Josh sarcopenia
2025-12-03
creat any_2
creat any_3
add varaibles
ggplot(final_master, aes(x = z_score, y = cr_cys)) +
geom_point(size = 2, alpha = 0.7) +
geom_smooth(method = "lm", se = TRUE, color = "blue", linewidth = 1) +
labs(
x = "Z Score",
y = "Creatinine/Cystatin C",
title = " Z Score and Creatinine/Cystatin C"
) +
theme_bw(base_size = 14) +
theme(
plot.title = element_text(hjust = 0.5),
panel.grid = element_blank()
)## `geom_smooth()` using formula = 'y ~ x'
final_master_sarcopenia cmp_time_any_3
final_master_sarcopenia$cmp_status_any_3 <- as.factor(final_master_sarcopenia$cmp_status_any_3)
tidycmprsk::crr(Surv(cmp_time_any_3,cmp_status_any_3) ~ cr_cys_7 + age + sex + cancer_stage + ecog_score_2 + cockcroft,failcode=1,cencode=0, data = final_master_sarcopenia) %>% tbl_regression(exp = TRUE) %>% add_n()| Characteristic | N | HR1 | 95% CI1 | p-value |
|---|---|---|---|---|
| cr_cys_7 | 87 | |||
| None | — | — | ||
| 30% | 3.32 | 1.24, 8.88 | 0.017 | |
| age | 87 | 1.01 | 0.95, 1.06 | 0.8 |
| sex | 87 | |||
| 1 | — | — | ||
| 2 | 0.72 | 0.20, 2.50 | 0.6 | |
| cancer_stage | 87 | |||
| 1 | — | — | ||
| 2 | 5.38 | 0.52, 56.0 | 0.2 | |
| ecog_score_2 | 87 | |||
| >=1 | — | — | ||
| 1 | 0.50 | 0.13, 1.99 | 0.3 | |
| cockcroft | 87 | 1.00 | 0.98, 1.02 | >0.9 |
| 1 HR = Hazard Ratio, CI = Confidence Interval | ||||
final_master_no_sarcopenia cmp_time_any_3
final_master_no_sarcopenia$cmp_status_any_3 <- as.factor(final_master_no_sarcopenia$cmp_status_any_3)
tidycmprsk::crr(Surv(cmp_time_any_3,cmp_status_any_3) ~ cr_cys_7 + age + sex + cancer_stage + ecog_score_2 + cockcroft,failcode=1,cencode=0, data = final_master_no_sarcopenia) %>% tbl_regression(exp = TRUE) %>% add_n()| Characteristic | N | HR1 | 95% CI1 | p-value |
|---|---|---|---|---|
| cr_cys_7 | 371 | |||
| None | — | — | ||
| 30% | 2.34 | 1.33, 4.10 | 0.003 | |
| age | 371 | 0.99 | 0.97, 1.02 | 0.6 |
| sex | 371 | |||
| 1 | — | — | ||
| 2 | 0.84 | 0.49, 1.45 | 0.5 | |
| cancer_stage | 371 | |||
| 1 | — | — | ||
| 2 | 1.16 | 0.65, 2.06 | 0.6 | |
| ecog_score_2 | 371 | |||
| >=1 | — | — | ||
| 1 | 1.13 | 0.69, 1.84 | 0.6 | |
| cockcroft | 371 | 1.00 | 0.99, 1.01 | 0.9 |
| 1 HR = Hazard Ratio, CI = Confidence Interval | ||||
final_master_sarcopenia cmp_time_hosp
final_master_sarcopenia$cmp_status_hosp <- as.factor(final_master_sarcopenia$cmp_status_hosp)
tidycmprsk::crr(Surv(cmp_time_hosp,cmp_status_hosp) ~ cr_cys_7 + age + sex + cancer_stage + ecog_score_2 + cockcroft,failcode=1,cencode=0, data = final_master_sarcopenia) %>% tbl_regression(exp = TRUE) %>% add_n()| Characteristic | N | HR1 | 95% CI1 | p-value |
|---|---|---|---|---|
| cr_cys_7 | 87 | |||
| None | — | — | ||
| 30% | 1.68 | 0.80, 3.53 | 0.2 | |
| age | 87 | 0.99 | 0.95, 1.03 | 0.6 |
| sex | 87 | |||
| 1 | — | — | ||
| 2 | 0.90 | 0.35, 2.33 | 0.8 | |
| cancer_stage | 87 | |||
| 1 | — | — | ||
