
column name containing visit names, default to "VISIT".
- cn_visit_num
column name containing visit numbers, default to "VISITNUM".
- cn_grade
column name containing reference range indicators, default to "LBNRIND".
- cn_usubjid
column name containing unique subject inditifiers, default to "USUBJID".
- cn_lab_cat
column name containing lab tests or examination names, default to "LBTEST".
- cn_is_baseline
column name containing baseline flags, default to "LBBLFL".
- baseline_identifier
baseline flag value to use for baseline identification. Its default is "Y".
- cn_treatment
column name containing treatment names, default to
NA.- grade_levels
levels to use for reference range indicators
- grade_labels
labels to use for reference range indicators
Value
the shift table as a data.frame. Additionnal elements are provided in attributes:
"VISIT_N": count of unique subject id per visits, labs and eventually treatments. This element is supposed to be used as value for argument
hidden_dataof functiontabulator()."FUN_VISIT": a utility function to easily turn visit column as a factor column. It should be applied after the shift table creation.
"FUN_GRADE": a utility function to easily turn grade column as a factor column. It adds "MISSING/Missing" and "SUM/Sum" at the end of the set of values specified in arguments
grade_levelsandgrade_labels. It should be applied after the shift table creation.
Examples
library(data.table)
library(flextable)
# data simulation ----
USUBJID <- sprintf("01-ABC-%04.0f", 1:200)
VISITS <- c("SCREENING 1", "WEEK 2", "MONTH 3")
LBTEST <- c("Albumin", "Sodium")
VISITNUM <- seq_along(VISITS)
LBBLFL <- rep(NA_character_, length(VISITNUM))
LBBLFL[1] <- "Y"
VISIT <- data.frame(
VISIT = VISITS, VISITNUM = VISITNUM,
LBBLFL = LBBLFL, stringsAsFactors = FALSE
)
labdata <- expand.grid(
USUBJID = USUBJID, LBTEST = LBTEST,
VISITNUM = VISITNUM,
stringsAsFactors = FALSE
)
setDT(labdata)
labdata <- merge(labdata, VISIT, by = "VISITNUM")
subject_elts <- unique(labdata[, .SD, .SDcols = "USUBJID"])
subject_elts <- unique(subject_elts)
subject_elts[, c("TREAT") := list(
sample(x = c("Treatment", "Placebo"), size = .N, replace = TRUE)
)]
#> USUBJID TREAT
#> <char> <char>
#> 1: 01-ABC-0001 Placebo
#> 2: 01-ABC-0002 Treatment
#> 3: 01-ABC-0003 Placebo
#> 4: 01-ABC-0004 Placebo
#> 5: 01-ABC-0005 Treatment
#> ---
#> 196: 01-ABC-0196 Treatment
#> 197: 01-ABC-0197 Placebo
#> 198: 01-ABC-0198 Treatment
#> 199: 01-ABC-0199 Treatment
#> 200: 01-ABC-0200 Placebo
subject_elts[, c("TREAT") := list(
