Count Patients with Marked Laboratory Abnormalities
Source:R/abnormal_by_marked.R
abnormal_by_marked.Rd
Primary analysis variable .var
indicates whether single, replicated or last marked laboratory
abnormality was observed (factor
). Additional analysis variables are id
(character
or factor
)
and direction
(factor
) indicating the direction of the abnormality. Denominator is number of
patients with at least one valid measurement during the analysis.
For
Single, not last
andLast or replicated
: Numerator is number of patients withSingle, not last
andLast or replicated
levels, respectively.For
Any
: Numerator is the number of patients with either single or replicated marked abnormalities.
Usage
s_count_abnormal_by_marked(
df,
.var = "AVALCAT1",
.spl_context,
category = list(single = "SINGLE", last_replicated = c("LAST", "REPLICATED")),
variables = list(id = "USUBJID", param = "PARAM", direction = "abn_dir")
)
a_count_abnormal_by_marked(
df,
.var = "AVALCAT1",
.spl_context,
category = list(single = "SINGLE", last_replicated = c("LAST", "REPLICATED")),
variables = list(id = "USUBJID", param = "PARAM", direction = "abn_dir")
)
count_abnormal_by_marked(
lyt,
var,
...,
.stats = NULL,
.formats = NULL,
.labels = NULL,
.indent_mods = NULL
)
Arguments
- df
(
data.frame
)
data set containing all analysis variables.- .var, var
(
string
)
single variable name that is passed byrtables
when requested by a statistics function.- .spl_context
(
data.frame
)
gives information about ancestor split states that is passed byrtables
.- category
(
list
)
with different marked category names for single and last or replicated.- variables
(named
list
ofstring
)
list of additional analysis variables.- lyt
(
layout
)
input layout where analyses will be added to.- ...
additional arguments for the lower level functions.
- .stats
(
character
)
statistics to select for the table.- .formats
(named
character
orlist
)
formats for the statistics.- .labels
(named
character
)
labels for the statistics (without indent).- .indent_mods
(named
integer
)
indent modifiers for the labels.
Value
s_count_abnormal_by_marked()
returns statisticcount_fraction
withSingle, not last
,Last or replicated
, andAny
results.
a_count_abnormal_by_marked()
returns the corresponding list with formattedrtables::CellValue()
.
count_abnormal_by_marked()
returns a layout object suitable for passing to further layouting functions, or tortables::build_table()
. Adding this function to anrtable
layout will add formatted rows containing the statistics froms_count_abnormal_by_marked()
to the table layout.
Functions
s_count_abnormal_by_marked()
: Statistics function for patients with marked lab abnormalities.a_count_abnormal_by_marked()
: Formatted analysis function which is used asafun
incount_abnormal_by_marked()
.count_abnormal_by_marked()
: Layout-creating function which can take statistics function arguments and additional format arguments. This function is a wrapper forrtables::analyze()
.
Note
Single, not last
and Last or replicated
levels are mutually exclusive. If a patient has
abnormalities that meet both the Single, not last
and Last or replicated
criteria, then the
patient will be counted only under the Last or replicated
category.
Examples
library(dplyr)
df <- data.frame(
USUBJID = as.character(c(rep(1, 5), rep(2, 5), rep(1, 5), rep(2, 5))),
ARMCD = factor(c(rep("ARM A", 5), rep("ARM B", 5), rep("ARM A", 5), rep("ARM B", 5))),
ANRIND = factor(c(
"NORMAL", "HIGH", "HIGH", "HIGH HIGH", "HIGH",
"HIGH", "HIGH", "HIGH HIGH", "NORMAL", "HIGH HIGH", "NORMAL", "LOW", "LOW", "LOW LOW", "LOW",
"LOW", "LOW", "LOW LOW", "NORMAL", "LOW LOW"
)),
ONTRTFL = rep(c("", "Y", "Y", "Y", "Y", "Y", "Y", "Y", "Y", "Y"), 2),
PARAMCD = factor(c(rep("CRP", 10), rep("ALT", 10))),
AVALCAT1 = factor(rep(c("", "", "", "SINGLE", "REPLICATED", "", "", "LAST", "", "SINGLE"), 2)),
stringsAsFactors = FALSE
)
df <- df %>%
mutate(abn_dir = factor(
case_when(
ANRIND == "LOW LOW" ~ "Low",
ANRIND == "HIGH HIGH" ~ "High",
TRUE ~ ""
),
levels = c("Low", "High")
))
