Count patients with toxicity grades that have worsened from baseline by highest grade post-baseline
Source:R/abnormal_lab_worsen_by_baseline.R
abnormal_lab_worsen_by_baseline.Rd![[Stable]](figures/lifecycle-stable.svg)
The analyze function count_abnormal_lab_worsen_by_baseline() creates a layout element to count patients with
analysis toxicity grades which have worsened from baseline, categorized by highest (worst) grade post-baseline.
This function analyzes primary analysis variable var which indicates analysis toxicity grades. Additional
analysis variables that can be supplied as a list via the variables parameter are id (defaults to USUBJID),
a variable to indicate unique subject identifiers, baseline_var (defaults to BTOXGR), a variable to indicate
baseline toxicity grades, and direction_var (defaults to GRADDIR), a variable to indicate toxicity grade
directions of interest to include (e.g. "H" (high), "L" (low), or "B" (both)).
For the direction(s) specified in direction_var, patient counts by worst grade for patients who have
worsened from baseline are calculated as follows:
1to4: The number of patients who have worsened from their baseline grades with worst grades 1-4, respectively.Any: The total number of patients who have worsened from their baseline grades.
Fractions are calculated by dividing the above counts by the number of patients who's analysis toxicity grades have worsened from baseline toxicity grades during treatment.
Prior to using this function in your table layout you must use rtables::split_rows_by() to create a row
split on variable direction_var.
count_abnormal_lab_worsen_by_baseline(
lyt,
var,
variables = list(id = "USUBJID", baseline_var = "BTOXGR", direction_var = "GRADDR"),
na_str = default_na_str(),
nested = TRUE,
...,
table_names = lifecycle::deprecated(),
.stats = "fraction",
.stat_names = NULL,
.formats = list(fraction = format_fraction),
.labels = NULL,
.indent_mods = NULL
)
s_count_abnormal_lab_worsen_by_baseline(
df,
.var = "ATOXGR",
variables = list(id = "USUBJID", baseline_var = "BTOXGR", direction_var = "GRADDR"),
...
)
a_count_abnormal_lab_worsen_by_baseline(
df,
...,
.stats = NULL,
.stat_names = NULL,
.formats = NULL,
.labels = NULL,
.indent_mods = NULL
)Arguments
- lyt
(
PreDataTableLayouts)
layout that analyses will be added to.- variables
(named
listofstring)
list of additional analysis variables including:id(string)
subject variable name.baseline_var(string)
name of the data column containing baseline toxicity variable.direction_var(string)
seedirection_varfor more details.
- na_str
(
string)
string used to replace allNAor empty values in the output.- nested
(
flag)
whether this layout instruction should be applied within the existing layout structure _if possible (TRUE, the default) or as a new top-level element (FALSE). Ignored if it would nest a split. underneath analyses, which is not allowed.- ...
additional arguments for the lower level functions.
- table_names
![[Deprecated]](figures/lifecycle-deprecated.svg)
this parameter has no effect.Options are:
'fraction'- .stats
(
character)
statistics to select for the table.- .stat_names
(
character)
names of the statistics that are passed directly to name single statistics (.stats). This option is visible when producingrtables::as_result_df()withmake_ard = TRUE.- .formats
(named
characterorlist)
formats for the statistics. See Details inanalyze_varsfor more information on the"auto"setting.- .labels
(named
character)
labels for the statistics (without indent).- .indent_mods
(named
integer)
indent modifiers for the labels. Defaults to 0, which corresponds to the unmodified default behavior. Can be negative.- df
(
data.frame)
data set containing all analysis variables.- .var, var
(
string)
single variable name that is passed byrtableswhen requested by a statistics function.
Value
count_abnormal_lab_worsen_by_baseline()returns a layout object suitable for passing to further layouting functions, or tortables::build_table(). Adding this function to anrtablelayout will add formatted rows containing the statistics froms_count_abnormal_lab_worsen_by_baseline()to the table layout.
s_count_abnormal_lab_worsen_by_baseline()returns the counts and fraction of patients whose worst post-baseline lab grades are worse than their baseline grades, for post-baseline worst grades "1", "2", "3", "4" and "Any".
a_count_abnormal_lab_worsen_by_baseline()returns the corresponding list with formattedrtables::CellValue().