factor(.SD$TREAT, levels = c("Treatment", "Placebo"))
)]
#> USUBJID TREAT
#> <char> <fctr>
#> 1: 01-ABC-0001 Placebo
#> 2: 01-ABC-0002 Treatment
#> 3: 01-ABC-0003 Placebo
#> 4: 01-ABC-0004 Placebo
#> 5: 01-ABC-0005 Treatment
#> ---
#> 196: 01-ABC-0196 Treatment
#> 197: 01-ABC-0197 Placebo
#> 198: 01-ABC-0198 Treatment
#> 199: 01-ABC-0199 Treatment
#> 200: 01-ABC-0200 Placebo
setDF(subject_elts)
labdata <- merge(labdata, subject_elts,
by = "USUBJID", all.x = TRUE, all.y = FALSE
)
labdata[, c("LBNRIND") := list(
sample(
x = c("LOW", "NORMAL", "HIGH"), size = .N,
replace = TRUE, prob = c(.03, .9, .07)
)
)]
#> Key: <USUBJID>
#> USUBJID VISITNUM LBTEST VISIT LBBLFL TREAT LBNRIND
#> <char> <int> <char> <char> <char> <fctr> <char>
#> 1: 01-ABC-0001 1 Albumin SCREENING 1 Y Placebo NORMAL
#> 2: 01-ABC-0001 1 Sodium SCREENING 1 Y Placebo HIGH
#> 3: 01-ABC-0001 2 Albumin WEEK 2 <NA> Placebo NORMAL
#> 4: 01-ABC-0001 2 Sodium WEEK 2 <NA> Placebo NORMAL
#> 5: 01-ABC-0001 3 Albumin MONTH 3 <NA> Placebo NORMAL
#> ---
#> 1196: 01-ABC-0200 1 Sodium SCREENING 1 Y Placebo NORMAL
#> 1197: 01-ABC-0200 2 Albumin WEEK 2 <NA> Placebo NORMAL
#> 1198: 01-ABC-0200 2 Sodium WEEK 2 <NA> Placebo NORMAL
#> 1199: 01-ABC-0200 3 Albumin MONTH 3 <NA> Placebo NORMAL
#> 1200: 01-ABC-0200 3 Sodium MONTH 3 <NA> Placebo HIGH
setDF(labdata)
# shift table calculation ----
SHIFT_TABLE <- shift_table(
x = labdata, cn_visit = "VISIT",
cn_grade = "LBNRIND",
cn_usubjid = "USUBJID",
cn_lab_cat = "LBTEST",
cn_treatment = "TREAT",
cn_is_baseline = "LBBLFL",
baseline_identifier = "Y",
grade_levels = c("LOW", "NORMAL", "HIGH")
)
# get attrs for post treatment ----
SHIFT_TABLE_VISIT <- attr(SHIFT_TABLE, "VISIT_N")
visit_as_factor <- attr(SHIFT_TABLE, "FUN_VISIT")
range_as_factor <- attr(SHIFT_TABLE, "FUN_GRADE")
# post treatments ----
SHIFT_TABLE$VISIT <- visit_as_factor(SHIFT_TABLE$VISIT)
SHIFT_TABLE$BASELINE <- range_as_factor(SHIFT_TABLE$BASELINE)
SHIFT_TABLE$LBNRIND <- range_as_factor(SHIFT_TABLE$LBNRIND)
SHIFT_TABLE_VISIT$VISIT <- visit_as_factor(SHIFT_TABLE_VISIT$VISIT)
# tabulator ----
my_format <- function(z) {
formatC(z * 100,
digits = 1, format = "f",
flag = "0", width = 4
)
}
tab <- tabulator(
x = SHIFT_TABLE,
hidden_data = SHIFT_TABLE_VISIT,
row_compose = list(
VISIT = as_paragraph(VISIT, "\n(N=", N_VISIT, ")")
),
rows = c("LBTEST", "VISIT", "BASELINE"),
columns = c("TREAT", "LBNRIND"),
`n` = as_paragraph(N),
`%` = as_paragraph(as_chunk(PCT, formatter = my_format))
)
# as_flextable ----
ft_1 <- as_flextable(
