Change from Baseline

Source: R/tbl_baseline_chg.R

Typical use is tabulating changes from baseline measurement of an Analysis Variable.

tbl_baseline_chg(
  data,
  baseline_level,
  denominator,
  by = NULL,
  digits = NULL,
  id = "USUBJID",
  visit = "AVISIT",
  visit_number = "AVISITN",
  analysis_variable = "AVAL",
  change_variable = "CHG"
)

# S3 method for class 'tbl_baseline_chg'
add_overall(
  x,
  last = FALSE,
  col_label = "All Participants  \n(N = {style_roche_number(n)})",
  ...
)

Arguments

data

(data.frame)
A data frame.

baseline_level

(string)
String identifying baseline level in the visit variable.

denominator

(data.frame)
Data set used to compute the header counts (typically ADSL).

by

(tidy-select)
A single column from data. Summary statistics will be stratified by this variable. Default is NULL.

digits

(formula-list-selector)
Specifies how summary statistics are rounded. Values may be either integer(s) or function(s). If not specified, default formatting is assigned via assign_summary_digits(). See below for details.

id

(tidy-select)
String identifying the unique subjects. Default is 'USUBJID'.

visit

(tidy-select)
String for the visit variable. Default is 'AVISIT'. If there are more than one entry for each visit and subject, only the first row is kept.

visit_number

(tidy-select)
String identifying the visit or analysis sequence number. Default is 'AVISITN'.

analysis_variable

(tidy-select)
String identifying the analysis values. Default is 'AVAL'.

change_variable

(tidy-select)
String identifying the change from baseline values. Default is 'CHG'.

x

(tbl_summary, tbl_svysummary, tbl_continuous, tbl_custom_summary)
A stratified 'gtsummary' table

last

(scalar logical)
Logical indicator to display overall column last in table. Default is FALSE, which will display overall column first.

col_label

(string)
String indicating the column label. Default is "**Overall** \nN = {style_number(N)}"

...

These dots are for future extensions and must be empty.

Value

A gtsummary table.

Examples

theme_gtsummary_roche()
#> Setting theme "Roche"

df <- cards::ADLB |>
  dplyr::mutate(AVISIT = trimws(AVISIT)) |>
  dplyr::filter(
    AVISIT != "End of Treatment",
    PARAMCD %in% c("SODIUM", "K")
  )

tbl_baseline_chg(
  data = df |> dplyr::filter(PARAMCD == "SODIUM"),
  baseline_level = "Baseline",
  by = "TRTA",
  denominator = cards::ADSL
)
#> ℹ Converting column "TRTA" to a factor.



  
Visit
      
        
Placebo

(N = 86)

      		
      
        
Xanomeline High Dose

(N = 84)

      		
      
        
Xanomeline Low Dose

(N = 84)

      		
    
Value at Visit
      Change from Baseline
      Value at Visit
      Change from Baseline
      Value at Visit
      Change from Baseline
    
Baseline











    n
7


7


6

    Mean (SD)
141.1 (1.5)


139.1 (2.2)


139.5 (4.2)

    Median
141.0


139.0


138.5

    Min - Max
140 - 144


136 - 142


134 - 145

Week 2











    n
7
7
6
6
6
6
    Mean (SD)
140.6 (1.6)
-0.6 (1.9)
138.8 (3.3)
0.2 (3.5)
139.5 (2.3)
0.0 (3.7)
    Median
141.0
-1.0
140.5
0.5
139.5
-0.5
    Min - Max
138 - 142
-3 - 2
133 - 141
-5 - 5
136 - 142
-5 - 5
Week 4











    n
7
7
6
6
5
5
    Mean (SD)
139.3 (2.8)
-1.9 (2.5)
139.8 (3.5)
1.2 (2.0)
139.4 (1.3)
-0.6 (3.5)
    Median
140.0
-1.0
138.5
0.0
140.0
0.0
    Min - Max
134 - 142
-7 - 0
138 - 147
0 - 5
138 - 141
-5 - 4
Week 6











    n
5
5
6
6
4
4
    Mean (SD)
140.0 (1.9)
-0.4 (1.7)
139.7 (2.0)
1.0 (2.3)
140.5 (2.6)
1.8 (5.4)
    Median
140.0
0.0
139.0
0.5
140.0
2.5
    Min - Max
138 - 143
-2 - 2
138 - 143
-1 - 5
138 - 144
-5 - 7
Week 8











    n
5
5
4
4
3
3
    Mean (SD)
140.6 (1.5)
0.2 (1.6)
139.0 (2.2)
-0.5 (2.4)
139.0 (2.6)
0.0 (3.5)
    Median
141.0
1.0
139.5
-0.5
140.0
2.0
    Min - Max
139 - 142
-2 - 2
136 - 141
-3 - 2
136 - 141
-4 - 2
Week 12