# Select only post-baseline records.
df <- df %>% filter(ONTRTFL == "Y")
df_crp <- df %>%
filter(PARAMCD == "CRP") %>%
droplevels()
full_parent_df <- list(df_crp, "not_needed")
cur_col_subset <- list(rep(TRUE, nrow(df_crp)), "not_needed")
spl_context <- data.frame(
split = c("PARAMCD", "GRADE_DIR"),
full_parent_df = I(full_parent_df),
cur_col_subset = I(cur_col_subset)
)
# Internal function - s_count_abnormal_by_marked
if (FALSE) {
s_count_abnormal_by_marked(
df = df_crp %>% filter(abn_dir == "High"),
.spl_context = spl_context,
.var = "AVALCAT1",
variables = list(id = "USUBJID", param = "PARAMCD", direction = "abn_dir")
)
}
# Internal function - a_count_abnormal_by_marked
if (FALSE) {
# Use the Formatted Analysis function for `analyze()`. We need to ungroup `count_fraction` first
# so that the `rtables` formatting function `format_count_fraction()` can be applied correctly.
afun <- make_afun(a_count_abnormal_by_marked, .ungroup_stats = "count_fraction")
afun(
df = df_crp %>% filter(abn_dir == "High"),
.spl_context = spl_context,
variables = list(id = "USUBJID", param = "PARAMCD", direction = "abn_dir")
)
}
map <- unique(
df[df$abn_dir %in% c("Low", "High") & df$AVALCAT1 != "", c("PARAMCD", "abn_dir")]
) %>%
lapply(as.character) %>%
as.data.frame() %>%
arrange(PARAMCD, abn_dir)
basic_table() %>%
split_cols_by("ARMCD") %>%
split_rows_by("PARAMCD") %>%
summarize_num_patients(
var = "USUBJID",
.stats = "unique_count"
) %>%
split_rows_by(
"abn_dir",
split_fun = trim_levels_to_map(map)
) %>%
count_abnormal_by_marked(
var = "AVALCAT1",
variables = list(
id = "USUBJID",
param = "PARAMCD",
direction = "abn_dir"
)
) %>%
build_table(df = df)
#> ARM A ARM B
#> ————————————————————————————————————————————
#> ALT (n) 1 1
#> Low
#> Single, not last 1 (100%) 0
#> Last or replicated 0 1 (100%)
#> Any Abnormality 1 (100%) 1 (100%)
#> CRP (n) 1 1
#> High
#> Single, not last 1 (100%) 0
#> Last or replicated 0 1 (100%)
#> Any Abnormality 1 (100%) 1 (100%)
basic_table() %>%
split_cols_by("ARMCD") %>%
split_rows_by("PARAMCD") %>%
summarize_num_patients(
var = "USUBJID",
.stats = "unique_count"
) %>%
split_rows_by(
"abn_dir",
split_fun = trim_levels_in_group("abn_dir")
) %>%
count_abnormal_by_marked(
var = "AVALCAT1",
variables = list(
id = "USUBJID",
param = "PARAMCD",
direction = "abn_dir"
)
) %>%
build_table(df = df)
#> ARM A ARM B
#> ————————————————————————————————————————————
#> ALT (n) 1 1
#> Low
#> Single, not last 1 (100%) 0
#> Last or replicated 0 1 (100%)
#> Any Abnormality 1 (100%) 1 (100%)
#> CRP (n) 1 1
#> High
#> Single, not last 1 (100%) 0
#> Last or replicated 0 1 (100%)
#> Any Abnormality 1 (100%) 1 (100%)