| 2 | 4.00 | 1.11, 14.3 | 0.034 | |
| ecog_score_2 | 87 | |||
| >=1 | — | — | ||
| 1 | 1.21 | 0.51, 2.89 | 0.7 | |
| cockcroft | 87 | 1.01 | 1.00, 1.02 | 0.13 |
| 1 HR = Hazard Ratio, CI = Confidence Interval | ||||
final_master_no_sarcopenia cmp_time_hosp
final_master_no_sarcopenia$cmp_status_hosp <- as.factor(final_master_no_sarcopenia$cmp_status_hosp)
tidycmprsk::crr(Surv(cmp_time_hosp,cmp_status_hosp) ~ cr_cys_7 + age + sex + cancer_stage + ecog_score_2 + cockcroft,failcode=1,cencode=0, data = final_master_no_sarcopenia) %>% tbl_regression(exp = TRUE) %>% add_n()| Characteristic | N | HR1 | 95% CI1 | p-value |
|---|---|---|---|---|
| cr_cys_7 | 371 | |||
| None | — | — | ||
| 30% | 1.46 | 0.94, 2.28 | 0.10 | |
| age | 371 | 1.00 | 0.98, 1.02 | >0.9 |
| sex | 371 | |||
| 1 | — | — | ||
| 2 | 0.95 | 0.61, 1.48 | 0.8 | |
| cancer_stage | 371 | |||
| 1 | — | — | ||
| 2 | 1.65 | 1.03, 2.63 | 0.036 | |
| ecog_score_2 | 371 | |||
| >=1 | — | — | ||
| 1 | 0.97 | 0.66, 1.42 | 0.9 | |
| cockcroft | 371 | 1.00 | 1.00, 1.01 | 0.2 |
| 1 HR = Hazard Ratio, CI = Confidence Interval | ||||
final_master_sarcopenia cmp_time_side_effect
final_master_sarcopenia$cmp_status_side_effect <- as.factor(final_master_sarcopenia$cmp_status_side_effect)
tidycmprsk::crr(Surv(cmp_time_side_effect,cmp_status_side_effect) ~ cr_cys_7 + age + sex + cancer_stage + ecog_score_2 + cockcroft,failcode=1,cencode=0, data = final_master_sarcopenia) %>% tbl_regression(exp = TRUE) %>% add_n()| Characteristic | N | HR1 | 95% CI1 | p-value |
|---|---|---|---|---|
| cr_cys_7 | 87 | |||
| None | — | — | ||
| 30% | 2.08 | 0.87, 4.96 | 0.10 | |
| age | 87 | 1.00 | 0.96, 1.04 | 0.9 |
| sex | 87 | |||
| 1 | — | — | ||
| 2 | 0.78 | 0.27, 2.26 | 0.7 | |
| cancer_stage | 87 | |||
| 1 | — | — | ||
| 2 | 2.78 | 0.77, 10.0 | 0.12 | |
| ecog_score_2 | 87 | |||
| >=1 | — | — | ||
| 1 | 1.02 | 0.37, 2.77 | >0.9 | |
| cockcroft | 87 | 1.00 | 0.99, 1.02 | 0.6 |
| 1 HR = Hazard Ratio, CI = Confidence Interval | ||||
final_master_no_sarcopenia cmp_time_side_effect
final_master_no_sarcopenia$cmp_status_side_effect <- as.factor(final_master_no_sarcopenia$cmp_status_side_effect)
tidycmprsk::crr(Surv(cmp_time_side_effect,cmp_status_side_effect) ~ cr_cys_7 + age + sex + cancer_stage + ecog_score_2 + cockcroft,failcode=1,cencode=0, data = final_master_no_sarcopenia) %>% tbl_regression(exp = TRUE) %>% add_n()| Characteristic | N | HR1 | 95% CI1 | p-value |
|---|---|---|---|---|
| cr_cys_7 | 371 | |||
| None | — | — | ||
| 30% | 2.33 | 1.25, 4.34 | 0.008 | |
| age | 371 | 0.99 | 0.96, 1.01 | 0.3 |
| sex | 371 | |||
| 1 | — | — | ||
| 2 | 0.58 | 0.31, 1.08 | 0.086 | |
| cancer_stage | 371 | |||
| 1 | — | — | ||
| 2 | 1.16 | 0.63, 2.13 | 0.6 | |
| ecog_score_2 | 371 | |||
| >=1 | — | — | ||
| 1 | 0.78 | 0.46, 1.33 | 0.4 | |
| cockcroft | 371 | 0.99 | 0.98, 1.00 | 0.3 |
| 1 HR = Hazard Ratio, CI = Confidence Interval | ||||
