The CFBT01 table provides an
overview of the actual values and its change from baseline of each respective arm
over the course of the trial.
Usage
cfbt01_main(
adam_db,
dataset,
arm_var = "ACTARM",
lbl_overall = NULL,
row_split_var = NULL,
summaryvars = c("AVAL", "CHG"),
visitvar = "AVISIT",
precision = list(default = 2L),
page_var = "PARAMCD",
.stats = c("n", "mean_sd", "median", "range"),
skip = list(CHG = "BASELINE"),
...
)
cfbt01_pre(adam_db, dataset, ...)
cfbt01_post(tlg, prune_0 = TRUE, ...)
cfbt01Arguments
- adam_db
(
listofdata.frames) object containing theADaMdatasets- dataset
(
string) the name of a table in theadam_dbobject.- arm_var
(
string) variable used for column splitting- lbl_overall
(
string) label used for overall column, if set toNULLthe overall column is omitted- row_split_var
(
character) additional row split variables.- summaryvars
(
character) variables to be analyzed. The label attribute of the corresponding column in table ofadam_dbis used as label.- visitvar
(
string) typically one of"AVISIT"or user-defined visit incorporating"ATPT".- precision
(named
listofinteger) where names are values found in thePARAMCDcolumn and the values indicate the number of digits in statistics. Ifdefaultis set, and parameter precision not specified, the value fordefaultwill be used.- page_var
(
string) variable name prior to which the row split is by page.- .stats
(
character) statistics names, seetern::analyze_vars().- skip
Named (
list) of visit values that need to be inhibited.- ...
additional arguments like
.indent_mods,.labels.- 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
The
Analysis Valuecolumn, displays the number of patients, the mean, standard deviation, median and range of the analysis value for each visit.The
Change from Baselinecolumn, displays the number of patient and the mean, standard deviation, median and range of changes relative to the baseline.Remove zero-count rows unless overridden with
prune_0 = FALSE.Split columns by arm, typically
ACTARM.Does not include a total column by default.
Sorted based on factor level; first by
PARAMlabels in alphabetic order then by chronological time point given byAVISIT. Re-level to customize order
Functions
cfbt01_main(): Main TLG functioncfbt01_pre(): Preprocessingcfbt01_post(): Postprocessing
Examples
library(dunlin)
proc_data <- log_filter(
syn_data,
PARAMCD %in% c("DIABP", "SYSBP"), "advs"
)
run(cfbt01, proc_data, dataset = "advs")
#> A: Drug X B: Placebo C: Combination
#> Change from Change from Change from
#> Value at Visit Baseline Value at Visit Baseline Value at Visit Baseline
#> Analysis Visit (N=15) (N=15) (N=15) (N=15) (N=15) (N=15)
#> —————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————
#> Diastolic Blood Pressure
#> SCREENING
#> n 15 0 15 0 15 0
#> Mean (SD) 94.385 (17.067) NE (NE) 106.381 (20.586) NE (NE) 106.468 (12.628) NE (NE)
#> Median 94.933 NE 111.133 NE 108.359 NE
#> Min - Max 55.71 - 122.00 NE - NE 60.21 - 131.91 NE - NE 83.29 - 127.17 NE - NE
#> BASELINE
#> n 15 15 15
#> Mean (SD) 96.133 (22.458) 108.111 (15.074) 103.149 (19.752)
#> Median 93.328 108.951 102.849
#> Min - Max 60.58 - 136.59 83.44 - 131.62 66.05 - 136.55
#> WEEK 1 DAY 8
#> n 15 15 15 15 15 15
#> Mean (SD) 98.977 (21.359) 2.844 (28.106) 104.110 (16.172) -4.001 (21.867) 100.826 (19.027) -2.323 (25.018)
#> Median 92.447 -4.066 107.703 3.227 103.058 -2.476
