Cumulative incidence curve for death, with LT as a competing
event
tidycmprsk::cuminc(Surv(time_90days,status_90days) ~ alcoholic_hepatitis_admission , data = master) %>%
ggcuminc(linetype_aes = T) +
add_confidence_interval() +
add_risktable()+
scale_x_continuous(breaks = seq(0, 90, by = 30), limits = c(0, 90))+
theme(panel.background = element_rect(fill = "white", color = NA),
plot.background = element_rect(fill = "white", color = NA),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank())
## Plotting outcome "1".
Cumulative incidence at 30 60 90 days by group
tidycmprsk::cuminc(Surv(time_90days,status_90days) ~ alcoholic_hepatitis_admission , data = master) %>%
tbl_cuminc(
times = c(30,60,90),
label_header = "**{time}-month cuminc**") %>%
add_p() %>% add_n(location = "level")
| Characteristic |
N |
30-month cuminc |
60-month cuminc |
90-month cuminc |
p-value |
| alcoholic_hepatitis_admission |
|
|
|
|
0.026 |
| 0 |
1,759 |
25% (23%, 27%) |
34% (32%, 36%) |
38% (35%, 40%) |
|
| 1 |
303 |
31% (25%, 36%) |
41% (35%, 47%) |
45% (39%, 51%) |
|
Subdistribution hazard model
tidycmprsk::crr(Surv(time_90days,status_90days) ~ alcoholic_hepatitis_admission, data = master) %>%
tbl_regression(exp = TRUE)
| Characteristic |
HR |
95% CI |
p-value |
| alcoholic_hepatitis_admission |
1.24 |
1.03, 1.50 |
0.024 |
Univariate subdistribution hazard model
tidycmprsk::crr(Surv(time_90days,status_90days) ~ age_admission, data = master) %>%
tbl_regression(exp = TRUE) %>% add_n()
| Characteristic |
N |
HR |
95% CI |
p-value |
| age_admission |
2,062 |
1.00 |
1.00, 1.01 |
0.9 |
tidycmprsk::crr(Surv(time_90days,status_90days) ~ MELD_Na_baseline, data = master) %>%
tbl_regression(exp = TRUE) %>% add_n() %>%
as_gt() %>%
gt::tab_source_note(gt::md("*With 63 missing values*"))
## 63 cases omitted due to missing values
| Characteristic |
N |
HR |
95% CI |
p-value |
| MELD_Na_baseline |
1,999 |
1.06 |
1.05, 1.07 |
<0.001 |
| With 63 missing values |
tidycmprsk::crr(Surv(time_90days,status_90days) ~ CLIF_C_Score, data = master) %>%
tbl_regression(exp = TRUE) %>% add_n()
| Characteristic |
N |
HR |
95% CI |
p-value |
| CLIF_C_Score |
2,062 |
1.07 |
1.07, 1.08 |
<0.001 |
tidycmprsk::crr(Surv(time_90days,status_90days) ~ final_type_of_aki, data = master) %>%
tbl_regression(exp = TRUE) %>% add_n()
| Characteristic |
N |
HR |
95% CI |
p-value |
| final_type_of_aki |
2,062 |
|
|
|
| 1 |
|
— |
— |
|
| 2 |
|
3.02 |
2.43, 3.77 |
<0.001 |
| 3 |
|
3.24 |
2.72, 3.86 |
<0.001 |
| 4 |
|
1.08 |
0.74, 1.58 |
0.7 |
| 5 |
|
2.52 |
1.92, 3.31 |
<0.001 |
tidycmprsk::crr(Surv(time_90days,status_90days) ~ alcoholic_hepatitis_admission, data = master) %>%
tbl_regression(exp = TRUE) %>% add_n()
| Characteristic |