    n
5
5
4
4
2
2
    Mean (SD)
141.0 (1.6)
0.6 (1.1)
140.8 (3.0)
1.3 (1.3)
139.0 (0.0)
0.0 (7.1)
    Median
141.0
1.0
140.0
1.0
139.0
0.0
    Min - Max
139 - 143
-1 - 2
138 - 145
0 - 3
139 - 139
-5 - 5
Week 16











    n
5
5
4
4
2
2
    Mean (SD)
140.8 (1.1)
0.4 (0.9)
142.0 (3.6)
2.5 (1.9)
139.5 (0.7)
0.5 (6.4)
    Median
141.0
1.0
141.0
2.0
139.5
0.5
    Min - Max
139 - 142
-1 - 1
139 - 147
1 - 5
139 - 140
-4 - 5
Week 20











    n
5
5
4
4
2
2
    Mean (SD)
141.6 (1.7)
1.2 (1.9)
138.8 (3.6)
-0.8 (2.2)
137.5 (0.7)
-1.5 (6.4)
    Median
142.0
2.0
137.5
-1.0
137.5
-1.5
    Min - Max
139 - 143
-2 - 3
136 - 144
-3 - 2
137 - 138
-6 - 3
Week 24











    n
5
5
4
4
2
2
    Mean (SD)
140.4 (1.1)
0.0 (1.2)
139.3 (3.6)
-0.3 (2.6)
138.0 (2.8)
-1.0 (4.2)
    Median
140.0
0.0
140.5
0.5
138.0
-1.0
    Min - Max
139 - 142
-2 - 1
134 - 142
-4 - 2
136 - 140
-4 - 2
Week 26











    n
5
5
4
4
2
2
    Mean (SD)
140.6 (2.5)
0.2 (2.8)
138.8 (4.6)
-0.8 (2.9)
142.5 (2.1)
3.5 (4.9)
    Median
140.0
-1.0
138.0
-1.0
142.5
3.5
    Min - Max
139 - 145
-2 - 5
134 - 145
-4 - 3
141 - 144
0 - 7

tbl_baseline_chg(
  data = df |> dplyr::filter(PARAMCD == "K"),
  baseline_level = "Baseline",
  by = "TRTA",
  denominator = cards::ADSL
) |>
  add_overall(last = TRUE, col_label = "All Participants")
#> ℹ Converting column "TRTA" to a factor.



  
Visit
      
        
Placebo

(N = 86)

      		
      
        
Xanomeline High Dose

(N = 84)

      		
      
        
Xanomeline Low Dose

(N = 84)

      		
      
        
All Participants

      		
    
Value at Visit
      Change from Baseline
      Value at Visit
      Change from Baseline
      Value at Visit
      Change from Baseline
      Value at Visit
      Change from Baseline
    
Baseline















    n
7


7


6


20

    Mean (SD)
4.34 (0.40)


4.30 (0.18)


4.23 (0.37)


4.30 (0.31)

    Median
4.30


4.40


4.20


4.30

    Min - Max
3.7 - 4.9


4.0 - 4.5


3.8 - 4.7


3.7 - 4.9

Week 2















    n
7
7
6
6
6
6
19
19
    Mean (SD)
4.47 (0.42)
0.13 (0.46)
4.35 (0.27)
0.07 (0.12)
4.57 (0.38)
0.33 (0.40)
4.46 (0.36)
0.17 (0.36)
    Median
4.50
-0.10
4.40
0.05
4.60
0.25
4.50
0.10
    Min - Max
3.9 - 5.1
-0.4 - 1.0
3.9 - 4.6
-0.1 - 0.2
4.1 - 5.1
-0.2 - 0.8
3.9 - 5.1
-0.4 - 1.0
Week 4















    n
7
7
6
6
5
5
18
18
    Mean (SD)
4.44 (0.38)
0.10 (0.37)
4.32 (0.46)
-0.02 (0.32)
4.46 (0.39)
0.16 (0.26)
4.41 (0.39)
0.08 (0.32)
    Median
4.60
0.00
4.45
0.05
4.70
0.20
4.55
0.05
    Min - Max
3.9 - 4.8
-0.4 - 0.7
3.4 - 4.6
-0.6 - 0.3
3.9 - 4.8
-0.2 - 0.4
3.4 - 4.8
-0.6 - 0.7
Week 6