death coxph final_master_sarcopenia
table(final_master_sarcopenia$death_90,final_master_sarcopenia$cancer_stage)##
## 1 2
## 0 19 59
## 1 0 9coxph(Surv(time_to_death_90,death_90) ~ cr_cys_7 + age + sex + ecog_score_2 + cockcroft, data = final_master_sarcopenia)%>% tbl_regression(exp = TRUE)%>% add_n()| Characteristic | N | HR1 | 95% CI1 | p-value |
|---|---|---|---|---|
| cr_cys_7 | 87 | |||
| None | — | — | ||
| 30% | 3.90 | 0.90, 17.0 | 0.069 | |
| age | 87 | 0.99 | 0.90, 1.09 | 0.8 |
| sex | 87 | |||
| 1 | — | — | ||
| 2 | 0.37 | 0.04, 3.24 | 0.4 | |
| ecog_score_2 | 87 | |||
| >=1 | — | — | ||
| 1 | 0.35 | 0.04, 3.10 | 0.3 | |
| cockcroft | 87 | 0.99 | 0.96, 1.02 | 0.4 |
| 1 HR = Hazard Ratio, CI = Confidence Interval | ||||
death coxph final_master_no_sarcopenia
coxph(Surv(time_to_death_90,death_90) ~ cr_cys_7 + age + sex + ecog_score_2 + cockcroft, data = final_master_no_sarcopenia)%>% tbl_regression(exp = TRUE)%>% add_n()| Characteristic | N | HR1 | 95% CI1 | p-value |
|---|---|---|---|---|
| cr_cys_7 | 371 | |||
| None | — | — | ||
| 30% | 7.04 | 1.72, 28.8 | 0.007 | |
| age | 371 | 1.01 | 0.95, 1.09 | 0.7 |
| sex | 371 | |||
| 1 | — | — | ||
| 2 | 0.57 | 0.17, 1.90 | 0.4 | |
| ecog_score_2 | 371 | |||
| >=1 | — | — | ||
| 1 | 0.37 | 0.08, 1.75 | 0.2 | |
| cockcroft | 371 | 1.01 | 1.00, 1.03 | 0.14 |
| 1 HR = Hazard Ratio, CI = Confidence Interval | ||||
new cr_cys_7
new cr_cys_7 color
any_3 final_master_sarcopenia
plot_adj_cif_cr_cys_7(
data = final_master_sarcopenia,
time = cmp_time_any_3,
status = cmp_status_any_3,
title = "any_3 final_master_sarcopenia"
)
any_3 final_master_no_sarcopenia
plot_adj_cif_cr_cys_7_color(
data = final_master_no_sarcopenia,
time = cmp_time_any_3,
status = cmp_status_any_3,
title = "any_3 final_master_no_sarcopenia"
)
side_effect final_master_sarcopenia
plot_adj_cif_cr_cys_7(
data = final_master_sarcopenia,
time = cmp_time_side_effect, # Pass as a quoted string
status = cmp_status_side_effect,
title = "side_effect final_master_sarcopenia"
)
side_effect final_master_no_sarcopenia
plot_adj_cif_cr_cys_7_color(
data = final_master_no_sarcopenia,
time = cmp_time_side_effect, # Pass as a quoted string
status = cmp_status_side_effect,
title = "side_effect final_master_no_sarcopenia"
)
hosp final_master_sarcopenia
plot_adj_cif_cr_cys_7(
data = final_master_sarcopenia,
time = cmp_time_hosp, # Pass as a quoted string
status = cmp_status_hosp,
title = "hosp final_master_sarcopenia"
)
hosp final_master_no_sarcopenia
plot_adj_cif_cr_cys_7_color(
data = final_master_no_sarcopenia,
time = cmp_time_hosp, # Pass as a quoted string
status = cmp_status_hosp,
title = "hosp final_master_no_sarcopenia"
)
#1-KM final_master_sarcopenia 365
#1-KM final_master_sarcopenia 90
#1-KM final_master_no_sarcopenia 365
#1-KM final_master_no_sarcopenia 90
new cys_c_egfr_ge_60
new cys_c_egfr_ge_60 color