N |
HR |
95% CI |
p-value |
| alcoholic_hepatitis_admission |
2,062 |
1.24 |
1.03, 1.50 |
0.024 |
tidycmprsk::crr(Surv(time_90days,status_90days) ~ aki_stage_4, data = master) %>%
tbl_regression(exp = TRUE) %>% add_n()
## 17 cases omitted due to missing values
| Characteristic |
N |
HR |
95% CI |
p-value |
| aki_stage_4 |
2,045 |
|
|
|
| 1 |
|
— |
— |
|
| 2 |
|
1.58 |
1.26, 1.97 |
<0.001 |
| 3 |
|
2.45 |
2.00, 3.00 |
<0.001 |
| 4 |
|
3.91 |
3.18, 4.80 |
<0.001 |
Multivariate
#age, sex, MELD Na and alc hep
tidycmprsk::crr(Surv(time_90days,status_90days) ~age_admission+sex+MELD_Na_baseline+ alcoholic_hepatitis_admission, data = master) %>%
tbl_regression(exp = TRUE) %>% add_n()
## 64 cases omitted due to missing values
| Characteristic |
N |
HR |
95% CI |
p-value |
| age_admission |
1,998 |
1.01 |
1.01, 1.02 |
<0.001 |
| sex |
1,998 |
|
|
|
| 1 |
|
— |
— |
|
| 2 |
|
1.07 |
0.92, 1.24 |
0.4 |
| MELD_Na_baseline |
1,998 |
1.07 |
1.06, 1.08 |
<0.001 |
| alcoholic_hepatitis_admission |
1,998 |
1.00 |
0.81, 1.24 |
>0.9 |
#age, sex, ACLF stage and alc hep
tidycmprsk::crr(Surv(time_90days,status_90days) ~age_admission+sex+aclf_grade+ alcoholic_hepatitis_admission, data = master) %>%
tbl_regression(exp = TRUE) %>% add_n()
## 1 cases omitted due to missing values
| Characteristic |
N |
HR |
95% CI |
p-value |
| age_admission |
2,061 |
1.01 |
1.00, 1.02 |
0.002 |
| sex |
2,061 |
|
|
|
| 1 |
|
— |
— |
|
| 2 |
|
1.08 |
0.93, 1.25 |
0.3 |
| aclf_grade |
2,061 |
|
|
|
| 1 |
|
— |
— |
|
| 2 |
|
1.82 |
1.31, 2.53 |
<0.001 |
| 3 |
|
4.79 |
3.54, 6.49 |
<0.001 |
| alcoholic_hepatitis_admission |
2,061 |
1.11 |
0.90, 1.36 |
0.3 |
#age, sex, CLIF-C ACLF and alc hep
tidycmprsk::crr(Surv(time_90days,status_90days) ~age_admission+sex+ clif_score + alcoholic_hepatitis_admission, data = master) %>%
tbl_regression(exp = TRUE) %>% add_n()
## 1 cases omitted due to missing values
| Characteristic |
N |
HR |
95% CI |
p-value |
| age_admission |
2,061 |
1.02 |
1.01, 1.02 |
<0.001 |
| sex |
2,061 |
|
|
|
| 1 |
|
— |
— |
|
| 2 |
|
1.06 |
0.91, 1.23 |
0.4 |
| clif_score |
2,061 |
1.36 |
1.32, 1.40 |
<0.001 |
| alcoholic_hepatitis_admission |
2,061 |
1.01 |
0.81, 1.24 |
>0.9 |
#age, sex, MELD Na, AKI phenotype and alc hep
tidycmprsk::crr(Surv(time_90days,status_90days) ~age_admission+sex+ final_type_of_aki +MELD_Na_baseline+ alcoholic_hepatitis_admission, data = master) %>%
tbl_regression(exp = TRUE) %>% add_n()
## 64 cases omitted due to missing values
| Characteristic |
N |
HR |
95% CI |
p-value |
| age_admission |
1,998 |
1.01 |
1.01, 1.02 |
<0.001 |
| sex |
1,998 |
|
|
|
| 1 |
|
— |
— |
|
| 2 |
|
1.02 |
0.88, 1.19 |
0.8 |
| final_type_of_aki |
1,998 |
|
|
|
| 1 |
|
— |
— |
|
| 2 |
|
2.24 |