#> Min - Max 67.55 - 130.37 -32.82 - 47.68 70.91 - 132.89 -52.94 - 28.63 70.04 - 128.68 -55.15 - 41.81
#> WEEK 2 DAY 15
#> n 15 15 15 15 15 15
#> Mean (SD) 99.758 (14.477) 3.626 (21.189) 97.473 (17.296) -10.638 (20.831) 94.272 (16.961) -8.877 (27.229)
#> Median 101.498 1.731 99.501 -9.727 96.789 -10.155
#> Min - Max 71.98 - 122.81 -39.50 - 47.57 53.80 - 125.81 -55.15 - 25.26 63.45 - 117.47 -73.10 - 46.54
#> WEEK 3 DAY 22
#> n 15 15 15 15 15 15
#> Mean (SD) 99.101 (26.109) 2.968 (34.327) 91.984 (16.925) -16.127 (21.881) 94.586 (13.560) -8.563 (21.713)
#> Median 101.146 -0.271 91.244 -14.384 98.398 -16.075
#> Min - Max 47.68 - 162.22 -47.87 - 76.64 67.80 - 119.72 -53.06 - 22.52 73.50 - 115.43 -37.90 - 32.66
#> WEEK 4 DAY 29
#> n 15 15 15 15 15 15
#> Mean (SD) 103.400 (22.273) 7.267 (30.740) 96.467 (19.451) -11.644 (25.922) 108.338 (18.417) 5.189 (21.881)
#> Median 98.168 2.510 97.385 -16.793 107.555 7.966
#> Min - Max 63.09 - 148.25 -38.43 - 61.90 63.35 - 131.57 -57.11 - 48.13 68.78 - 132.52 -33.96 - 41.50
#> WEEK 5 DAY 36
#> n 15 15 15 15 15 15
#> Mean (SD) 93.222 (18.536) -2.911 (28.873) 97.890 (20.701) -10.221 (27.593) 95.317 (16.401) -7.832 (19.827)
#> Median 90.799 -3.385 99.049 -11.319 93.876 -4.665
#> Min - Max 63.55 - 139.11 -48.63 - 47.35 69.47 - 137.64 -54.38 - 37.85 71.91 - 138.54 -44.47 - 29.11
#> Systolic Blood Pressure
#> SCREENING
#> n 15 0 15 0 15 0
#> Mean (SD) 154.073 (33.511) NE (NE) 157.840 (34.393) NE (NE) 152.407 (22.311) NE (NE)
#> Median 156.169 NE 161.670 NE 149.556 NE
#> Min - Max 78.31 - 210.70 NE - NE 79.76 - 210.40 NE - NE 108.21 - 184.88 NE - NE
#> BASELINE
#> n 15 15 15
#> Mean (SD) 145.925 (28.231) 152.007 (28.664) 154.173 (26.317)
#> Median 142.705 157.698 155.282
#> Min - Max 85.21 - 195.68 98.90 - 194.62 86.65 - 192.68
#> WEEK 1 DAY 8
#> n 15 15 15 15 15 15
#> Mean (SD) 156.509 (21.097) 10.584 (34.598) 147.480 (33.473) -4.527 (48.895) 143.319 (30.759) -10.854 (34.553)
#> Median 160.711 5.802 155.030 2.758 145.548 -5.636
#> Min - Max 126.84 - 185.53 -53.28 - 91.52 85.22 - 189.88 -77.34 - 90.98 90.37 - 191.58 -65.71 - 49.04
#> WEEK 2 DAY 15
#> n 15 15 15 15 15 15
#> Mean (SD) 144.202 (33.676) -1.723 (27.067) 136.892 (30.178) -15.115 (37.794) 148.622 (27.088) -5.551 (44.670)
#> Median 144.253 5.325 142.679 -14.083 147.102 -11.512
#> Min - Max 62.56 - 203.66 -53.89 - 44.16 70.34 - 174.27 -83.07 - 62.39 108.82 - 200.23 -69.54 - 113.59
#> WEEK 3 DAY 22
#> n 15 15 15 15 15 15
#> Mean (SD) 154.887 (35.374) 8.962 (38.455) 149.761 (28.944) -2.247 (44.835) 150.460 (21.352) -3.712 (37.984)
#> Median 158.938 17.191 155.044 -1.796 156.505 -7.606
#> Min - Max 112.32 - 218.83 -47.28 - 96.18 84.42 - 192.92 -110.20 - 94.02 94.70 - 180.41 -74.91 - 72.74
#> WEEK 4 DAY 29
#> n 15 15 15 15 15 15
#> Mean (SD) 150.159 (32.249) 4.234 (32.965) 156.043 (22.863) 4.036 (42.494) 145.714 (22.980) -8.458 (33.175)
#> Median 145.506 3.754 149.094 -10.000 150.797 -14.432
#> Min - Max 69.37 - 210.43 -89.16 - 54.32 113.57 - 195.10 -71.44 - 77.75 106.91 - 188.09 -41.95 - 65.16
#> WEEK 5 DAY 36
#> n 15 15 15 15 15 15
#> Mean (SD) 155.964 (30.945) 10.039 (42.252) 156.387 (35.274) 4.380 (51.782) 143.592 (33.170) -10.581 (44.799)
#> Median 158.142 1.448 164.552 7.060 148.501 -2.385
#> Min - Max 110.61 - 212.47 -53.91 - 90.45 63.28 - 198.79 -131.34 - 86.84 92.18 - 191.05 -78.77 - 64.35