#Bivariat ## install.packages(“gtsummary”)

library(gtsummary)

#Cross Table Summary

trial %>%
tbl_summary(
by = trt)

Characteristic	Drug A N = 981	Drug B N = 1021
Age	46 (37, 60)	48 (39, 56)
Unknown	7	4
Marker Level (ng/mL)	0.84 (0.23, 1.60)	0.52 (0.18, 1.21)
Unknown	6	4
T Stage
T1	28 (29%)	25 (25%)
T2	25 (26%)	29 (28%)
T3	22 (22%)	21 (21%)
T4	23 (23%)	27 (26%)
Grade
I	35 (36%)	33 (32%)
II	32 (33%)	36 (35%)
III	31 (32%)	33 (32%)
Tumor Response	28 (29%)	33 (34%)
Unknown	3	4
Patient Died	52 (53%)	60 (59%)
Months to Death/Censor	23.5 (17.4, 24.0)	21.2 (14.5, 24.0)
1 Median (Q1, Q3); n (%)

Table printed with {flextable}, not {gt}. Learn why at

https://www.danieldsjoberg.com/gtsummary/articles/rmarkdown.html

trial %>%
tbl_summary(
by = trt,
statistic = list(
all_continuous() ~ "{mean} ({sd})",
all_categorical() ~ "{n} / {N} ({p}%)"
)
)

Characteristic	Drug A N = 981	Drug B N = 1021
Age	47 (15)	47 (14)
Unknown	7	4
Marker Level (ng/mL)	1.02 (0.89)	0.82 (0.83)
Unknown	6	4
T Stage
T1	28 / 98 (29%)	25 / 102 (25%)
T2	25 / 98 (26%)	29 / 102 (28%)
T3	22 / 98 (22%)	21 / 102 (21%)
T4	23 / 98 (23%)	27 / 102 (26%)
Grade
I	35 / 98 (36%)	33 / 102 (32%)
II	32 / 98 (33%)	36 / 102 (35%)
III	31 / 98 (32%)	33 / 102 (32%)
Tumor Response	28 / 95 (29%)	33 / 98 (34%)
Unknown	3	4
Patient Died	52 / 98 (53%)	60 / 102 (59%)
Months to Death/Censor	20.2 (5.0)	19.0 (5.5)
1 Mean (SD); n / N (%)

##Add p, Add N-n, header

trial %>%
tbl_summary(by = trt) %>%
add_p() %>%
add_overall() %>%
add_n()

Characteristic	N	Overall N = 2001	Drug A N = 981	Drug B N = 1021	p-value2
Age	189	47 (38, 57)	46 (37, 60)	48 (39, 56)	0.7
Unknown		11	7	4
Marker Level (ng/mL)	190	0.64 (0.22, 1.41)	0.84 (0.23, 1.60)	0.52 (0.18, 1.21)	0.085
Unknown		10	6	4
T Stage	200				0.9
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%)
Grade	200				0.9
I		68 (34%)	35 (36%)	33 (32%)
II		68 (34%)	32 (33%)	36 (35%)
III		64 (32%)	31 (32%)	33 (32%)
Tumor Response	193	61 (32%)	28 (29%)	33 (34%)	0.5
Unknown		7	3	4
Patient Died	200	112 (56%)	52 (53%)	60 (59%)	0.4
Months to Death/Censor	200	22.4 (15.9, 24.0)	23.5 (17.4, 24.0)	21.2 (14.5, 24.0)	0.14
1 Median (Q1, Q3); n (%)
2 Wilcoxon rank sum test; Pearson’s Chi-squared test

##Add p, Add N-n, header, spanning_header, footnote, caption

trial %>%
tbl_summary(by = trt) %>%
add_p() %>%
add_overall() %>%
add_n() %>%
modify_header(label ~ "**Variable**") %>%
modify_spanning_header(c("stat_1", "stat_2") ~ "**Treatment Received**")%>%
modify_footnote(
all_stat_cols() ~ "Median (IQR) or Frequency (%)"
) %>%
modify_caption("**Table 1. Patient Characteristics**") %>%
bold_labels()

Table 1. Patient Characteristics

Variable	N	Overall N = 2001	Treatment Received		p-value2
			Drug A N = 981	Drug B N = 1021
Age	189	47 (38, 57)	46 (37, 60)	48 (39, 56)	0.7
Unknown		11	7	4
Marker Level (ng/mL)	190	0.64 (0.22, 1.41)	0.84 (0.23, 1.60)	0.52 (0.18, 1.21)	0.085
Unknown		10	6	4
T Stage	200				0.9
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%)
Grade	200				0.9
I		68 (34%)	35 (36%)	33 (32%)
II		68 (34%)	32 (33%)	36 (35%)
III		64 (32%)	31 (32%)	33 (32%)
Tumor Response	193	61 (32%)	28 (29%)	33 (34%)	0.5
Unknown		7	3	4
Patient Died	200	112 (56%)	52 (53%)	60 (59%)	0.4
Months to Death/Censor	200	22.4 (15.9, 24.0)	23.5 (17.4, 24.0)	21.2 (14.5, 24.0)	0.14
1 Median (IQR) or Frequency (%)
2 Wilcoxon rank sum test; Pearson’s Chi-squared test