The EXT01 table provides an overview of the of the exposure of the
patients in terms of Total dose administered or missed, and treatment duration.
Usage
ext01_main(
adam_db,
arm_var = "ACTARM",
lbl_overall = NULL,
summaryvars = "AVAL",
row_split_var = "PARCAT2",
page_var = NULL,
map = NULL,
stats = list(default = c("n", "mean_sd", "median", "range", "count_fraction")),
precision = list(default = 0),
...
)
ext01_pre(adam_db, ...)
ext01_post(tlg, prune_0 = TRUE, ...)
ext01Arguments
- adam_db
(
listofdata.frames) object containing theADaMdatasets- arm_var
(
string) variable used for column splitting- lbl_overall
(
string) label used for overall column, if set toNULLthe overall column is omitted- summaryvars
(
character) variables to be analyzed. The label attribute of the corresponding column inadextable ofadam_dbis used as label.- row_split_var
(
character) additional row split variables.- page_var
(
string) variable name prior to which the row split is by page.- map
(
data.frame) of mapping for split rows.- stats
(named
listof character) where names are values found in thePARAMCDcolumn and the values indicate the statistical analysis to perform. Ifdefaultis set, and parameter precision not specified, the value fordefaultwill be used.- precision
(named
listofinteger) where names are values found in thePARAMCDcolumn and the values- ...
not used.
- tlg
(
TableTree,Listingorggplot) object typically produced by amainfunction.- prune_0
(
flag) remove 0 count rows
Value
the main function returns an rtables object.
the preprocessing function returns a list of data.frame.
the postprocessing function returns an rtables object or an ElementaryTable (null report).
Details
Default Exposure table
The
nrow provides the number of non-missing values. The percentages for categorical variables is based onn. The percentages forTotal number of patients with at least one dose modificationare based on the number of patients in the corresponding analysis population given byN.Split columns by arm, typically
ACTARM.Does not include a total column by default.
Sorted by alphabetic order of the
PARAMvalue. Transform to factor and re-level for custom order.ANL01FLis not relevant subset.
Examples
run(ext01, syn_data)
#> A: Drug X B: Placebo C: Combination
#> PARCAT2 (N=15) (N=15) (N=15)
#> ———————————————————————————————————————————————————————————————————————————————
#> Drug A
#> Overall duration (days)
#> n 11 7 7
#> Mean (SD) 157.5 (67.4) 115.4 (62.8) 98.6 (68.8)
#> Median 174.0 119.0 89.0
#> Min - Max 53 - 239 22 - 219 1 - 182
#> Total dose administered
#> n 11 7 7
#> Mean (SD) 6567.3 (1127.1) 7028.6 (1626.1) 6377.1 (863.7)
#> Median 6720.0 7200.0 6480.0
#> Min - Max 4800 - 8400 5280 - 9360 5280 - 7440
#> Drug B
#> Overall duration (days)
#> n 4 8 8
#> Mean (SD) 142.2 (100.3) 105.9 (60.0) 158.2 (96.2)
#> Median 160.0 95.0 203.0
#> Min - Max 17 - 232 37 - 211 27 - 249
#> Total dose administered
#> n 4 8 8
#> Mean (SD) 7020.0 (1148.9) 5250.0 (864.7) 5940.0 (1187.9)
#> Median 6960.0 5160.0 5880.0
#> Min - Max 5760 - 8400 4080 - 6480 4320 - 7680
run(ext01, syn_data, summaryvars = c("AVAL", "AVALCAT1"), prune_0 = FALSE)