1.77, 2.83 |
<0.001 |
| 3 |
|
2.77 |
2.31, 3.32 |
<0.001 |
| 4 |
|
1.15 |
0.79, 1.67 |
0.5 |
| 5 |
|
2.36 |
1.79, 3.10 |
<0.001 |
| MELD_Na_baseline |
1,998 |
1.05 |
1.04, 1.06 |
<0.001 |
| alcoholic_hepatitis_admission |
1,998 |
0.97 |
0.78, 1.20 |
0.8 |
# MELD Na and alc hep
tidycmprsk::crr(Surv(time_90days,status_90days) ~MELD_Na_baseline + alcoholic_hepatitis_admission, data = master) %>%
tbl_regression(exp = TRUE) %>% add_n()
## 63 cases omitted due to missing values
| Characteristic |
N |
HR |
95% CI |
p-value |
| MELD_Na_baseline |
1,999 |
1.06 |
1.05, 1.07 |
<0.001 |
| alcoholic_hepatitis_admission |
1,999 |
0.88 |
0.72, 1.08 |
0.2 |
#age, sex, MELD Na and alc hep with interaction
final_type_of_aki*alcoholic_hepatitis_admission
#age, sex, MELD Na, AKI phenotype and alc hep
tidycmprsk::crr(Surv(time_90days,status_90days) ~age_admission+sex+ final_type_of_aki*alcoholic_hepatitis_admission +MELD_Na_baseline, data = master) %>%
tbl_regression(exp = TRUE) %>% add_n() %>%
add_global_p()
## 64 cases omitted due to missing values
| Characteristic |
N |
HR |
95% CI |
p-value |
| age_admission |
1,998 |
1.01 |
1.01, 1.02 |
<0.001 |
| sex |
1,998 |
|
|
0.8 |
| 1 |
|
— |
— |
|
| 2 |
|
1.02 |
0.88, 1.19 |
|
| final_type_of_aki |
1,998 |
|
|
<0.001 |
| 1 |
|
— |
— |
|
| 2 |
|
2.08 |
1.60, 2.70 |
|
| 3 |
|
2.94 |
2.41, 3.58 |
|
| 4 |
|
1.11 |
0.74, 1.66 |
|
| 5 |
|
2.44 |
1.83, 3.26 |
|
| alcoholic_hepatitis_admission |
1,998 |
1.08 |
0.73, 1.60 |
0.7 |
| MELD_Na_baseline |
1,998 |
1.05 |
1.04, 1.06 |
<0.001 |
| final_type_of_aki * alcoholic_hepatitis_admission |
1,998 |
|
|
0.065 |
| 2 * alcoholic_hepatitis_admission |
|
1.46 |
0.83, 2.56 |
|
| 3 * alcoholic_hepatitis_admission |
|
0.71 |
0.44, 1.16 |
|
| 4 * alcoholic_hepatitis_admission |
|
1.44 |
0.49, 4.27 |
|
| 5 * alcoholic_hepatitis_admission |
|
0.77 |
0.33, 1.80 |
|
#age, sex, MELD Na and alc hep with interaction
aki_stage_4i*alcoholic_hepatitis_admission
#age, sex, MELD Na, AKI phenotype and alc hep
tidycmprsk::crr(Surv(time_90days,status_90days) ~age_admission+sex+ aki_stage_4*alcoholic_hepatitis_admission +MELD_Na_baseline, data = master) %>%
tbl_regression(exp = TRUE) %>% add_n() %>%
add_global_p()
## 80 cases omitted due to missing values
| Characteristic |
N |
HR |
95% CI |
p-value |
| age_admission |
1,982 |
1.02 |
1.01, 1.02 |
<0.001 |
| sex |
1,982 |
|
|
0.9 |
| 1 |
|
— |
— |
|
| 2 |
|
0.99 |
0.85, 1.15 |
|
| aki_stage_4 |
1,982 |
|
|
<0.001 |
| 1 |
|
— |
— |
|
| 2 |
|
1.48 |
1.17, 1.89 |
|
| 3 |
|
2.04 |
1.61, 2.59 |
|
| 4 |
|
2.97 |
2.31, 3.82 |
|
| alcoholic_hepatitis_admission |
1,982 |
1.25 |
0.74, 2.13 |
0.4 |
| MELD_Na_baseline |
1,982 |
1.05 |
1.04, 1.06 |
<0.001 |
| aki_stage_4 * alcoholic_hepatitis_admission |
