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Summary tables for AE

Source: R/ae_table_grade.R
ae_table_grade.Rd

[Stable]
The function ae_table_grade() creates a summary table of maximum AE grades for each patient according to the CTCAE grade. The resulting dataframe can be piped to as_flextable() to get a nicely formatted flextable.

Usage

ae_table_grade(
  df_ae,
  ...,
  df_enrol,
  variant = c("max", "sup", "eq"),
  arm = NULL,
  grade = "AEGR",
  subjid = "SUBJID",
  ae_label = "AE",
  percent = TRUE,
  digits = 2,
  total = TRUE
)

Arguments

df_ae

adverse event dataset, one row per AE, containing subjid, soc, and grade.

...

unused

df_enrol

enrollment dataset, one row per patient, containing subjid (and arm if needed). All patients should be in this dataset.

variant

one or several of c("max", "sup", "eq"). max computes the maximum AE grade per patient, sup computes the number of patients having experienced at least one AE of grade higher or equal to X, and eq computes the number of patients having experienced at least one AE of grade equal to X.

arm

name of the treatment column in df_enrol. Case-insensitive. Can be set to NULL.

grade

name of the AE grade column in df_ae. Case-insensitive.

subjid

name of the patient ID in both df_ae and df_enrol. Case-insensitive.

ae_label

the label of adverse events, usually "AE" or "SAE".

percent

whether to show percentages with counts. Defaults to TRUE. Can also be "only" to not show counts.

digits

significant digits for percentages.

total

whether to add a total column for each arm.

Value

a crosstable

See also

ae_table_grade(), ae_table_soc(), ae_plot_grade(), ae_plot_grade_sum(), butterfly_plot()

Examples

tm = grstat_example()
attach(tm, warn.conflicts=FALSE)

ae_table_grade(df_ae=ae, df_enrol=enrolres, arm=NULL) %>%
  as_flextable(header_show_n=TRUE)

label
variable
Treatment arm
All patients (N=200)
Patient maximum AE grade
No declared AE
3 (2%)
Grade 1
35 (18%)
Grade 2
62 (31%)
Grade 3
51 (26%)
Grade 4
39 (20%)
Grade 5
10 (5%)
Patient had at least one AE of grade
No declared AE
3 (2%)
Grade ≥ 1
197 (98%)
Grade ≥ 2
162 (81%)
Grade ≥ 3
100 (50%)
Grade ≥ 4
49 (24%)
Grade = 5
10 (5%)
Patient had at least one AE of grade 
No declared AE
3 (2%)
Grade 1
164 (82%)
Grade 2
117 (58%)
Grade 3
62 (31%)
Grade 4
44 (22%)
Grade 5
10 (5%)

ae_table_grade(df_ae=ae, df_enrol=enrolres, arm="arm") %>%
  as_flextable(header_show_n=TRUE)

label
variable
Treatment arm
Total
Control (N=100)
Treatment (N=100)
Patient maximum AE grade
No declared AE
3 (3%)
0 (0%)
3 (2%)
Grade 1
27 (27%)
8 (8%)
35 (18%)
Grade 2
32 (32%)
30 (30%)
62 (31%)
Grade 3
23 (23%)
28 (28%)
51 (26%)
Grade 4
14 (14%)
25 (25%)
39 (20%)
Grade 5
1 (1%)
9 (9%)
10 (5%)
Patient had at least one AE of grade
No declared AE
3 (3%)
0 (0%)
3 (2%)
Grade ≥ 1
97 (97%)
100 (100%)
197 (98%)
Grade ≥ 2
70 (70%)
92 (92%)
162 (81%)
Grade ≥ 3
38 (38%)
62 (62%)
100 (50%)
Grade ≥ 4
15 (15%)
34 (34%)
49 (24%)
Grade = 5
1 (1%)
9 (9%)
10 (5%)
Patient had at least one AE of grade 
No declared AE
3 (3%)
0 (0%)
3 (2%)
Grade 1
83 (83%)
81 (81%)
164 (82%)
Grade 2
53 (53%)
64 (64%)
117 (58%)
Grade 3
25 (25%)
37 (37%)
62 (31%)
Grade 4
15 (15%)
29 (29%)
44 (22%)
Grade 5
1 (1%)
9 (9%)
10 (5%)

