Vital Signs Analysis Dataset (ADVS)

Synthetic record-level vital signs dataset from study TFRM-2024-001. Contains one row per subject per parameter per visit. Some subjects have missing parameters to create natural N variation across vital sign groups — exactly the scenario that per-group N-count headers address.

Designed as the source for fr_cols() .n data frame parameter when the display table (tbl_vs) is pre-summarized.

Usage

advs

Format

A data frame with approximately 1900 rows and 12 variables:

STUDYID: Study identifier ("TFRM-2024-001")
USUBJID: Unique subject identifier
TRTA: Actual treatment arm: "Placebo", "Zomerane 50mg", or "Zomerane 100mg"
TRTAN: Actual treatment numeric code: 0, 50, or 100
SAFFL: Safety population flag ("Y")
PARAM: Vital sign parameter: "Systolic BP (mmHg)", "Diastolic BP (mmHg)", "Heart Rate (bpm)", "Weight (kg)", or "Temperature (C)"
PARAMCD: Parameter code: "SYSBP", "DIABP", "HR", "WEIGHT", or "TEMP"
AVISIT: Analysis visit: "Baseline", "Week 12", or "Week 24"
AVAL: Analysis value (measured vital sign)
BASE: Baseline value (copy of AVAL at Baseline visit)
CHG: Change from baseline (NA at baseline)
ABLFL: Baseline record flag: "Y" at Baseline, NA otherwise

Source

Synthetic data generated in data-raw/create_adam_datasets.R using subjects from adsl.

N variation by design

Not all subjects have every parameter measured. Availability rates decrease with dose and parameter complexity — Temperature has the most missing data, Blood Pressure the least. This produces realistic per-group N differences:

Parameter	Placebo	Zom 50mg	Zom 100mg
Systolic BP	45	~41	~43
Heart Rate	~40	~42	~38
Temperature	~38	~42	~36

Examples

# Subjects per parameter per arm
with(
  advs[advs$AVISIT == "Baseline", ],
  tapply(USUBJID, list(PARAM, TRTA), function(x) length(unique(x)))
)
#>                     Placebo Zomerane 100mg Zomerane 50mg
#> Diastolic BP (mmHg)      45             43            45
#> Heart Rate (bpm)         40             38            42
#> Systolic BP (mmHg)       45             43            41
#> Temperature (C)          38             36            42
#> Weight (kg)              43             42            41

# Use as N-count source via data frame
vs_n <- aggregate(
  USUBJID ~ PARAM + TRTA, data = advs[advs$AVISIT == "Baseline", ],
  FUN = function(x) length(unique(x))
)
names(vs_n) <- c("param", "trt", "n")
tbl_vs |>
  fr_table() |>
  fr_rows(page_by = "param") |>
  fr_cols(.n = vs_n, .n_format = "{label}\n(N={n})")
#> 
#> ── fr_spec: Table 
#> Data: 60 rows x 12 columns
#> Page: landscape letter, 9pt Courier New
#> Columns (12 visible of 12):
#> param "param" 1.57in left
#> timepoint "timepoint" 0.82in left
#> statistic "statistic" 0.82in left
#> placebo_base "placebo_base" 1.12in left
#> placebo_value "placebo_value" 1.12in left
#> placebo_chg "placebo_chg" 0.97in left
#> zom_50mg_base "zom_50mg_base" 1.12in left
#> zom_50mg_value "zom_50mg_value" 1.20in left
#> ... and 4 more
#> Header: valign=bottom
#> Rows: page_by=param