1,982 |
|
|
0.8 |
| 2 * alcoholic_hepatitis_admission |
|
0.77 |
0.38, 1.55 |
|
| 3 * alcoholic_hepatitis_admission |
|
0.73 |
0.39, 1.36 |
|
| 4 * alcoholic_hepatitis_admission |
|
0.81 |
0.43, 1.50 |
|
#create meld score quantiles multivariate model
master <- master %>% mutate(meld_na_4 = cut(MELD_Na_baseline,breaks = quantile(MELD_Na_baseline, probs = c(0, 0.25, 0.5, 0.75, 1), na.rm = TRUE), labels = c("Q1", "Q2", "Q3", "Q4"), include.lowest = TRUE))
master$meld_na_4 <- as.factor(master$meld_na_4)
tidycmprsk::crr(Surv(time_90days,status_90days) ~age_admission+sex+ aki_stage_4+alcoholic_hepatitis_admission +meld_na_4, data = master) %>%
tbl_regression(exp = TRUE) %>% add_n()
## 80 cases omitted due to missing values
| Characteristic |
N |
HR |
95% CI |
p-value |
| age_admission |
1,982 |
1.02 |
1.01, 1.02 |
<0.001 |
| sex |
1,982 |
|
|
|
| 1 |
|
— |
— |
|
| 2 |
|
0.96 |
0.82, 1.12 |
0.6 |
| aki_stage_4 |
1,982 |
|
|
|
| 1 |
|
— |
— |
|
| 2 |
|
1.45 |
1.15, 1.81 |
0.002 |
| 3 |
|
1.97 |
1.58, 2.46 |
<0.001 |
| 4 |
|
3.13 |
2.49, 3.95 |
<0.001 |
| alcoholic_hepatitis_admission |
1,982 |
1.06 |
0.86, 1.32 |
0.6 |
| meld_na_4 |
1,982 |
|
|
|
| Q1 |
|
— |
— |
|
| Q2 |
|
1.54 |
1.22, 1.94 |
<0.001 |
| Q3 |
|
2.20 |
1.73, 2.81 |
<0.001 |
| Q4 |
|
2.52 |
1.95, 3.25 |
<0.001 |
tidycmprsk::crr(Surv(time_90days,status_90days) ~age_admission+sex+ final_type_of_aki+alcoholic_hepatitis_admission +meld_na_4, data = master) %>%
tbl_regression(exp = TRUE) %>% add_n()
## 64 cases omitted due to missing values
| Characteristic |
N |
HR |
95% CI |
p-value |
| age_admission |
1,998 |
1.01 |
1.01, 1.02 |
<0.001 |
| sex |
1,998 |
|
|
|
| 1 |
|
— |
— |
|
| 2 |
|
0.99 |
0.85, 1.15 |
0.9 |
| final_type_of_aki |
1,998 |
|
|
|
| 1 |
|
— |
— |
|
| 2 |
|
2.29 |
1.81, 2.89 |
<0.001 |
| 3 |
|
2.86 |
2.39, 3.42 |
<0.001 |
| 4 |
|
1.13 |
0.77, 1.64 |
0.5 |
| 5 |
|
2.39 |
1.81, 3.14 |
<0.001 |
| alcoholic_hepatitis_admission |
1,998 |
1.04 |
0.84, 1.28 |
0.8 |
| meld_na_4 |
1,998 |
|
|
|
| Q1 |
|
— |
— |
|
| Q2 |
|
1.68 |
1.34, 2.12 |
<0.001 |
| Q3 |
|
2.38 |
1.87, 3.02 |
<0.001 |
| Q4 |
|
3.02 |
2.36, 3.86 |
<0.001 |
#AH vs no AH and 90 day alive vs dead
master_rrt <- master %>% filter(rrt==1)
master_rrt$alcoholic_hepatitis_admission <- factor(master_rrt$alcoholic_hepatitis_admission,
levels = c(0, 1),
labels = c("No", "Yes"))
# Create a new factor variable with custom labels for death_in_90days_status
labels_death <- c("Alive", "Dead") # Custom labels
master_rrt$death_in_90days_status <- factor(master_rrt$death_in_90days_status,
levels = c(0, 1),
labels = c("Alive", "Dead"))
table <- table(master_rrt$alcoholic_hepatitis_admission,master_rrt$death_in_90days_status)
table