any_3 final_master_sarcopenia
plot_adj_cif_cys_c_egfr_ge_60(
data = final_master_sarcopenia,
time = cmp_time_any_3,
status = cmp_status_any_3,
title = "any_3 final_master_sarcopenia"
)
any_3 final_master_no_sarcopenia
plot_adj_cif_cys_c_egfr_ge_60_color(
data = final_master_no_sarcopenia,
time = cmp_time_any_3,
status = cmp_status_any_3,
title = "any_3 final_master_no_sarcopenia"
)
side_effect final_master_sarcopenia
plot_adj_cif_cys_c_egfr_ge_60(
data = final_master_sarcopenia,
time = cmp_time_side_effect, # Pass as a quoted string
status = cmp_status_side_effect,
title = "side_effect final_master_sarcopenia"
)
side_effect final_master_no_sarcopenia
plot_adj_cif_cys_c_egfr_ge_60_color(
data = final_master_no_sarcopenia,
time = cmp_time_side_effect, # Pass as a quoted string
status = cmp_status_side_effect,
title = "side_effect final_master_no_sarcopenia"
)
hosp final_master_sarcopenia
plot_adj_cif_cys_c_egfr_ge_60(
data = final_master_sarcopenia,
time = cmp_time_hosp, # Pass as a quoted string
status = cmp_status_hosp,
title = "hosp final_master_sarcopenia"
)
hosp final_master_no_sarcopenia
plot_adj_cif_cys_c_egfr_ge_60_color(
data = final_master_no_sarcopenia,
time = cmp_time_hosp, # Pass as a quoted string
status = cmp_status_hosp,
title = "hosp final_master_no_sarcopenia"
)
#1-KM final_master_sarcopenia 365
#1-KM final_master_sarcopenia 90
#1-KM final_master_no_sarcopenia 365
#1-KM final_master_no_sarcopenia 90
#1 Grade 3 z score
#2 Death z score
#3 platinum_related_hos
#4 Overall Hospitalization
#Table one ## for cre/cys ratio
##dose_1: carbo-AUC ≥ 5 mg/mL/min, or r cisplatin ≥ 75 mg/m2
table_one <- final_master%>%
dplyr::select(age,age_cat,sex,race,ethnicity,cancer_stage,
ici,Bevacizumab,Paclitaxel,Pemetrexed,Doxorubicin,Etoposide,Gemcitabine,Pertuzumab,Trastuzumab,Docetaxel,Fluorouracil,Methotrexate,Vinblastine,Administered_alone,
dm,htn,cirrhosis,cad,hiv,ppi,ace_arb,diu,steroids,statins,nsaids,smoking,thyroid,
ECOG_Score,ecog_score_2,bmi,bmi_cat,pre_HGB_45days,pre_PLT_45days,pre_ALB_45days,baseline_cystatin_c,baseline_cre,cockcroft,baseline_cre_egfr,baseline_cys_c_egfr,cr_cys_7,sarcopenia)
all_vars <- names(table_one)
num_vars <- c(
"age","bmi","pre_HGB_45days","pre_PLT_45days","pre_ALB_45days",
"baseline_cystatin_c","baseline_cre","cockcroft",
"baseline_cre_egfr","baseline_cys_c_egfr"
)
cat_vars <- setdiff(names(table_one),num_vars)
table_one <- table_one %>% mutate_at(cat_vars,as.factor)
# T1 <- tableone::CreateTableOne(
# vars = all_vars,
# strata = "sarcopenia", # variable to stratify by
# data = table_one,
# factorVars = cat_vars, # specify which variables are factors
# addOverall = TRUE,
# includeNA = FALSE
# )
#
t1 <- table_one %>%
tbl_summary(
by = sarcopenia,
statistic = list(
all_continuous() ~ "{mean} ({sd})",
all_categorical() ~ "{n} ({p}%)"
),
digits = all_continuous() ~ 1,
missing = "ifany"
) %>%
add_overall() %>%