    n
5
5
6
6
4
4
15
15
    Mean (SD)
4.50 (0.35)
0.26 (0.26)
4.20 (0.23)
-0.13 (0.12)
4.53 (0.59)
0.18 (0.59)
4.39 (0.39)
0.08 (0.36)
    Median
4.60
0.10
4.25
-0.15
4.45
0.05
4.30
0.00
    Min - Max
4.0 - 4.8
0.1 - 0.7
3.8 - 4.4
-0.3 - 0.0
3.9 - 5.3
-0.4 - 1.0
3.8 - 5.3
-0.4 - 1.0
Week 8















    n
5
5
4
4
3
3
12
12
    Mean (SD)
4.18 (0.23)
-0.06 (0.33)
4.18 (0.56)
-0.13 (0.41)
4.73 (0.25)
0.50 (0.17)
4.32 (0.42)
0.06 (0.40)
    Median
4.10
0.00
4.20
-0.20
4.70
0.40
4.35
0.10
    Min - Max
3.9 - 4.5
-0.4 - 0.3
3.5 - 4.8
-0.5 - 0.4
4.5 - 5.0
0.4 - 0.7
3.5 - 5.0
-0.5 - 0.7
Week 12















    n
5
5
4
4
2
2
11
11
    Mean (SD)
4.06 (0.31)
-0.18 (0.50)
4.13 (0.22)
-0.18 (0.24)
4.10 (0.14)
-0.10 (0.42)
4.09 (0.24)
-0.16 (0.37)
    Median
4.20
0.10
4.10
-0.10
4.10
-0.10
4.20
0.00
    Min - Max
3.6 - 4.4
-0.9 - 0.2
3.9 - 4.4
-0.5 - 0.0
4.0 - 4.2
-0.4 - 0.2
3.6 - 4.4
-0.9 - 0.2
Week 16















    n
5
5
4
4
2
2
11
11
    Mean (SD)
4.24 (0.47)
0.00 (0.47)
4.35 (0.51)
0.05 (0.35)
4.35 (0.49)
0.15 (0.07)
4.30 (0.44)
0.05 (0.36)
    Median
4.10
-0.20
4.45
0.05
4.35
0.15
4.20
0.00
    Min - Max
3.7 - 4.9
-0.4 - 0.8
3.7 - 4.8
-0.3 - 0.4
4.0 - 4.7
0.1 - 0.2
3.7 - 4.9
-0.4 - 0.8
Week 20















    n
5
5
4
4
2
2
11
11
    Mean (SD)
4.26 (0.39)
0.02 (0.50)
4.15 (0.26)
-0.15 (0.26)
4.10 (0.14)
-0.10 (0.42)
4.19 (0.30)
-0.06 (0.38)
    Median
4.20
-0.20
4.10
-0.10
4.10
-0.10
4.20
-0.20
    Min - Max
3.9 - 4.9
-0.5 - 0.8
3.9 - 4.5
-0.5 - 0.1
4.0 - 4.2
-0.4 - 0.2
3.9 - 4.9
-0.5 - 0.8
Week 24















    n
5
5
4
4
2
2
11
11
    Mean (SD)
4.26 (0.32)
0.02 (0.29)
4.20 (0.41)
-0.10 (0.32)
4.00 (0.14)
-0.20 (0.42)
4.19 (0.32)
-0.06 (0.30)
    Median
4.30
0.10
4.20
-0.05
4.00
-0.20
4.10
0.10
    Min - Max
3.8 - 4.6
-0.4 - 0.4
3.8 - 4.6
-0.5 - 0.2
3.9 - 4.1
-0.5 - 0.1
3.8 - 4.6
-0.5 - 0.4
Week 26















    n
5
5
4
4
2
2
11
11
    Mean (SD)
4.18 (0.37)
-0.06 (0.36)
4.28 (0.46)
-0.03 (0.31)
4.50 (0.71)
0.30 (0.14)
4.27 (0.43)
0.02 (0.32)
    Median
4.20
0.00
4.30
-0.10
4.50
0.30
4.20
0.00
    Min - Max
3.6 - 4.5
-0.6 - 0.4
3.7 - 4.8
-0.3 - 0.4
4.0 - 5.0
0.2 - 0.4
3.6 - 5.0
-0.6 - 0.4

# Split by PARAM
tbl_strata(
  data = df,
  strata = PARAMCD,
  .tbl_fun = ~ tbl_baseline_chg(
    data = .x,
    baseline_level = "Baseline",
    by = "TRTA",
    denominator = cards::ADSL
  ),
  .combine_with = "tbl_stack",
  .combine_args = list(group_header = NULL, quiet = TRUE)
) |>
  tbl_split_by_rows(variable_level = ends_with("lbl"))
#> ℹ Converting column "TRTA" to a factor.
#> ℹ Converting column "TRTA" to a factor.
#> 
#> ── Printing 2 Tables ──
#> 
#> ── Table 1 of 2: K 
#> 
#> ── Table 2 of 2: SODIUM