##
## Alive Dead
## No 124 176
## Yes 26 47
chisq.test(table)
##
## Pearson's Chi-squared test with Yates' continuity correction
##
## data: table
## X-squared = 0.57806, df = 1, p-value = 0.4471
#cumulative incidence curve for death,competing risk LT in subgroup
of patient with AH, comparing ATN vs HRS vs pre renal, with
corresponding % death 95%CI at 30, 60 and 90d.
master_ah <- master %>% filter(alcoholic_hepatitis_admission==1,final_type_of_aki %in% c(1,2,3))
master_ah$final_type_of_aki <- factor(master_ah$final_type_of_aki)
levels(master_ah$final_type_of_aki) <- c("Prerenal","HRS","ATN")
master_ah$status_90days <- factor(master_ah$status_90days)
master_ah <- master_ah %>% rename(Group=final_type_of_aki)
str(master_ah$status_90days)
## Factor w/ 3 levels "0","1","2": 1 2 1 2 1 1 1 1 1 1 ...
tidycmprsk::cuminc(Surv(time_90days,status_90days) ~ Group , data = master_ah) %>%
ggcuminc() +
add_confidence_interval() +
add_risktable()+
scale_x_continuous(breaks = seq(0, 90, by = 30), limits = c(0, 90))+
theme(panel.background = element_rect(fill = "white", color = NA),
plot.background = element_rect(fill = "white", color = NA),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank())
## Plotting outcome "1".
Cumulative incidence at 30 60 90 days by group
tidycmprsk::cuminc(Surv(time_90days,status_90days) ~ Group , data = master_ah) %>%
tbl_cuminc(
times = c(30,60,90),
label_header = "**{time}-month cuminc**") %>%
add_p() %>% add_n(location = "level")
| Characteristic |
N |
30-month cuminc |
60-month cuminc |
90-month cuminc |
p-value |
| Group |
|
|
|
|
<0.001 |
| Prerenal |
111 |
13% (7.5%, 20%) |
23% (15%, 31%) |
27% (19%, 36%) |
|
| HRS |
42 |
47% (29%, 62%) |
75% (54%, 87%) |
78% (58%, 89%) |
|
| ATN |
119 |
43% (33%, 52%) |
50% (40%, 59%) |
53% (43%, 62%) |
|
1. Additional MVA
tidycmprsk::crr(Surv(time_90days,status_90days) ~age_admission+sex+tb_admit+inr_admit+creatinine_admission+na_admit+alcoholic_hepatitis_admission, data = master) %>%
tbl_regression(exp = TRUE) %>% add_n()
## 64 cases omitted due to missing values
| Characteristic |
N |
HR |
95% CI |
p-value |
| age_admission |
1,998 |
1.01 |
1.01, 1.02 |
<0.001 |
| sex |
1,998 |
|
|
|
| 1 |
|
— |
— |
|
| 2 |
|
1.07 |
0.92, 1.25 |
0.4 |
| tb_admit |
1,998 |
1.04 |
1.03, 1.05 |
<0.001 |
| inr_admit |
1,998 |
1.16 |
1.09, 1.25 |
<0.001 |
| creatinine_admission |
1,998 |
1.04 |
0.99, 1.09 |
0.11 |
| na_admit |
1,998 |
1.00 |
0.99, 1.01 |
0.4 |
| alcoholic_hepatitis_admission |
1,998 |
0.87 |
0.69, 1.09 |
0.2 |
interaction MVA
tidycmprsk::crr(Surv(time_90days,status_90days) ~alcoholic_hepatitis_admission*tb_admit +age_admission+sex+inr_admit+creatinine_admission+na_admit, data = master) %>%
tbl_regression(exp = TRUE) %>% add_n()
