Cox regression with simple additive model
wrapper_cox_regression_core_simple.RdThis function can be used if one is interested in effects of multiple covariates in a multivariate model.
Usage
wrapper_cox_regression_core_simple(
data,
tte_var,
censor_var,
covariate_vars,
strata_vars = NULL,
return_vars = NULL,
keep_obs = TRUE,
variable_names = NULL,
caption = NULL,
force_empty_cols = FALSE,
sr_times = NULL,
print_nevent = TRUE,
print_mst = TRUE,
print_total = TRUE,
print_pvalues = TRUE,
print_adjpvalues = TRUE,
print_hr = TRUE,
print_sr_cis = FALSE
)
wrapper_cox_regression_core_simple_strat(
data,
tte_var,
censor_var,
covariate_vars,
strata_vars = NULL,
return_vars = NULL,
strat1_var = NULL,
strat2_var = NULL,
variable_names = NULL,
caption = NULL,
force_empty_cols = FALSE,
sr_times = NULL,
print_nevent = TRUE,
print_mst = TRUE,
print_total = TRUE,
print_pvalues = TRUE,
print_adjpvalues = TRUE,
print_hr = TRUE,
print_sr_cis = FALSE
)Arguments
- data
Data frame.
- tte_var
Name of the time-to-event variable. This variable must be numeric.
- censor_var
Name of the censor variable. It has to be numeric and encode 1 for event and 0 for censor.
- covariate_vars
Vector with names of covariates that are included in the formula of the simple additive model: `~ covariate_vars[1] + covariate_vars[2] + covariate_vars[3] + ....`
- strata_vars
Vector with names of covariates that are used as strata.
- return_vars
Vector with names of covariates for which the statistics should be returned. If NULL, statistics are returned for all covariates.
- variable_names
Named vector with variable names. If not supplied, variable names are created by replacing in column names underscores with spaces.
- caption
Caption for the table with results.
- force_empty_cols
Logical. Whether to display output columns which are all empty.
- sr_times
Vector of times used to compute survival rates, for example, percent of 3-year IDSF.
- print_nevent
Logical. Whether to print numbers of events.
- print_mst
Logical. Whether to print median survival time (MST).
- print_total
Logical. Whether to print total number of samples and total number of events.
- print_pvalues
Logical. Whether to print p-values.
- print_adjpvalues
Logical. Whether to print adjusted p-values.
- strat1_var
Name of the first stratification variable used for splitting the data.
- strat2_var
Name of the second stratification variable used for splitting the data.
Details
If for a factor covariate that should be returned the reference level has zero count, results are set to NAs because this levels is not used as a reference which means that it is not possible to fit the model that we want.
Examples
data(bdata)
data <- bdata
tte_var <- "PFS"
censor_var <- "PFS_Event"
covariate_vars <- c("Treatment_Arm", "GeneA", "IPI", "Cell_Of_Origin")
x <- wrapper_cox_regression_core_simple(data, tte_var = tte_var, censor_var = censor_var, covariate_vars = covariate_vars)
#> Warning: row names were found from a short variable and have been discarded
#> Warning: row names were found from a short variable and have been discarded
#> Warning: row names were found from a short variable and have been discarded
boutput(x)
#> Covariate Subgroup Total N Total Events N Events MST
#> 1 Treatment Arm CTRL 391 165 200 85 (42.5%) 83.0
#> 2 TRT 391 165 191 80 (41.9%) 100.3
#> 3 GeneA 391 165
#> 4 IPI Low 391 165 78 25 (32.1%) NA
#> 5 Low-Intermediate 391 165 144 51 (35.4%) 92.0
#> 6 High-Intermediate 391 165 103 49 (47.6%) 83.1
#> 7 High 391 165 66 40 (60.6%) 63.6
#> 8 Cell Of Origin GCB 391 165 218 80 (36.7%) NA
#> 9 UNCLASSIFIED 391 165 62 34 (54.8%) 80.4
#> 10 ABC 391 165 111 51 (45.9%) 84.5
#> MST 95% CI HR HR 95% CI P-value Adj. P-value
#> 1 (80.3 - NA)
#> 2 (84.6 - NA) 0.73 (0.53 - 0.99) 0.0444 * 0.0777 .