bold_labels()
t1| Characteristic | Overall N = 4581 |
0 N = 3711 |
1 N = 871 |
|---|---|---|---|
| age | 65.2 (12.1) | 63.9 (12.4) | 71.0 (8.4) |
| age_cat | |||
| 1 | 194 (42%) | 175 (47%) | 19 (22%) |
| 2 | 228 (50%) | 172 (46%) | 56 (64%) |
| 3 | 36 (7.9%) | 24 (6.5%) | 12 (14%) |
| sex | |||
| 1 | 197 (43%) | 132 (36%) | 65 (75%) |
| 2 | 261 (57%) | 239 (64%) | 22 (25%) |
| race | |||
| 1 | 370 (81%) | 300 (81%) | 70 (80%) |
| 2 | 18 (3.9%) | 15 (4.0%) | 3 (3.4%) |
| 3 | 18 (3.9%) | 11 (3.0%) | 7 (8.0%) |
| 4 | 16 (3.5%) | 15 (4.0%) | 1 (1.1%) |
| 5 | 36 (7.9%) | 30 (8.1%) | 6 (6.9%) |
| ethnicity | |||
| 1 | 387 (84%) | 306 (82%) | 81 (93%) |
| 2 | 39 (8.5%) | 37 (10.0%) | 2 (2.3%) |
| 3 | 32 (7.0%) | 28 (7.5%) | 4 (4.6%) |
| cancer_stage | |||
| 1 | 128 (28%) | 109 (29%) | 19 (22%) |
| 2 | 330 (72%) | 262 (71%) | 68 (78%) |
| ici | |||
| 0 | 351 (77%) | 298 (80%) | 53 (61%) |
| 1 | 107 (23%) | 73 (20%) | 34 (39%) |
| Bevacizumab | |||
| 0 | 443 (97%) | 356 (96%) | 87 (100%) |
| 1 | 15 (3.3%) | 15 (4.0%) | 0 (0%) |
| Paclitaxel | |||
| 0 | 283 (62%) | 224 (60%) | 59 (68%) |
| 1 | 175 (38%) | 147 (40%) | 28 (32%) |
| Pemetrexed | |||
| 0 | 351 (77%) | 288 (78%) | 63 (72%) |
| 1 | 107 (23%) | 83 (22%) | 24 (28%) |
| Doxorubicin | |||
| 0 | 447 (98%) | 360 (97%) | 87 (100%) |
| 1 | 11 (2.4%) | 11 (3.0%) | 0 (0%) |
| Etoposide | |||
| 0 | 413 (90%) | 333 (90%) | 80 (92%) |
| 1 | 45 (9.8%) | 38 (10%) | 7 (8.0%) |
| Gemcitabine | |||
| 0 | 398 (87%) | 334 (90%) | 64 (74%) |
| 1 | 60 (13%) | 37 (10.0%) | 23 (26%) |
| Pertuzumab | |||
| 0 | 432 (94%) | 345 (93%) | 87 (100%) |
| 1 | 26 (5.7%) | 26 (7.0%) | 0 (0%) |
| Trastuzumab | |||
| 0 | 430 (94%) | 343 (92%) | 87 (100%) |
| 1 | 28 (6.1%) | 28 (7.5%) | 0 (0%) |
| Docetaxel | |||
| 0 | 426 (93%) | 340 (92%) | 86 (99%) |
| 1 | 32 (7.0%) | 31 (8.4%) | 1 (1.1%) |
| Fluorouracil | |||
| 0 | 455 (99%) | 368 (99%) | 87 (100%) |
| 1 | 3 (0.7%) | 3 (0.8%) | 0 (0%) |
| Methotrexate | |||
| 0 | 455 (99%) | 368 (99%) | 87 (100%) |
| 1 | 3 (0.7%) | 3 (0.8%) | 0 (0%) |
| Vinblastine | |||
| 0 | 455 (99%) | 368 (99%) | 87 (100%) |
| 1 | 3 (0.7%) | 3 (0.8%) | 0 (0%) |
| Administered_alone | |||
| 0 | 433 (95%) | 350 (94%) | 83 (95%) |
| 1 | 25 (5.5%) | 21 (5.7%) | 4 (4.6%) |
| dm | |||
| 0 | 378 (83%) | 312 (84%) | 66 (76%) |
| 1 | 80 (17%) | 59 (16%) | 21 (24%) |
| htn | |||
| 0 | 175 (38%) | 154 (42%) | 21 (24%) |
| 1 | 283 (62%) | 217 (58%) | 66 (76%) |
| cirrhosis | |||
| 0 | 436 (95%) | 356 (96%) | 80 (92%) |
| 1 | 22 (4.8%) | 15 (4.0%) | 7 (8.0%) |
| cad | |||
| 0 | 330 (72%) | 279 (75%) | 51 (59%) |
| 1 | 128 (28%) | 92 (25%) | 36 (41%) |
| hiv | |||
| 0 | 434 (95%) | 349 (94%) | 85 (98%) |
| 1 | 24 (5.2%) | 22 (5.9%) | 2 (2.3%) |
| ppi | |||
| 0 | 305 (67%) | 250 (67%) | 55 (63%) |
| 1 | 153 (33%) | 121 (33%) | 32 (37%) |
| ace_arb | |||
| 0 | 342 (75%) | 281 (76%) | 61 (70%) |
