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Table Styling and Formatting

library(sumExtras)
library(gtsummary)
library(dplyr)
library(gt)

use_jama_theme()

Group Headers

gtsummary::add_variable_group_header() creates section headers in your table. {sumExtras} provides functions to style them.

trial |>
  select(age, marker, grade, stage, response, trt) |>
  tbl_summary(by = trt) |>
  extras() |>
  add_variable_group_header(
    header = "Demographics",
    variables = age
  ) |>
  add_variable_group_header(
    header = "Clinical Measures",
    variables = marker:response
  )
Overall
N = 2001		 Drug A
N = 981		 Drug B
N = 1021		 p-value2
Demographics



    Age 47 (38, 57) 46 (37, 60) 48 (39, 56) 0.718
    Unknown 11 7 4
Clinical Measures



    Marker Level (ng/mL) 0.64 (0.22, 1.41) 0.84 (0.23, 1.60) 0.52 (0.18, 1.21) 0.085
    Unknown 10 6 4
    Grade


0.871
    I 68 (34%) 35 (36%) 33 (32%)
    II 68 (34%) 32 (33%) 36 (35%)
    III 64 (32%) 31 (32%) 33 (32%)
    T Stage


0.866
    T1 53 (27%) 28 (29%) 25 (25%)
    T2 54 (27%) 25 (26%) 29 (28%)
    T3 43 (22%) 22 (22%) 21 (21%)
    T4 50 (25%) 23 (23%) 27 (26%)
    Tumor Response 61 (32%) 28 (29%) 33 (34%) 0.530
    Unknown 7 3 4
1 Median (Q1, Q3); n (%)
2 Wilcoxon rank sum test; Pearson’s Chi-squared test

The headers are there, but they don’t stand out. That’s where add_group_styling() comes in.

add_group_styling()

Adds bold and/or italic formatting to group headers. Also restores left-justified variable label indentation that add_variable_group_header() changes.

Without styling

trial |>
  select(age, marker, grade, stage, trt) |>
  tbl_summary(by = trt) |>
  extras() |>
  add_variable_group_header(
    header = "Patient Variables",
    variables = age:stage
  )

With add_group_styling()

trial |>
  select(age, marker, grade, stage, trt) |>
  tbl_summary(by = trt) |>
  extras() |>
  add_variable_group_header(
    header = "Patient Variables",
    variables = age:stage
  ) |>
  add_group_styling()
Overall
N = 2001		 Drug A
N = 981		 Drug B
N = 1021		 p-value2
Patient Variables



    Age 47 (38, 57) 46 (37, 60) 48 (39, 56) 0.718
    Unknown 11 7 4
    Marker Level (ng/mL) 0.64 (0.22, 1.41) 0.84 (0.23, 1.60) 0.52 (0.18, 1.21) 0.085
    Unknown 10 6 4
    Grade


0.871
    I 68 (34%) 35 (36%) 33 (32%)
    II 68 (34%) 32 (33%) 36 (35%)
    III 64 (32%) 31 (32%) 33 (32%)
    T Stage


0.866
    T1 53 (27%) 28 (29%) 25 (25%)
    T2 54 (27%) 25 (26%) 29 (28%)
    T3 43 (22%) 22 (22%) 21 (21%)
    T4 50 (25%) 23 (23%) 27 (26%)
1 Median (Q1, Q3); n (%)
2 Wilcoxon rank sum test; Pearson’s Chi-squared test
Overall
N = 2001		 Drug A
N = 981		 Drug B
N = 1021		 p-value2
Patient Variables



Age 47 (38, 57) 46 (37, 60) 48 (39, 56) 0.718
    Unknown 11 7 4
Marker Level (ng/mL) 0.64 (0.22, 1.41) 0.84 (0.23, 1.60) 0.52 (0.18, 1.21) 0.085
    Unknown 10 6 4
Grade


0.871
    I 68 (34%) 35 (36%) 33 (32%)
    II 68 (34%) 32 (33%) 36 (35%)
    III 64 (32%) 31 (32%) 33 (32%)
T Stage


0.866
    T1 53 (27%) 28 (29%) 25 (25%)
    T2 54 (27%) 25 (26%) 29 (28%)
    T3 43 (22%) 22 (22%) 21 (21%)
    T4 50 (25%) 23 (23%) 27 (26%)
1 Median (Q1, Q3); n (%)
2 Wilcoxon rank sum test; Pearson’s Chi-squared test

The format argument controls the text style:

# Bold only
trial |>
  select(age, marker, grade, stage, trt) |>
  tbl_summary(by = trt) |>
  extras() |>
  add_variable_group_header(
    header = "Patient Characteristics",
    variables = age:stage
  ) |>
  add_group_styling(format = "bold")
Overall
N = 2001		 Drug A
N = 981		 Drug B
N = 1021		 p-value2
Patient Characteristics