#> 3 1.03 (0.89 - 1.20) 0.6919 0.6919
#> 4 (99.9 - NA)
#> 5 (84.5 - NA) 1.17 (0.72 - 1.91) 0.5157 0.6017
#> 6 (63.4 - NA) 1.79 (1.10 - 2.93) 0.0202 * 0.0500 *
#> 7 (27.3 - 82.2) 2.70 (1.62 - 4.51) 0.0001 *** 0.0010 ***
#> 8 (87.1 - NA)
#> 9 (57.6 - 88.7) 1.62 (1.07 - 2.44) 0.0214 * 0.0500 *
#> 10 (74.7 - NA) 1.23 (0.86 - 1.75) 0.2659 0.3723
bforest(x)
### Fit a stratified model
covariate_vars <- c("Treatment_Arm", "GeneA")
strata_vars <- c("IPI", "Cell_Of_Origin")
x <- wrapper_cox_regression_core_simple(data, tte_var = tte_var, censor_var = censor_var, covariate_vars = covariate_vars, strata_vars = strata_vars)
#> Warning: row names were found from a short variable and have been discarded
boutput(x)
#> Covariate Subgroup Total N Total Events N Events MST MST 95% CI
#> 1 Treatment Arm CTRL 391 165 200 85 (42.5%) 83.0 (80.3 - NA)
#> 2 TRT 391 165 191 80 (41.9%) 100.3 (84.6 - NA)
#> 3 GeneA 391 165
#> HR HR 95% CI P-value Adj. P-value
#> 1
#> 2 0.74 (0.54 - 1.01) 0.0555 . 0.1110
#> 3 0.99 (0.85 - 1.16) 0.9334 0.9334
data(bdata)
data <- bdata
tte_var <- "PFS"
censor_var <- "PFS_Event"
covariate_vars <- c("IPI", "GeneA")
strat1_var = "Cell_Of_Origin"
strat2_var = "Treatment_Arm"
x <- wrapper_cox_regression_core_simple_strat(data, tte_var = tte_var, censor_var = censor_var, covariate_vars = covariate_vars, strat1_var = strat1_var, strat2_var = strat2_var)
#> Warning: row names were found from a short variable and have been discarded
#> Warning: row names were found from a short variable and have been discarded
#> Warning: row names were found from a short variable and have been discarded
#> Warning: row names were found from a short variable and have been discarded
#> Warning: row names were found from a short variable and have been discarded
#> Warning: row names were found from a short variable and have been discarded
boutput(x)
#> Treatment Arm Cell Of Origin Covariate Subgroup Total N
#> 1 CTRL GCB IPI Low 121
#> 2 Low-Intermediate 121
#> 3 High-Intermediate 121
#> 4 High 121
#> 5 CTRL GCB GeneA 121
#> 6 CTRL UNCLASSIFIED IPI Low 28
#> 7 Low-Intermediate 28
#> 8 High-Intermediate 28
#> 9 High 28
#> 10 CTRL UNCLASSIFIED GeneA 28
#> 11 CTRL ABC IPI Low 51
#> 12 Low-Intermediate 51
#> 13 High-Intermediate 51
#> 14 High 51
#> 15 CTRL ABC GeneA 51
#> 16 TRT GCB IPI Low 97
#> 17 Low-Intermediate 97