| 1 | 116 (25%) | 90 (24%) | 26 (30%) |
| diu | |||
| 0 | 358 (78%) | 292 (79%) | 66 (76%) |
| 1 | 100 (22%) | 79 (21%) | 21 (24%) |
| steroids | |||
| 0 | 21 (4.6%) | 11 (3.0%) | 10 (11%) |
| 1 | 437 (95%) | 360 (97%) | 77 (89%) |
| statins | |||
| 0 | 308 (67%) | 256 (69%) | 52 (60%) |
| 1 | 150 (33%) | 115 (31%) | 35 (40%) |
| nsaids | |||
| 0 | 256 (56%) | 201 (54%) | 55 (63%) |
| 1 | 202 (44%) | 170 (46%) | 32 (37%) |
| smoking | |||
| 0 | 214 (47%) | 184 (50%) | 30 (34%) |
| 1 | 244 (53%) | 187 (50%) | 57 (66%) |
| thyroid | |||
| 0 | 385 (84%) | 312 (84%) | 73 (84%) |
| 1 | 73 (16%) | 59 (16%) | 14 (16%) |
| ECOG_Score | |||
| 0 | 195 (43%) | 162 (44%) | 33 (38%) |
| 1 | 228 (50%) | 182 (49%) | 46 (53%) |
| 2 | 30 (6.6%) | 24 (6.5%) | 6 (6.9%) |
| 3 | 5 (1.1%) | 3 (0.8%) | 2 (2.3%) |
| ecog_score_2 | |||
| >=1 | 263 (57%) | 209 (56%) | 54 (62%) |
| 1 | 195 (43%) | 162 (44%) | 33 (38%) |
| bmi | 27.1 (5.8) | 27.6 (5.8) | 25.0 (5.2) |
| bmi_cat | |||
| 1 | 17 (3.7%) | 10 (2.7%) | 7 (8.0%) |
| 2 | 166 (36%) | 125 (34%) | 41 (47%) |
| 3 | 148 (32%) | 121 (33%) | 27 (31%) |
| 4 | 127 (28%) | 115 (31%) | 12 (14%) |
| pre_HGB_45days | 12.5 (1.6) | 12.5 (1.5) | 12.5 (1.9) |
| Unknown | 1 | 0 | 1 |
| pre_PLT_45days | 289.0 (105.7) | 291.2 (101.5) | 279.2 (122.3) |
| Unknown | 1 | 0 | 1 |
| pre_ALB_45days | 4.1 (0.4) | 4.1 (0.4) | 4.0 (0.4) |
| Unknown | 1 | 0 | 1 |
| baseline_cystatin_c | 1.1 (0.4) | 1.1 (0.4) | 1.2 (0.4) |
| baseline_cre | 0.9 (0.3) | 0.8 (0.2) | 1.0 (0.4) |
| cockcroft | 89.2 (35.3) | 92.0 (36.4) | 77.4 (27.4) |
| baseline_cre_egfr | 86.0 (18.4) | 87.0 (18.4) | 81.7 (18.1) |
| baseline_cys_c_egfr | 71.4 (23.6) | 73.7 (23.7) | 61.7 (20.3) |
| cr_cys_7 | |||
| None | 325 (71%) | 266 (72%) | 59 (68%) |
| 30% | 133 (29%) | 105 (28%) | 28 (32%) |
| 1 Mean (SD); n (%) | |||
final_master_sarcopenia cmp_time_any_3
final_master_sarcopenia$cmp_status_any_3 <- as.factor(final_master_sarcopenia$cmp_status_any_3)
tidycmprsk::crr(Surv(cmp_time_any_3,cmp_status_any_3) ~ cys_c_egfr_ge_60 + age + sex + cancer_stage + ecog_score_2 + cockcroft,failcode=1,cencode=0, data = final_master_sarcopenia) %>% tbl_regression(exp = TRUE) %>% add_n()| Characteristic | N | HR1 | 95% CI1 | p-value |
|---|---|---|---|---|
| cys_c_egfr_ge_60 | 87 | |||
| <60 | — | — | ||
| >=60 | 0.52 | 0.21, 1.25 | 0.14 | |
| age | 87 | 1.01 | 0.95, 1.08 | 0.7 |
| sex | 87 | |||
| 1 | — | — | ||
| 2 | 1.00 | 0.28, 3.53 | >0.9 | |
| cancer_stage | 87 | |||
| 1 | — | — | ||
| 2 | 4.39 | 0.44, 43.5 | 0.2 | |
| ecog_score_2 | 87 | |||
| >=1 | — | — | ||
| 1 | 0.36 | 0.09, 1.42 | 0.14 | |
| cockcroft | 87 | 1.01 | 0.99, 1.03 | 0.3 |
| 1 HR = Hazard Ratio, CI = Confidence Interval | ||||
final_master_no_sarcopenia cmp_time_any_3
final_master_no_sarcopenia$cmp_status_any_3 <- as.factor(final_master_no_sarcopenia$cmp_status_any_3)