Functions
count_abnormal_lab_worsen_by_baseline(): Layout-creating function which can take statistics function arguments and additional format arguments. This function is a wrapper forrtables::analyze().s_count_abnormal_lab_worsen_by_baseline(): Statistics function for patients whose worst post-baseline lab grades are worse than their baseline grades.a_count_abnormal_lab_worsen_by_baseline(): Formatted analysis function which is used asafunincount_abnormal_lab_worsen_by_baseline().
See also
Relevant helper functions h_adlb_worsen() and h_worsen_counter() which are used within
s_count_abnormal_lab_worsen_by_baseline() to process input data.
Examples
library(dplyr)
# The direction variable, GRADDR, is based on metadata
adlb <- tern_ex_adlb %>%
mutate(
GRADDR = case_when(
PARAMCD == "ALT" ~ "B",
PARAMCD == "CRP" ~ "L",
PARAMCD == "IGA" ~ "H"
)
) %>%
filter(SAFFL == "Y" & ONTRTFL == "Y" & GRADDR != "")
df <- h_adlb_worsen(
adlb,
worst_flag_low = c("WGRLOFL" = "Y"),
worst_flag_high = c("WGRHIFL" = "Y"),
direction_var = "GRADDR"
)
basic_table() %>%
split_cols_by("ARMCD") %>%
add_colcounts() %>%
split_rows_by("PARAMCD") %>%
split_rows_by("GRADDR") %>%
count_abnormal_lab_worsen_by_baseline(
var = "ATOXGR",
variables = list(
id = "USUBJID",
baseline_var = "BTOXGR",
direction_var = "GRADDR"
)
) %>%
append_topleft("Direction of Abnormality") %>%
build_table(df = df, alt_counts_df = tern_ex_adsl)
#> ARM A ARM B ARM C
#> Direction of Abnormality (N=69) (N=73) (N=58)
#> ————————————————————————————————————————————————————————————————————————
#> IGA
#> High
#> 1 6/63 (9.5%) 6/64 (9.4%) 4/50 (8%)
#> 2 8/64 (12.5%) 5/67 (7.5%) 8/53 (15.1%)
#> 3 7/66 (10.6%) 5/68 (7.4%) 9/57 (15.8%)
#> 4 6/68 (8.8%) 2/72 (2.8%) 3/58 (5.2%)
#> Any 27/68 (39.7%) 18/72 (25%) 24/58 (41.4%)
#> ALT
#> High
#> 1 7/63 (11.1%) 6/62 (9.7%) 2/48 (4.2%)
#> 2 12/63 (19%) 4/67 (6%) 11/50 (22%)
#> 3 4/65 (6.2%) 11/71 (15.5%) 7/56 (12.5%)
#> 4 1/67 (1.5%) 8/71 (11.3%) 4/57 (7%)
#> Any 24/67 (35.8%) 29/71 (40.8%) 24/57 (42.1%)
#> Low
#> 1 12/67 (17.9%) 4/66 (6.1%) 7/52 (13.5%)
#> 2 9/68 (13.2%) 12/69 (17.4%) 6/55 (10.9%)
#> 3 6/69 (8.7%) 4/71 (5.6%) 5/56 (8.9%)
#> 4 7/69 (10.1%) 7/73 (9.6%) 6/58 (10.3%)
#> Any 34/69 (49.3%) 27/73 (37%) 24/58 (41.4%)
#> CRP
#> Low
#> 1 11/66 (16.7%) 10/67 (14.9%) 4/47 (8.5%)
#> 2 8/66 (12.1%) 1/70 (1.4%) 6/50 (12%)
#> 3 4/68 (5.9%) 9/70 (12.9%) 5/53 (9.4%)
#> 4 7/69 (10.1%) 6/72 (8.3%) 4/55 (7.3%)
#> Any 30/69 (43.5%) 26/72 (36.1%) 19/55 (34.5%)