#> 18 High-Intermediate 97
#> 19 High 97
#> 20 TRT GCB GeneA 97
#> 21 TRT UNCLASSIFIED IPI Low 34
#> 22 Low-Intermediate 34
#> 23 High-Intermediate 34
#> 24 High 34
#> 25 TRT UNCLASSIFIED GeneA 34
#> 26 TRT ABC IPI Low 60
#> 27 Low-Intermediate 60
#> 28 High-Intermediate 60
#> 29 High 60
#> 30 TRT ABC GeneA 60
#> Total Events N Events MST MST 95% CI HR HR 95% CI P-value
#> 1 50 32 12 (37.5%) NA (76.9 - NA)
#> 2 50 44 14 (31.8%) NA (78.3 - NA) 0.97 (0.45 - 2.11) 0.9439
#> 3 50 32 17 (53.1%) 65.7 (36.5 - NA) 2.22 (1.05 - 4.70) 0.0374 *
#> 4 50 13 7 (53.8%) 98.3 (19.6 - NA) 1.89 (0.74 - 4.82) 0.1860
#> 5 50 0.99 (0.73 - 1.34) 0.9417
#> 6 14 7 3 (42.9%) NA (32.1 - NA)
#> 7 14 10 6 (60.0%) 80.4 (15.1 - NA) 1.65 (0.37 - 7.43) 0.5120
#> 8 14 7 3 (42.9%) NA (1.6 - NA) 1.29 (0.25 - 6.61) 0.7592
#> 9 14 4 2 (50.0%) 28.8 (13.7 - NA) 1.74 (0.28 - 10.74) 0.5528
#> 10 14 0.93 (0.59 - 1.45) 0.7359
#> 11 21 5 2 (40.0%) NA (4.0 - NA)
#> 12 21 17 3 (17.6%) NA (83.0 - NA) 0.23 (0.03 - 1.53) 0.1271
#> 13 21 18 9 (50.0%) 82.6 (33.3 - NA) 0.91 (0.18 - 4.62) 0.9130
#> 14 21 11 7 (63.6%) 23.4 (9.9 - NA) 2.91 (0.59 - 14.20) 0.1874
#> 15 21 1.68 (1.01 - 2.79) 0.0463 *
#> 16 30 23 3 (13.0%) NA NA
#> 17 30 36 9 (25.0%) NA (91.0 - NA) 2.19 (0.59 - 8.13) 0.2396
#> 18 30 20 7 (35.0%) 100.3 (72.4 - NA) 3.06 (0.79 - 11.86) 0.1065
#> 19 30 18 11 (61.1%) 75.5 (27.3 - NA) 6.13 (1.70 - 22.09) 0.0055 **
#> 20 30 1.08 (0.71 - 1.64) 0.7348
#> 21 20 5 1 (20.0%) NA (31.9 - NA)
#> 22 20 14 8 (57.1%) 82.1 (31.2 - NA) 3.53 (0.44 - 28.27) 0.2346
#> 23 20 10 6 (60.0%) 72.7 (48.8 - NA) 4.07 (0.49 - 34.00) 0.1954
#> 24 20 5 5 (100.0%) 21.9 (8.9 - NA) 10.54 (1.07 - 103.38) 0.0433 *
#> 25 20 1.02 (0.67 - 1.54) 0.9268
#> 26 30 6 4 (66.7%) 76.1 (33.6 - NA)
#> 27 30 23 11 (47.8%) 84.5 (74.7 - NA) 0.70 (0.22 - 2.20) 0.5411
#> 28 30 16 7 (43.8%) NA (40.7 - NA) 0.63 (0.18 - 2.15) 0.4583
#> 29 30 15 8 (53.3%) 67.6 (15.9 - NA) 1.03 (0.31 - 3.42) 0.9676
#> 30 30 0.81 (0.53 - 1.25) 0.3499
#> Adj. P-value
#> 1
#> 2 0.9676
#> 3 0.2777
#> 4 0.5209
#> 5 0.9676
#> 6
#> 7 0.8292
#> 8 0.9590
#> 9 0.8292
#> 10 0.9590
#> 11
#> 12 0.5085
#> 13 0.9676
#> 14 0.5209
#> 15 0.2777
#> 16
#> 17 0.5229
#> 18 0.5085
#> 19 0.1328
#> 20 0.9590
#> 21
#> 22 0.5229
#> 23 0.5209
#> 24 0.2777
#> 25 0.9676
#> 26
#> 27 0.8292
#> 28 0.8292
#> 29 0.9676
#> 30 0.6999