## 64 cases omitted due to missing values
| Characteristic |
N |
HR |
95% CI |
p-value |
| alcoholic_hepatitis_admission |
1,998 |
0.97 |
0.70, 1.34 |
0.9 |
| tb_admit |
1,998 |
1.04 |
1.03, 1.05 |
<0.001 |
| age_admission |
1,998 |
1.01 |
1.01, 1.02 |
<0.001 |
| sex |
1,998 |
|
|
|
| 1 |
|
— |
— |
|
| 2 |
|
1.07 |
0.92, 1.25 |
0.4 |
| inr_admit |
1,998 |
1.16 |
1.09, 1.24 |
<0.001 |
| creatinine_admission |
1,998 |
1.04 |
0.99, 1.09 |
0.10 |
| na_admit |
1,998 |
1.00 |
0.99, 1.01 |
0.4 |
| alcoholic_hepatitis_admission * tb_admit |
1,998 |
0.99 |
0.98, 1.01 |
0.4 |
2. APASL ACLF
master <- master %>% mutate(ACLF=case_when(tb_admit>=5 & inr_admit>=1.5 & ( ascites_admission==1 |encephalopathy_admission ==1) ~ 1,
TRUE ~ 0))
gmodels::CrossTable(master$alcoholic_hepatitis_admission,master$ACLF, prop.chisq=F,chisq = T,prop.r=F, prop.c=F,
prop.t=F)
##
##
## Cell Contents
## |-------------------------|
## | N |
## |-------------------------|
##
##
## Total Observations in Table: 2062
##
##
## | master$ACLF
## master$alcoholic_hepatitis_admission | 0 | 1 | Row Total |
## -------------------------------------|-----------|-----------|-----------|
## 0 | 1388 | 371 | 1759 |
## -------------------------------------|-----------|-----------|-----------|
## 1 | 119 | 184 | 303 |
## -------------------------------------|-----------|-----------|-----------|
## Column Total | 1507 | 555 | 2062 |
## -------------------------------------|-----------|-----------|-----------|
##
##
## Statistics for All Table Factors
##
##
## Pearson's Chi-squared test
## ------------------------------------------------------------
## Chi^2 = 206.4137 d.f. = 1 p = 8.323706e-47
##
## Pearson's Chi-squared test with Yates' continuity correction
## ------------------------------------------------------------
## Chi^2 = 204.4038 d.f. = 1 p = 2.284941e-46
##
##
CKD
# CKD-EPI Creatinine Equation (2021)
# sex 1: male 2: female
ckd_epi_gfr <- function(creat, sex, age) {
k <- ifelse(sex == 1, 0.9, 0.7)
a <- ifelse(sex == 1, -0.302, -0.241)
m <- ifelse(sex == 1, 1, 1.012)
gfr <- 142 * min(c(creat/k,1))^a * max(c(creat/k,1))^-1.2 * 0.9938^age * m
return(gfr)
}
# creat new variables
master$eGFR <- mapply(ckd_epi_gfr , master$creatinine_last_available,master$sex,master$age_admission)
master_ckd <- master %>% filter(ckd==1)
master_ckd <-master_ckd %>% mutate(eGFR_cat =case_when(eGFR<15 ~ "<15",
eGFR>=15 & eGFR < 30 ~ "15-29",
eGFR>=30 & eGFR < 45 ~ "30-44",
eGFR>=45 & eGFR < 60~ "45-59"))
gmodels::CrossTable(master_ckd$alcoholic_hepatitis_admission,master_ckd$eGFR_cat, prop.chisq=F,chisq = T,prop.r=F, prop.c=F,
prop.t=F)