#> A: Drug X B: Placebo C: Combination
#> PARCAT2 (N=15) (N=15) (N=15)
#> ———————————————————————————————————————————————————————————————————————————————
#> Drug A
#> Overall duration (days)
#> n 11 7 7
#> Mean (SD) 157.5 (67.4) 115.4 (62.8) 98.6 (68.8)
#> Median 174.0 119.0 89.0
#> Min - Max 53 - 239 22 - 219 1 - 182
#> n 11 7 7
#> < 1 month 0 1 (14.3%) 1 (14.3%)
#> 1 to <3 months 3 (27.3%) 1 (14.3%) 3 (42.9%)
#> 3 to <6 months 3 (27.3%) 4 (57.1%) 2 (28.6%)
#> >=6 months 5 (45.5%) 1 (14.3%) 1 (14.3%)
#> <700 0 0 0
#> 700-900 0 0 0
#> 900-1200 0 0 0
#> >1200 0 0 0
#> <5000 0 0 0
#> 5000-7000 0 0 0
#> 7000-9000 0 0 0
#> >9000 0 0 0
#> 7 0 0 0
#> Total dose administered
#> n 11 7 7
#> Mean (SD) 6567.3 (1127.1) 7028.6 (1626.1) 6377.1 (863.7)
#> Median 6720.0 7200.0 6480.0
#> Min - Max 4800 - 8400 5280 - 9360 5280 - 7440
#> n 11 7 7
#> < 1 month 0 0 0
#> 1 to <3 months 0 0 0
#> 3 to <6 months 0 0 0
#> >=6 months 0 0 0
#> <700 0 0 0
#> 700-900 0 0 0
#> 900-1200 0 0 0
#> >1200 0 0 0
#> <5000 1 (9.1%) 0 0
#> 5000-7000 6 (54.5%) 3 (42.9%) 5 (71.4%)
#> 7000-9000 4 (36.4%) 3 (42.9%) 2 (28.6%)
#> >9000 0 1 (14.3%) 0
#> 7 0 0 0
#> Drug B
#> Overall duration (days)
#> n 4 8 8
#> Mean (SD) 142.2 (100.3) 105.9 (60.0) 158.2 (96.2)
#> Median 160.0 95.0 203.0
#> Min - Max 17 - 232 37 - 211 27 - 249
#> n 4 8 8
#> < 1 month 1 (25.0%) 0 1 (12.5%)
#> 1 to <3 months 0 4 (50.0%) 2 (25.0%)
#> 3 to <6 months 1 (25.0%) 3 (37.5%) 0
#> >=6 months 2 (50.0%) 1 (12.5%) 5 (62.5%)
#> <700 0 0 0
#> 700-900 0 0 0
#> 900-1200 0 0 0
#> >1200 0 0 0
#> <5000 0 0 0
#> 5000-7000 0 0 0
#> 7000-9000 0 0 0
#> >9000 0 0 0
#> 7 0 0 0
#> Total dose administered
#> n 4 8 8
#> Mean (SD) 7020.0 (1148.9) 5250.0 (864.7) 5940.0 (1187.9)
#> Median 6960.0 5160.0 5880.0
#> Min - Max 5760 - 8400 4080 - 6480 4320 - 7680
#> n 4 8 8
#> < 1 month 0 0 0
#> 1 to <3 months 0 0 0
#> 3 to <6 months 0 0 0
#> >=6 months 0 0 0
#> <700 0 0 0
#> 700-900 0 0 0
#> 900-1200 0 0 0
#> >1200 0 0 0
#> <5000 0 4 (50.0%) 2 (25.0%)
#> 5000-7000 2 (50.0%) 4 (50.0%) 4 (50.0%)
#> 7000-9000 2 (50.0%) 0 2 (25.0%)
#> >9000 0 0 0
#> 7 0 0 0
levels(syn_data$adex$AVALCAT1) <- c(levels(syn_data$adex$AVALCAT1), "12 months")
map <- data.frame(
PARAMCD = "TDURD",
AVALCAT1 = c("< 1 month", "1 to <3 months", ">=6 months", "3 to <6 months", "12 months")
)
run(
ext01,
syn_data,
summaryvars = c("AVAL", "AVALCAT1"),
prune_0 = FALSE,
map = map,
precision = list(TDOSE = 4, default = 4),
stats = list(TDURD = "n", default = c("n", "count_fraction"))
)
#> A: Drug X B: Placebo C: Combination
#> PARCAT2 (N=15) (N=15) (N=15)
#> ———————————————————————————————————————————————————————————————————
#> Drug A
#> Overall duration (days)
#> n 11 7 7
#> n 11 7 7
#> Total dose administered
#> n 11 7 7
#> n 11 7 7
#> <5000 1 (9.1%) 0 0
#> 5000-7000 6 (54.5%) 3 (42.9%) 5 (71.4%)
#> 7000-9000 4 (36.4%) 3 (42.9%) 2 (28.6%)
#> >9000 0 1 (14.3%) 0
#> Drug B
#> Overall duration (days)
#> n 4 8 8
#> n 4 8 8
#> Total dose administered
#> n 4 8 8
#> n 4 8 8
#> <5000 0 4 (50.0%) 2 (25.0%)
#> 5000-7000 2 (50.0%) 4 (50.0%) 4 (50.0%)
#> 7000-9000 2 (50.0%) 0 2 (25.0%)
#> >9000 0 0 0