Age 47 (38, 57) 46 (37, 60) 48 (39, 56) 0.718
    Unknown 11 7 4
Marker Level (ng/mL) 0.64 (0.22, 1.41) 0.84 (0.23, 1.60) 0.52 (0.18, 1.21) 0.085
    Unknown 10 6 4
Grade


0.871
    I 68 (34%) 35 (36%) 33 (32%)
    II 68 (34%) 32 (33%) 36 (35%)
    III 64 (32%) 31 (32%) 33 (32%)
T Stage


0.866
    T1 53 (27%) 28 (29%) 25 (25%)
    T2 54 (27%) 25 (26%) 29 (28%)
    T3 43 (22%) 22 (22%) 21 (21%)
    T4 50 (25%) 23 (23%) 27 (26%)
1 Median (Q1, Q3); n (%)
2 Wilcoxon rank sum test; Pearson’s Chi-squared test

Options are "bold", "italic", or c("bold", "italic") (the default).

add_group_colors()

Adds a background color to group header rows. This is a terminal operation in that it converts the table to {gt}. It must be the last step in your pipeline.

trial |>
  select(age, marker, grade, stage, response, trt) |>
  tbl_summary(by = trt) |>
  extras() |>
  add_variable_group_header(
    header = "Demographics",
    variables = age
  ) |>
  add_variable_group_header(
    header = "Clinical Measures",
    variables = marker:response
  ) |>
  add_group_styling() |>
  add_group_colors(color = "#E3F2FD")
Overall
N = 2001		 Drug A
N = 981		 Drug B
N = 1021		 p-value2
Demographics



Age 47 (38, 57) 46 (37, 60) 48 (39, 56) 0.718
    Unknown 11 7 4
Clinical Measures



Marker Level (ng/mL) 0.64 (0.22, 1.41) 0.84 (0.23, 1.60) 0.52 (0.18, 1.21) 0.085
    Unknown 10 6 4
Grade


0.871
    I 68 (34%) 35 (36%) 33 (32%)
    II 68 (34%) 32 (33%) 36 (35%)
    III 64 (32%) 31 (32%) 33 (32%)
T Stage


0.866
    T1 53 (27%) 28 (29%) 25 (25%)
    T2 54 (27%) 25 (26%) 29 (28%)
    T3 43 (22%) 22 (22%) 21 (21%)
    T4 50 (25%) 23 (23%) 27 (26%)
Tumor Response 61 (32%) 28 (29%) 33 (34%) 0.530
    Unknown 7 3 4
1 Median (Q1, Q3); n (%)
2 Wilcoxon rank sum test; Pearson’s Chi-squared test

The default color is "#E8E8E8" (light gray). Pass any CSS color string, or a vector of colors (one per group):

trial |>
  select(age, marker, grade, stage, response, trt) |>
  tbl_summary(by = trt) |>
  extras() |>
  add_variable_group_header(
    header = "Demographics",
    variables = age
  ) |>
  add_variable_group_header(
    header = "Clinical Measures",
    variables = marker:response
  ) |>
  add_group_styling() |>
  add_group_colors(color = c("#E3F2FD", "#FFF9E6"))
Overall
N = 2001		 Drug A
N = 981		 Drug B
N = 1021		 p-value2
Demographics



Age 47 (38, 57) 46 (37, 60) 48 (39, 56) 0.718
    Unknown 11 7 4
Clinical Measures



Marker Level (ng/mL) 0.64 (0.22, 1.41) 0.84 (0.23, 1.60) 0.52 (0.18, 1.21) 0.085
    Unknown 10 6 4
Grade


0.871
    I 68 (34%) 35 (36%) 33 (32%)
    II 68 (34%) 32 (33%) 36 (35%)
    III 64 (32%) 31 (32%) 33 (32%)
T Stage


0.866
    T1 53 (27%) 28 (29%) 25 (25%)
    T2 54 (27%) 25 (26%) 29 (28%)
    T3 43 (22%) 22 (22%) 21 (21%)
    T4 50 (25%) 23 (23%) 27 (26%)
Tumor Response 61 (32%) 28 (29%) 33 (34%) 0.530
    Unknown 7 3 4
1 Median (Q1, Q3); n (%)
2 Wilcoxon rank sum test; Pearson’s Chi-squared test

get_group_rows()

If you need more control than add_group_colors() provides, get_group_rows() returns the row indices of group headers. You can then use those with gt::tab_style() directly:

my_table <- trial |>
  select(age, marker, grade, stage, trt) |>
  tbl_summary(by = trt) |>
  extras() |>
  add_variable_group_header(
    header = "Demographics",
    variables = age:marker
  ) |>
  add_variable_group_header(
    header = "Disease",
    variables = grade:stage
  ) |>
  add_group_styling()

group_rows <- get_group_rows(my_table)

my_table |>
  as_gt() |>
  gt::tab_style(
    style = list(
      gt::cell_fill(color = "#E8E8E8"),
      gt::cell_text(weight = "bold")
    ),
    locations = gt::cells_body(rows = group_rows)
  )
Overall
N = 2001		 Drug A
N = 981		 Drug B
N = 1021		 p-value2
Demographics