##
##
## Cell Contents
## |-------------------------|
## | N |
## |-------------------------|
##
##
## Total Observations in Table: 491
##
##
## | master_ckd$eGFR_cat
## master_ckd$alcoholic_hepatitis_admission | <15 | 15-29 | 30-44 | 45-59 | Row Total |
## -----------------------------------------|-----------|-----------|-----------|-----------|-----------|
## 0 | 86 | 145 | 129 | 100 | 460 |
## -----------------------------------------|-----------|-----------|-----------|-----------|-----------|
## 1 | 7 | 10 | 9 | 5 | 31 |
## -----------------------------------------|-----------|-----------|-----------|-----------|-----------|
## Column Total | 93 | 155 | 138 | 105 | 491 |
## -----------------------------------------|-----------|-----------|-----------|-----------|-----------|
##
##
## Statistics for All Table Factors
##
##
## Pearson's Chi-squared test
## ------------------------------------------------------------
## Chi^2 = 0.6739554 d.f. = 3 p = 0.8793121
##
##
##
excluding ckd
master_exclduing_ckd <- master %>% filter(ckd!=1)
#create table one for expourse response#
T1 <- CreateTableOne(vars = all_var,strata ="alcoholic_hepatitis_admission" ,includeNA = F,addOverall = TRUE,data = master_exclduing_ckd, factorVars = cat_var)
## Warning in ModuleReturnVarsExist(vars, data): The data frame does not have:
## days_icu days_discharge_to_transplant Dropped
#print table one
T1_print <- print(T1,exact = c("kidney_transplant","Alcoholic_hepatitis","HCC"), nonnormal=num_var,showAllLevels = F,missing = T,quote = FALSE, noSpaces = TRUE, printToggle = FALSE)
#save
write.csv(T1_print, file = "C:\\Users\\to909\\Desktop\\Projects\\alcoholic_hepatitis_admission\\Table_1_excluding_ckd .csv")
Cumulative incidence at 30 60 90 days by group
tidycmprsk::cuminc(Surv(time_90days,status_90days) ~ alcoholic_hepatitis_admission , data = master_exclduing_ckd) %>%
tbl_cuminc(
times = c(30,60,90),
label_header = "**{time}-month cuminc**") %>%
add_p() %>% add_n(location = "level")
| Characteristic |
N |
30-month cuminc |
60-month cuminc |
90-month cuminc |
p-value |
| alcoholic_hepatitis_admission |
|
|
|
|
0.2 |
| 0 |
1,178 |
29% (27%, 32%) |
37% (34%, 40%) |
41% (38%, 44%) |
|
| 1 |
256 |
33% (27%, 39%) |
43% (36%, 49%) |
46% (40%, 53%) |
|
excluding ckd Cumulative incidence curve for death, with LT as a
competing event
tidycmprsk::cuminc(Surv(time_90days,status_90days) ~ alcoholic_hepatitis_admission , data = master_exclduing_ckd) %>%
ggcuminc(linetype_aes = T) +
add_confidence_interval() +
add_risktable()+
scale_x_continuous(breaks = seq(0, 90, by = 30), limits = c(0, 90))+
theme(panel.background = element_rect(fill = "white", color = NA),
plot.background = element_rect(fill = "white", color = NA),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank())
