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Patient Counts for Laboratory Events (Worsen From Baseline) by Highest Grade Post-Baseline

Source: R/abnormal_by_worst_grade_worsen.R
abnormal_by_worst_grade_worsen.Rd

[Stable]

Patient count and fraction for laboratory events (worsen from baseline) shift table.

Usage

h_adlb_worsen(
  adlb,
  worst_flag_low = NULL,
  worst_flag_high = NULL,
  direction_var
)

h_worsen_counter(df, id, .var, baseline_var, direction_var)

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,
  .var = "ATOXGR",
  variables = list(id = "USUBJID", baseline_var = "BTOXGR", direction_var = "GRADDR")
)

count_abnormal_lab_worsen_by_baseline(
  lyt,
  var,
  ...,
  table_names = NULL,
  .stats = NULL,
  .formats = NULL,
  .labels = NULL,
  .indent_mods = NULL
)

Arguments

adlb

(data frame)
ADLB dataframe

worst_flag_low

(named vector)
Worst low post-baseline lab grade flag variable

worst_flag_high

(named vector)
Worst high post-baseline lab grade flag variable

direction_var

(string)
Direction variable specifying the direction of the shift table of interest. Only lab records flagged by L, H or B are included in the shift table.

  • L: low direction only

  • H: high direction only

  • B: both low and high directions

df

(data frame)
data set containing all analysis variables.

id

(string)
subject variable name.

.var, var

(string)
single variable name that is passed by rtables when requested by a statistics function.

baseline_var

(string)
baseline lab grade variable

variables

(named list of string)
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): See direction_var for more detail

lyt

(layout)
input layout where analyses will be added to.

...

additional arguments for the lower level functions.

table_names

(character)
this can be customized in case that the same vars are analyzed multiple times, to avoid warnings from rtables.

.stats

(character)
statistics to select for the table.

.formats

(named character or list)
formats for the statistics.

.labels

(named character)
labels for the statistics (without indent).

.indent_mods

(named integer)
indent modifiers for the labels.

Value

h_adlb_worsen() returns the adlb

data frame containing only the worst labs specified according to worst_flag_low or worst_flag_high for the direction specified according to direction_var. For instance, for a lab that is needed for the low direction only, only records flagged by worst_flag_low are selected. For a lab that is needed for both low and high directions, the worst low records are selected for the low direction, and the worst high record are selected for the high direction.

h_worsen_counter() 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".

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 formatted rtables::CellValue().

Functions

  • h_adlb_worsen(): Helper function to prepare a df for generate the patient count shift table

  • h_worsen_counter(): Helper function to count the number of patients and the fraction of patients according to highest post-baseline lab grade variable .var, baseline lab grade variable baseline_var, and the direction of interest specified in direction_var.

  • s_count_abnormal_lab_worsen_by_baseline(): Statistics function which calculates 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(): Formatted Analysis function which can be further customized by calling rtables::make_afun() on it. It is used as afun in rtables::analyze().

  • count_abnormal_lab_worsen_by_baseline(): Layout creating function which can be used for creating tables, which can take statistics function arguments and additional format arguments (see below).

Examples


library(scda)
library(dplyr)
adlb <- synthetic_cdisc_data("latest")$adlb
adsl <- synthetic_cdisc_data("latest")$adsl

# The direction variable, GRADDR, is based on metadata
adlb <- 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"
)

# `h_worsen_counter`
h_worsen_counter(
  df %>% filter(PARAMCD == "CRP" & GRADDR == "Low"),
  id = "USUBJID",
  .var = "ATOXGR",
  baseline_var = "BTOXGR",
  direction_var = "GRADDR"
)
#> $fraction
#> $fraction$`1`
#>   num denom 
#>    44   367 
#> 
#> $fraction$`2`
#>   num denom 
#>    49   379 
#> 
#> $fraction$`3`
#>   num denom 
#>    38   386 
#> 
#> $fraction$`4`
#>   num denom 
#>    21   391 
#> 
#> $fraction$Any
#>   num denom 
#>   152   391 
#> 
#> 

# Internal function - s_count_abnormal_lab_worsen_by_baseline
if (FALSE) {
# Patients with worsening lab grade for CRP in the direction of low
s_count_abnormal_lab_worsen_by_baseline(
  df = df %>% filter(ARMCD == "ARM A" & PARAMCD == "CRP"),
  .var = "ATOXGR",
  variables = list(
    id = "USUBJID",
    baseline_var = "BTOXGR",
    direction_var = "GRADDR"
  )
)
}

# Internal function - a_count_abnormal_lab_worsen_by_baseline
if (FALSE) {
a_count_abnormal_lab_worsen_by_baseline(
  df = df %>% filter(ARMCD == "ARM A" & PARAMCD == "CRP"),
  .var = "ATOXGR",
  variables = list(id = "USUBJID", baseline_var = "BTOXGR", 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 = adsl)
#> Direction of Abnormality       ARM A            ARM B            ARM C     
#>                               (N=134)          (N=134)          (N=132)    
#> ———————————————————————————————————————————————————————————————————————————
#> ALT                                                                        
#>   High                                                                     
#>     1                      16/121 (13.2%)   13/117 (11.1%)   17/117 (14.5%)
#>     2                      14/125 (11.2%)   12/121 (9.9%)    17/120 (14.2%)
#>     3                        9/129 (7%)      15/125 (12%)    13/124 (10.5%)
#>     4                      12/131 (9.2%)    11/130 (8.5%)    13/129 (10.1%)
#>     Any                    51/131 (38.9%)   51/130 (39.2%)   60/129 (46.5%)
#>   Low                                                                      
#>     1                      13/124 (10.5%)   12/121 (9.9%)     9/117 (7.7%) 
#>     2                      13/127 (10.2%)   17/127 (13.4%)   11/124 (8.9%) 
#>     3                      19/129 (14.7%)   12/128 (9.4%)    10/128 (7.8%) 
#>     4                       7/131 (5.3%)     7/131 (5.3%)    10/132 (7.6%) 
#>     Any                    52/131 (39.7%)   48/131 (36.6%)   40/132 (30.3%)
#> CRP                                                                        
#>   Low                                                                      
#>     1                      14/122 (11.5%)   17/125 (13.6%)   13/120 (10.8%)
#>     2                      21/124 (16.9%)   12/130 (9.2%)    16/125 (12.8%)
#>     3                      12/129 (9.3%)     9/131 (6.9%)    17/126 (13.5%)
#>     4                      10/131 (7.6%)     7/133 (5.3%)     4/127 (3.1%) 
#>     Any                    57/131 (43.5%)   45/133 (33.8%)   50/127 (39.4%)
#> IGA                                                                        
#>   High                                                                     
#>     1                      24/118 (20.3%)    12/120 (10%)    13/119 (10.9%)
#>     2                      13/120 (10.8%)   19/124 (15.3%)   13/125 (10.4%)
#>     3                      11/124 (8.9%)    10/128 (7.8%)    17/128 (13.3%)
#>     4                      11/129 (8.5%)     13/130 (10%)     4/130 (3.1%) 
#>     Any                    59/129 (45.7%)   54/130 (41.5%)   47/130 (36.2%)