Incidence of Laboratory Test Abnormalities (Without Regard to Baseline Abnormality)

Incidence of Laboratory Test Abnormalities (Without Regard to Baseline Abnormality)

Usage

lab_abnormality_summary(
  datain,
  crit_vars = "CRIT1~CRIT2",
  pctdisp = "SUBGRP",
  a_subset = NA_character_,
  denom_subset = NA_character_,
  sigdec = 2,
  sparseyn = "Y",
  pctsyn = "N",
  stathead = "n (%)"
)

Arguments

datain

Input dataset (adlb).

crit_vars

Criteria variables

pctdisp

Method to calculate denominator (for %) by. Possible values: "TRT", "VAR", "COL", "SUBGRP", "CAT", "NONE", "NO", "DPTVAR", "BYVARxyN"

a_subset

Analysis Subset condition specific to categorical analysis.

denom_subset

Subset condition to be applied to data set for calculating denominator.

sigdec

Number of decimal places for % displayed in output

sparseyn

To sparse missing categories/treatments or not? "Y"/"N"

pctsyn

Display Percentage Sign in table or not. Values: "Y"/"N"

stathead

Column label to display n in the output. Default is n (%) Values: "TRT", "VAR","COL", "SUBGRP", "SGRPN", "CAT", "NONE", "NO", "DPTVAR"

Value

data.frame with summary of laboratory abnormality incidence counts

Examples

data("adlb")

lb_entry <- adlb |>
  mentry(
    subset = NA_character_,
    byvar = "PARCAT1~PARAM",
    subgrpvar = NA_character_,
    trtvar = "TRTA",
    trtsort = "TRTAN",
    trttotalyn = "N",
    sgtotalyn = "N",
    add_grpmiss = "N",
    pop_fil = "SAFFL"
  )

out <-
  lb_entry |>
  lab_abnormality_summary(
    crit_vars = "CRIT1~CRIT2",
    pctdisp = "SUBGRP",
    a_subset = NA_character_,
    denom_subset = NA_character_,
    sigdec = 1
  ) |>
  display_bign_head(mentry_data = lb_entry) |>
  tbl_processor()
#> `denom_subset` not specified, set to APSBLFL == 'Y'
#> mcatstat success
#> mcatstat success

out
#> # A tibble: 2 × 12
#>   BYVAR1 BYVAR2               DPTVAL   DPTVALN DPTVARN CN    `Placebo (N=86)_N `
#>   <chr>  <chr>                <chr>      <dbl>   <int> <chr> <chr>              
#> 1 CHEM   Sodium (mmol/L)      < 135x …       1       1 C     5                  
#> 2 CHEM   Cholesterol (mmol/L) > 5.17x…       1       2 C     68                 
#> # ℹ 5 more variables: `Placebo (N=86)_n (%) ` <chr>,
#> #   `Xanomeline Low Dose (N=84)_N ` <chr>,
#> #   `Xanomeline Low Dose (N=84)_n (%) ` <chr>,
#> #   `Xanomeline High Dose (N=84)_N ` <chr>,
#> #   `Xanomeline High Dose (N=84)_n (%) ` <chr>

# `flextable` output
out |>
  tbl_display(
    bylabel = "Parameter Category~Parameter",
    dpthead = "Primary Criteria"
  )
Parameter Category
Parameter
Primary Criteria
Placebo (N=86)
Xanomeline Low Dose (N=84)
Xanomeline High Dose (N=84)
N 
n (%) 
N 
n (%) 
N 
n (%) 
CHEM
Sodium (mmol/L)
< 135x LLN
5
7 (140.0)
3
5 (166.7)
8
9 (112.5)
Cholesterol (mmol/L)
> 5.17x ULN
68
72 (105.9)
62
64 (103.2)
57
68 (119.3)