Age 47 (38, 57) 46 (37, 60) 48 (39, 56) 0.718
    Unknown 11 7 4
Marker Level (ng/mL) 0.64 (0.22, 1.41) 0.84 (0.23, 1.60) 0.52 (0.18, 1.21) 0.085
    Unknown 10 6 4
Disease



Grade


0.871
    I 68 (34%) 35 (36%) 33 (32%)
    II 68 (34%) 32 (33%) 36 (35%)
    III 64 (32%) 31 (32%) 33 (32%)
T Stage


0.866
    T1 53 (27%) 28 (29%) 25 (25%)
    T2 54 (27%) 25 (26%) 29 (28%)
    T3 43 (22%) 22 (22%) 21 (21%)
    T4 50 (25%) 23 (23%) 27 (26%)
1 Median (Q1, Q3); n (%)
2 Wilcoxon rank sum test; Pearson’s Chi-squared test

Matching gt Tables with theme_gt_compact()

If you mix {gtsummary} tables with plain {gt} tables in the same document, they won’t match visually. theme_gt_compact() applies the same JAMA compact look to {gt} tables so everything is consistent:

gtsummary with extras()

trial |>
  tbl_summary(
    by = trt,
    include = c(age, grade, marker)
  ) |>
  extras()

gt with theme_gt_compact()

trial |>
  select(trt, age, grade, marker) |>
  head(10) |>
  gt() |>
  theme_gt_compact()
Overall
N = 2001		 Drug A
N = 981		 Drug B
N = 1021		 p-value2
Age 47 (38, 57) 46 (37, 60) 48 (39, 56) 0.718
    Unknown 11 7 4
Grade


0.871
    I 68 (34%) 35 (36%) 33 (32%)
    II 68 (34%) 32 (33%) 36 (35%)
    III 64 (32%) 31 (32%) 33 (32%)
Marker Level (ng/mL) 0.64 (0.22, 1.41) 0.84 (0.23, 1.60) 0.52 (0.18, 1.21) 0.085
    Unknown 10 6 4
1 Median (Q1, Q3); n (%)
2 Wilcoxon rank sum test; Pearson’s Chi-squared test
Chemotherapy Treatment Age Grade Marker Level (ng/mL)
Drug A 23 II 0.160
Drug B 9 I 1.107
Drug A 31 II 0.277
Drug A NA III 2.067
Drug A 51 III 2.767
Drug B 39 I 0.613
Drug A 37 II 0.354
Drug A 32 I 1.739
Drug A 31 II 0.144
Drug B 34 I 0.205

See vignette("themes") for more on theming.

Complete Example

dictionary <- tibble::tribble(
  ~variable,    ~description,
  "trt",        "Treatment Assignment",
  "age",        "Age at Baseline (years)",
  "marker",     "Biomarker Level (ng/mL)",
  "stage",      "Clinical Stage",
  "grade",      "Tumor Grade",
  "response",   "Treatment Response",
  "death",      "Patient Died"
)

trial |>
  select(trt, age, marker, grade, stage, response, death) |>
  tbl_summary(by = trt, missing = "no") |>
  add_auto_labels(dictionary = dictionary) |>
  extras() |>
  add_variable_group_header(
    header = "BASELINE CHARACTERISTICS",
    variables = age:marker
  ) |>
  add_variable_group_header(
    header = "DISEASE CHARACTERISTICS",
    variables = grade:stage
  ) |>
  add_variable_group_header(
    header = "OUTCOMES",
    variables = response:death
  ) |>
  add_group_styling() |>
  add_group_colors(color = "#E8E8E8")
Overall
N = 2001		 Drug A
N = 981		 Drug B
N = 1021		 p-value2
BASELINE CHARACTERISTICS



Age 47 (38, 57) 46 (37, 60) 48 (39, 56) 0.718
Marker Level (ng/mL) 0.64 (0.22, 1.41) 0.84 (0.23, 1.60) 0.52 (0.18, 1.21) 0.085
DISEASE CHARACTERISTICS



Grade


0.871
    I 68 (34%) 35 (36%) 33 (32%)
    II 68 (34%) 32 (33%) 36 (35%)
    III 64 (32%) 31 (32%) 33 (32%)
T Stage


0.866
    T1 53 (27%) 28 (29%) 25 (25%)
    T2 54 (27%) 25 (26%) 29 (28%)
    T3 43 (22%) 22 (22%) 21 (21%)
    T4 50 (25%) 23 (23%) 27 (26%)
OUTCOMES



Tumor Response 61 (32%) 28 (29%) 33 (34%) 0.530
Patient Died 112 (56%) 52 (53%) 60 (59%) 0.412
1 Median (Q1, Q3); n (%)
2 Wilcoxon rank sum test; Pearson’s Chi-squared test

More Vignettes

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.