CMT01A
Concomitant Medication by Medication Class and Preferred Name.
cmt01a.Rd
A concomitant medication table with the number of subjects and the total number of treatments by medication class.
Usage
cmt01a_main(
adam_db,
arm_var = "ARM",
incl_n_treatment = TRUE,
row_split_var = "ATC2",
medname_var = "CMDECOD",
lbl_overall = NULL,
...
)
cmt01a_pre(adam_db, ...)
cmt01a_post(
tlg,
prune_0 = TRUE,
sort_by_freq = FALSE,
row_split_var = "ATC2",
medname_var = "CMDECOD",
...
)
cmt01a
Arguments
- adam_db
(
list
ofdata.frames
) object containing theADaM
datasets- arm_var
(
string
) variable used for column splitting- incl_n_treatment
(
flag
) include total number of treatments per medication.- row_split_var
(
character
) the variable defining the medication category. By defaultATC2
.- medname_var
(
string
) variable name of medical treatment name.- lbl_overall
(
string
) label used for overall column, if set toNULL
the overall column is omitted- ...
not used.
- tlg
(
TableTree
,Listing
orggplot
) object typically produced by amain
function.- prune_0
(
flag
) remove 0 count rows- sort_by_freq
(
flag
) whether to sort medication class by frequency.
Details
Data should be filtered for concomitant medication.
(ATIREL == "CONCOMITANT")
.Numbers represent absolute numbers of subjects and fraction of
N
, or absolute numbers when specified.Remove zero-count rows unless overridden with
prune_0 = FALSE
.Split columns by arm.
Does not include a total column by default.
Sort by medication class alphabetically and within medication class by decreasing total number of patients with the specific medication.
Functions
cmt01a_main()
: Main TLG functioncmt01a_pre()
: Preprocessingcmt01a_post()
: Postprocessing
Note
adam_db
object must contain anadcm
table with the columns specified inrow_split_var
andmedname_var
as well as"CMSEQ"
.
Examples
library(dplyr)
#>
#> Attaching package: ‘dplyr’
#> The following objects are masked from ‘package:stats’:
#>
#> filter, lag
#> The following objects are masked from ‘package:base’:
#>
#> intersect, setdiff, setequal, union
proc_data <- syn_data
proc_data$adcm <- proc_data$adcm %>%
filter(ATIREL == "CONCOMITANT")
run(cmt01a, proc_data)
#> ATC Level 2 Text A: Drug X B: Placebo C: Combination
#> Other Treatment (N=134) (N=134) (N=132)
#> ———————————————————————————————————————————————————————————————————————————————————————————————————
#> Total number of patients with at least one treatment 117 (87.3%) 116 (86.6%) 116 (87.9%)
#> Total number of treatments 415 414 460
#> ATCCLAS2 A
#> Total number of patients with at least one treatment 75 (56.0%) 79 (59.0%) 81 (61.4%)
#> Total number of treatments 134 137 143
#> medname A_2/3 53 (39.6%) 50 (37.3%) 56 (42.4%)
#> medname A_3/3 45 (33.6%) 54 (40.3%) 48 (36.4%)
#> ATCCLAS2 A p2
#> Total number of patients with at least one treatment 45 (33.6%) 54 (40.3%) 48 (36.4%)
#> Total number of treatments 58 66 64
#> medname A_3/3 45 (33.6%) 54 (40.3%) 48 (36.4%)
#> ATCCLAS2 B
#> Total number of patients with at least one treatment 83 (61.9%) 74 (55.2%) 88 (66.7%)
#> Total number of treatments 141 137 162
#> medname B_1/4 52 (38.8%) 57 (42.5%) 59 (44.7%)
#> medname B_4/4 50 (37.3%) 45 (33.6%) 55 (41.7%)
#> ATCCLAS2 B p2
#> Total number of patients with at least one treatment 52 (38.8%) 57 (42.5%) 59 (44.7%)
#> Total number of treatments 75 82 83
#> medname B_1/4 52 (38.8%) 57 (42.5%) 59 (44.7%)
#> ATCCLAS2 B p3
#> Total number of patients with at least one treatment 52 (38.8%) 57 (42.5%) 59 (44.7%)
#> Total number of treatments 75 82 83
#> medname B_1/4 52 (38.8%) 57 (42.5%) 59 (44.7%)
#> ATCCLAS2 C
#> Total number of patients with at least one treatment 82 (61.2%) 84 (62.7%) 89 (67.4%)
#> Total number of treatments 140 140 155
#> medname C_2/2 52 (38.8%) 58 (43.3%) 60 (45.5%)
#> medname C_1/2 51 (38.1%) 50 (37.3%) 56 (42.4%)
#> ATCCLAS2 C p2
#> Total number of patients with at least one treatment 82 (61.2%) 84 (62.7%) 89 (67.4%)
#> Total number of treatments 140 140 155
#> medname C_2/2 52 (38.8%) 58 (43.3%) 60 (45.5%)
#> medname C_1/2 51 (38.1%) 50 (37.3%) 56 (42.4%)
#> ATCCLAS2 C p3
#> Total number of patients with at least one treatment 52 (38.8%) 58 (43.3%) 60 (45.5%)
#> Total number of treatments 69 73 80
#> medname C_2/2 52 (38.8%) 58 (43.3%) 60 (45.5%)