tidycmprsk::crr(Surv(cmp_time_any_3,cmp_status_any_3) ~ cys_c_egfr_ge_60 + age + sex + cancer_stage + ecog_score_2 + cockcroft,failcode=1,cencode=0, data = final_master_no_sarcopenia) %>% tbl_regression(exp = TRUE) %>% add_n()| Characteristic | N | HR1 | 95% CI1 | p-value |
|---|---|---|---|---|
| cys_c_egfr_ge_60 | 371 | |||
| <60 | — | — | ||
| >=60 | 0.40 | 0.21, 0.74 | 0.004 | |
| age | 371 | 1.00 | 0.97, 1.02 | 0.7 |
| sex | 371 | |||
| 1 | — | — | ||
| 2 | 1.13 | 0.68, 1.88 | 0.6 | |
| cancer_stage | 371 | |||
| 1 | — | — | ||
| 2 | 1.08 | 0.59, 1.97 | 0.8 | |
| ecog_score_2 | 371 | |||
| >=1 | — | — | ||
| 1 | 1.04 | 0.65, 1.68 | 0.9 | |
| cockcroft | 371 | 1.01 | 1.00, 1.02 | 0.2 |
| 1 HR = Hazard Ratio, CI = Confidence Interval | ||||
final_master_sarcopenia cmp_time_hosp
final_master_sarcopenia$cmp_status_hosp <- as.factor(final_master_sarcopenia$cmp_status_hosp)
tidycmprsk::crr(Surv(cmp_time_hosp,cmp_status_hosp) ~ cys_c_egfr_ge_60 + age + sex + cancer_stage + ecog_score_2 + cockcroft,failcode=1,cencode=0, data = final_master_sarcopenia) %>% tbl_regression(exp = TRUE) %>% add_n()| Characteristic | N | HR1 | 95% CI1 | p-value |
|---|---|---|---|---|
| cys_c_egfr_ge_60 | 87 | |||
| <60 | — | — | ||
| >=60 | 0.56 | 0.23, 1.35 | 0.2 | |
| age | 87 | 0.99 | 0.95, 1.03 | 0.6 |
| sex | 87 | |||
| 1 | — | — | ||
| 2 | 1.19 | 0.43, 3.28 | 0.7 | |
| cancer_stage | 87 | |||
| 1 | — | — | ||
| 2 | 3.65 | 1.04, 12.9 | 0.044 | |
| ecog_score_2 | 87 | |||
| >=1 | — | — | ||
| 1 | 1.06 | 0.48, 2.38 | 0.9 | |
| cockcroft | 87 | 1.02 | 1.00, 1.03 | 0.034 |
| 1 HR = Hazard Ratio, CI = Confidence Interval | ||||
final_master_no_sarcopenia cmp_time_hosp
final_master_no_sarcopenia$cmp_status_hosp <- as.factor(final_master_no_sarcopenia$cmp_status_hosp)
tidycmprsk::crr(Surv(cmp_time_hosp,cmp_status_hosp) ~ cys_c_egfr_ge_60 + age + sex + cancer_stage + ecog_score_2 + cockcroft,failcode=1,cencode=0, data = final_master_no_sarcopenia) %>% tbl_regression(exp = TRUE) %>% add_n()| Characteristic | N | HR1 | 95% CI1 | p-value |
|---|---|---|---|---|
| cys_c_egfr_ge_60 | 371 | |||
| <60 | — | — | ||
| >=60 | 0.96 | 0.58, 1.57 | 0.9 | |
| age | 371 | 1.01 | 0.99, 1.02 | 0.6 |
| sex | 371 | |||
| 1 | — | — | ||
| 2 | 1.07 | 0.72, 1.60 | 0.7 | |
| cancer_stage | 371 | |||
| 1 | — | — | ||
| 2 | 1.73 | 1.06, 2.80 | 0.027 | |
| ecog_score_2 | 371 | |||
| >=1 | — | — | ||
| 1 | 0.92 | 0.63, 1.34 | 0.7 | |
| cockcroft | 371 | 1.01 | 1.00, 1.01 | 0.076 |
| 1 HR = Hazard Ratio, CI = Confidence Interval | ||||
final_master_sarcopenia cmp_time_side_effect
final_master_sarcopenia$cmp_status_side_effect <- as.factor(final_master_sarcopenia$cmp_status_side_effect)
tidycmprsk::crr(Surv(cmp_time_side_effect,cmp_status_side_effect) ~ cys_c_egfr_ge_60 + age + sex + cancer_stage + ecog_score_2 + cockcroft,failcode=1,cencode=0, data = final_master_sarcopenia) %>% tbl_regression(exp = TRUE) %>% add_n()| Characteristic | N | HR1 | 95% CI1 | p-value |