## Plotting outcome "1".
# excluding ckd 90 days morality, with LT as a competing event
tidycmprsk::crr(Surv(time_90days,status_90days) ~age_admission+sex+MELD_Na_baseline+ alcoholic_hepatitis_admission, data = master_exclduing_ckd) %>%
tbl_regression(exp = TRUE) %>% add_n()
## 31 cases omitted due to missing values
| Characteristic |
N |
HR |
95% CI |
p-value |
| age_admission |
1,403 |
1.02 |
1.01, 1.02 |
<0.001 |
| sex |
1,403 |
|
|
|
| 1 |
|
— |
— |
|
| 2 |
|
1.10 |
0.93, 1.31 |
0.3 |
| MELD_Na_baseline |
1,403 |
1.06 |
1.05, 1.08 |
<0.001 |
| alcoholic_hepatitis_admission |
1,403 |
0.99 |
0.79, 1.24 |
>0.9 |
#4. Acute kidney disease (AKD) and de novo CKD as outcomes
master <- master %>% mutate(de_novo_ckd=case_when(
ckd==1 ~ "Pre-exisiting CKD",
ckd!=1 & eGFR<60 ~ "De-novo CKD",
ckd!=1 & eGFR>=60 ~ "no CKD at 90 days",
is.na(creatinine_last_available) | days_liver<90 ~ "no GFR at 90 days available"
))
denovo_cohort <- master %>% filter(death_in_90days_status==0,liver_transplant ==0,ckd==0) %>% mutate(denovo_ckd=ifelse(eGFR<60,"De-novo CKD","No CKD")) %>% filter(!is.na(denovo_ckd))
gmodels::CrossTable(denovo_cohort$alcoholic_hepatitis_admission,denovo_cohort$denovo_ckd, prop.chisq=F,chisq = T,prop.r=F, prop.c=F,
prop.t=F)
##
##
## Cell Contents
## |-------------------------|
## | N |
## |-------------------------|
##
##
## Total Observations in Table: 157
##
##
## | denovo_cohort$denovo_ckd
## denovo_cohort$alcoholic_hepatitis_admission | De-novo CKD | No CKD | Row Total |
## --------------------------------------------|-------------|-------------|-------------|
## 0 | 50 | 83 | 133 |
## --------------------------------------------|-------------|-------------|-------------|
## 1 | 8 | 16 | 24 |
## --------------------------------------------|-------------|-------------|-------------|
## Column Total | 58 | 99 | 157 |
## --------------------------------------------|-------------|-------------|-------------|
##
##
## Statistics for All Table Factors
##
##
## Pearson's Chi-squared test
## ------------------------------------------------------------
## Chi^2 = 0.1584351 d.f. = 1 p = 0.6906014
##
## Pearson's Chi-squared test with Yates' continuity correction
## ------------------------------------------------------------
## Chi^2 = 0.02832104 d.f. = 1 p = 0.8663563
##
##
gmodels::CrossTable(denovo_cohort$rrt,denovo_cohort$denovo_ckd, prop.chisq=F,chisq = T,prop.r=F, prop.c=F,
prop.t=F)
## Warning in chisq.test(t, correct = TRUE, ...): Chi-squared approximation may be
## incorrect
## Warning in chisq.test(t, correct = FALSE, ...): Chi-squared approximation may
## be incorrect
##
##
## Cell Contents
## |-------------------------|
## | N |
## |-------------------------|
##
##
## Total Observations in Table: 157
##
##
## | denovo_cohort$denovo_ckd
## denovo_cohort$rrt | De-novo CKD | No CKD | Row Total |
## ------------------|-------------|-------------|-------------|
## 0 | 53 | 94 | 147 |
## ------------------|-------------|-------------|-------------|
## 1 | 5 | 5 | 10 |
## ------------------|-------------|-------------|-------------|
## Column Total | 58 | 99 | 157 |
## ------------------|-------------|-------------|-------------|
##
##
## Statistics for All Table Factors
##
##
## Pearson's Chi-squared test
## ------------------------------------------------------------
## Chi^2 = 0.7816761 d.f. = 1 p = 0.376629
##
## Pearson's Chi-squared test with Yates' continuity correction
## ------------------------------------------------------------
## Chi^2 = 0.2976461 d.f. = 1 p = 0.5853619
##
##