x = tab, separate_with = "VISIT",
label_rows = c(
LBTEST = "Lab Test", VISIT = "Visit",
BASELINE = "Reference Range Indicator"
)
)
ft_1
Lab Test
Visit
Reference Range Indicator
Treatment
Placebo
Low
Normal
High
Missing
Low
Normal
High
Missing
n
%
n
%
n
%
n
%
n
%
n
%
n
%
n
%
Albumin
WEEK 2
(N=95)
Low
0
00.0
4
04.2
1
01.1
0
00.0
0
00.0
4
03.8
0
00.0
0
00.0
0
00.0
4
04.2
1
01.1
0
00.0
0
00.0
4
03.8
0
00.0
0
00.0
Normal
4
04.2
72
75.8
5
05.3
0
00.0
4
03.8
76
72.4
13
12.4
0
00.0
4
04.2
72
75.8
5
05.3
0
00.0
4
03.8
76
72.4
13
12.4
0
00.0
High
0
00.0
9
09.5
0
00.0
0
00.0
0
00.0
8
07.6
0
00.0
0
00.0
0
00.0
9
09.5
0
00.0
0
00.0
0
00.0
8
07.6
0
00.0
0
00.0
Missing
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
Sum
4
04.2
85
89.5
6
06.3
0
00.0
4
03.8
88
83.8
13
12.4
0
00.0
4
04.2
85
89.5
6
06.3
0
00.0
4
03.8
88
83.8
13
12.4
0
00.0
MONTH 3
(N=95)
Low
0
00.0
5
05.3
0
00.0
0
00.0
0
00.0
4
03.8
0
00.0
0
00.0
0
00.0
5
05.3
0
00.0
0
00.0
0
00.0
4
03.8
0
00.0
0
00.0
Normal
2
02.1
75
78.9
4
04.2
0
00.0
3
02.9
84
80.0
6
05.7
0
00.0
2
02.1
75
78.9
4
04.2
0
00.0
3
02.9
84
80.0
6
05.7
0
00.0
High
0
00.0
8
08.4
1
01.1
0
00.0
0
00.0
8
07.6
0
00.0
0
00.0
0
00.0
8
08.4
1
01.1
0
00.0
0
00.0
8
07.6
0
00.0
0
00.0
Missing
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
Sum
2
02.1
88
92.6
5
05.3
0
00.0
3
02.9
96
91.4
6
05.7
0
00.0
2
02.1
88
92.6
5
05.3
0
00.0
3
02.9
96
91.4
6
05.7
0
00.0
Sodium
WEEK 2
(N=95)
Low
0
00.0
3
03.2
0
00.0
0
00.0
0
00.0
4
03.8
0
00.0
0
00.0
0
00.0
3
03.2
0
00.0
0
00.0
0
00.0
4
03.8
0
00.0
0
00.0
Normal
5
05.3
70
73.7
3
03.2
0
00.0
4
03.8
86
81.9
6
05.7
0
00.0
5
05.3
70
73.7
3
03.2
0
00.0
4
03.8
86
81.9
6
05.7
0
00.0
High
0
00.0
13
13.7
1
01.1
0
00.0
0
00.0
4
03.8
1
01.0
0
00.0
0
00.0
13
13.7
1
01.1
0
00.0
0
00.0
4
03.8
1
01.0
0
00.0
Missing
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
Sum
5
05.3
86
90.5
4
04.2
0
00.0
4
03.8
94
89.5
7
06.7
0
00.0
5
05.3
86
90.5
4
04.2
0
00.0
4
03.8
94
89.5
7
06.7
0
00.0
MONTH 3
(N=95)
Low
0
00.0
3
03.2
0
00.0
0
00.0
0
00.0
4
03.8
0
00.0
0
00.0
0
00.0
3
03.2
0
00.0
0
00.0
0
00.0
4
03.8
0
00.0
0
00.0
Normal
2
02.1
71
74.7
5
05.3
0
00.0
3
02.9
83
79.0
10
09.5
0
00.0
2
02.1
71
74.7
5
05.3
0
00.0
3
02.9
83
79.0
10
09.5
0
00.0
High
1
01.1
12
12.6
1
01.1
0
00.0
0
00.0
5
04.8
0
00.0
0
00.0
1
01.1
12
12.6
1
01.1
0
00.0
0
00.0
5
04.8
0
00.0
0
00.0
Missing
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
0
00.0
Sum
3
03.2
86
90.5
6
06.3
0
00.0
3
02.9
92
87.6
10
09.5
0
00.0
3
03.2
86
90.5
6
06.3
0
00.0
3
02.9
92
87.6
10
09.5
0
00.0