#To get SAE only, filter df_ae first
ae %>%
  dplyr::filter(sae=="Yes") %>%
  ae_table_grade(df_enrol=enrolres, arm="arm", ae_label="SAE") %>%
  as_flextable(header_show_n=TRUE)

label
variable
Treatment arm
Total
Control (N=100)
Treatment (N=100)
Patient maximum SAE grade
No declared SAE
73 (73%)
77 (77%)
150 (75%)
Grade 1
10 (10%)
1 (1%)
11 (6%)
Grade 2
6 (6%)
3 (3%)
9 (4%)
Grade 3
3 (3%)
7 (7%)
10 (5%)
Grade 4
8 (8%)
8 (8%)
16 (8%)
Grade 5
0 (0%)
4 (4%)
4 (2%)
Patient had at least one SAE of grade
No declared SAE
73 (73%)
77 (77%)
150 (75%)
Grade ≥ 1
27 (27%)
23 (23%)
50 (25%)
Grade ≥ 2
17 (17%)
22 (22%)
39 (20%)
Grade ≥ 3
11 (11%)
19 (19%)
30 (15%)
Grade ≥ 4
8 (8%)
12 (12%)
20 (10%)
Grade = 5
0 (0%)
4 (4%)
4 (2%)
Patient had at least one SAE of grade 
No declared SAE
73 (73%)
77 (77%)
150 (75%)
Grade 1
10 (10%)
2 (2%)
12 (6%)
Grade 2
8 (8%)
3 (3%)
11 (6%)
Grade 3
5 (5%)
8 (8%)
13 (6%)
Grade 4
8 (8%)
8 (8%)
16 (8%)
Grade 5
0 (0%)
4 (4%)
4 (2%)

#To describe a sub-population, filter df_enrol first
enrolres2 = enrolres %>%
  dplyr::filter(arm=="Control")
ae %>%
  ae_table_grade(df_enrol=enrolres2, arm="arm") %>%
  as_flextable(header_show_n=TRUE)

label
variable
Treatment arm
Total
Control (N=100)
Patient maximum AE grade
No declared AE
3 (3%)
3 (3%)
Grade 1
27 (27%)
27 (27%)
Grade 2
32 (32%)
32 (32%)
Grade 3
23 (23%)
23 (23%)
Grade 4
14 (14%)
14 (14%)
Grade 5
1 (1%)
1 (1%)
Patient had at least one AE of grade
No declared AE
3 (3%)
3 (3%)
Grade ≥ 1
97 (97%)
97 (97%)
Grade ≥ 2
70 (70%)
70 (70%)
Grade ≥ 3
38 (38%)
38 (38%)
Grade ≥ 4
15 (15%)
15 (15%)
Grade = 5
1 (1%)
1 (1%)
Patient had at least one AE of grade 
No declared AE
3 (3%)
3 (3%)
Grade 1
83 (83%)
83 (83%)
Grade 2
53 (53%)
53 (53%)
Grade 3
25 (25%)
25 (25%)
Grade 4
15 (15%)
15 (15%)
Grade 5
1 (1%)
1 (1%)

#You can also filter the AE table
ae %>%
  ae_table_grade(df_enrol=enrolres, arm="arm") %>%
  dplyr::filter(!variable %in% c("Grade 1", "Grade 2")) %>%
  as_flextable(header_show_n=TRUE)

label
variable
Treatment arm
Total
Control (N=100)
Treatment (N=100)
Patient maximum AE grade
No declared AE
3 (3%)
0 (0%)
3 (2%)
Grade 3
23 (23%)
28 (28%)
51 (26%)
Grade 4
14 (14%)
25 (25%)
39 (20%)
Grade 5
1 (1%)
9 (9%)
10 (5%)
Patient had at least one AE of grade
No declared AE
3 (3%)
0 (0%)
3 (2%)
Grade ≥ 1
97 (97%)
100 (100%)
197 (98%)
Grade ≥ 2
70 (70%)
92 (92%)
162 (81%)
Grade ≥ 3
38 (38%)
62 (62%)
100 (50%)
Grade ≥ 4
15 (15%)
34 (34%)
49 (24%)
Grade = 5
1 (1%)
9 (9%)
10 (5%)
Patient had at least one AE of grade 
No declared AE
3 (3%)
0 (0%)
3 (2%)
Grade 3
25 (25%)
37 (37%)
62 (31%)
Grade 4
15 (15%)
29 (29%)
44 (22%)
Grade 5
1 (1%)
9 (9%)
10 (5%)