|---|---|---|---|---|
| cys_c_egfr_ge_60 | 87 | |||
| <60 | — | — | ||
| >=60 | 0.42 | 0.15, 1.16 | 0.094 | |
| age | 87 | 1.00 | 0.95, 1.05 | >0.9 |
| sex | 87 | |||
| 1 | — | — | ||
| 2 | 1.17 | 0.39, 3.56 | 0.8 | |
| cancer_stage | 87 | |||
| 1 | — | — | ||
| 2 | 2.51 | 0.72, 8.73 | 0.2 | |
| ecog_score_2 | 87 | |||
| >=1 | — | — | ||
| 1 | 0.88 | 0.36, 2.15 | 0.8 | |
| cockcroft | 87 | 1.02 | 1.00, 1.03 | 0.10 |
| 1 HR = Hazard Ratio, CI = Confidence Interval | ||||
final_master_no_sarcopenia cmp_time_side_effect
final_master_no_sarcopenia$cmp_status_side_effect <- as.factor(final_master_no_sarcopenia$cmp_status_side_effect)
tidycmprsk::crr(Surv(cmp_time_side_effect,cmp_status_side_effect) ~ cys_c_egfr_ge_60 + age + sex + cancer_stage + ecog_score_2 + cockcroft,failcode=1,cencode=0, data = final_master_no_sarcopenia) %>% tbl_regression(exp = TRUE) %>% add_n()| Characteristic | N | HR1 | 95% CI1 | p-value |
|---|---|---|---|---|
| cys_c_egfr_ge_60 | 371 | |||
| <60 | — | — | ||
| >=60 | 0.61 | 0.32, 1.16 | 0.13 | |
| age | 371 | 0.99 | 0.97, 1.02 | 0.5 |
| sex | 371 | |||
| 1 | — | — | ||
| 2 | 0.78 | 0.45, 1.36 | 0.4 | |
| cancer_stage | 371 | |||
| 1 | — | — | ||
| 2 | 1.17 | 0.61, 2.22 | 0.6 | |
| ecog_score_2 | 371 | |||
| >=1 | — | — | ||
| 1 | 0.71 | 0.42, 1.21 | 0.2 | |
| cockcroft | 371 | 1.00 | 0.99, 1.01 | >0.9 |
| 1 HR = Hazard Ratio, CI = Confidence Interval | ||||
death coxph final_master_sarcopenia
table(final_master_sarcopenia$death_90,final_master_sarcopenia$cancer_stage)##
## 1 2
## 0 19 59
## 1 0 9coxph(Surv(time_to_death_90,death_90) ~ cys_c_egfr_ge_60 + age + sex + ecog_score_2 + cockcroft, data = final_master_sarcopenia)%>% tbl_regression(exp = TRUE)%>% add_n()| Characteristic | N | HR1 | 95% CI1 | p-value |
|---|---|---|---|---|
| cys_c_egfr_ge_60 | 87 | |||
| <60 | — | — | ||
| >=60 | 0.66 | 0.14, 3.21 | 0.6 | |
| age | 87 | 1.00 | 0.90, 1.10 | >0.9 |
| sex | 87 | |||
| 1 | — | — | ||
| 2 | 0.47 | 0.05, 4.26 | 0.5 | |
| ecog_score_2 | 87 | |||
| >=1 | — | — | ||
| 1 | 0.23 | 0.03, 1.88 | 0.2 | |
| cockcroft | 87 | 1.0 | 0.96, 1.03 | 0.7 |
| 1 HR = Hazard Ratio, CI = Confidence Interval | ||||
death coxph final_master_no_sarcopenia
coxph(Surv(time_to_death_90,death_90) ~ cys_c_egfr_ge_60 + age + sex + ecog_score_2 + cockcroft, data = final_master_no_sarcopenia)%>% tbl_regression(exp = TRUE)%>% add_n()| Characteristic | N | HR1 | 95% CI1 | p-value |
|---|---|---|---|---|
| cys_c_egfr_ge_60 | 371 | |||
| <60 | — | — | ||
| >=60 | 0.09 | 0.02, 0.40 | 0.001 | |
| age | 371 | 1.02 | 0.96, 1.09 | 0.6 |
| sex | 371 | |||
| 1 | — | — | ||
| 2 | 0.96 | 0.31, 3.00 | >0.9 | |
| ecog_score_2 | 371 | |||
| >=1 | — | — | ||
| 1 | 0.33 | 0.07, 1.53 | 0.2 | |
| cockcroft | 371 | 1.03 | 1.01, 1.04 | <0.001 |
| 1 HR = Hazard Ratio, CI = Confidence Interval | ||||