Adds a record for BMI/Body Mass Index using Weight and Height each by group (e.g., subject and visit) where the source parameters are available.
Note: This is a wrapper function for the more generic derive_param_computed().
derive_param_bmi(
dataset,
by_vars,
set_values_to = exprs(PARAMCD = "BMI"),
weight_code = "WEIGHT",
height_code = "HEIGHT",
get_unit_expr,
filter = NULL,
constant_by_vars = NULL
)Input dataset
The variables specified by the by_vars argument are expected to be in the dataset.
PARAMCD, and AVAL are expected as well.
The variable specified by by_vars and PARAMCD must be a unique key of
the input dataset after restricting it by the filter condition (filter
parameter) and to the parameters specified by weight_code and height_code.
none
Grouping variables
For each group defined by by_vars an observation is added to the output
dataset. Only variables specified in by_vars will be populated
in the newly created records.
list of variables created by exprs(), e.g., exprs(USUBJID, VISIT)
none
Variables to be set
The specified variables are set to the specified values for the new
observations. For example exprs(PARAMCD = "MAP") defines the parameter code
for the new parameter.
List of variable-value pairs
exprs(PARAMCD = "MAP")
WEIGHT parameter code
The observations where PARAMCD equals the specified value are considered
as the WEIGHT. It is expected that WEIGHT is measured in kg
character value
"WEIGHT"
HEIGHT parameter code
The observations where PARAMCD equals the specified value are considered
as the HEIGHT. It is expected that HEIGHT is measured in cm
logical scalar
"HEIGHT"
An expression providing the unit of the parameter
The result is used to check the units of the input parameters.
An expression which is evaluable in the input dataset and results in a character value
none
Filter condition
The specified condition is applied to the input dataset before deriving the new parameter, i.e., only observations fulfilling the condition are taken into account.
an unquoted condition, e.g., AVISIT == "BASELINE"
NULL
By variables for when HEIGHT is constant
When HEIGHT is constant, the HEIGHT parameters (measured only once) are merged to the other parameters using the specified variables.
If height is constant (e.g. only measured once at screening or baseline) then
use constant_by_vars to select the subject-level variable to merge on (e.g. USUBJID).
This will produce BMI at all visits where weight is measured. Otherwise
it will only be calculated at visits with both height and weight collected.
NULL
The input dataset with the new parameter added. Note, a variable will only
be populated in the new parameter rows if it is specified in by_vars.
The analysis value of the new parameter is derived as $$BMI = \frac{WEIGHT}{HEIGHT^2}$$
BDS-Findings Functions for adding Parameters/Records:
default_qtc_paramcd(),
derive_expected_records(),
derive_extreme_event(),
derive_extreme_records(),
derive_locf_records(),
derive_param_bsa(),
derive_param_computed(),
derive_param_doseint(),
derive_param_exist_flag(),
derive_param_exposure(),
derive_param_framingham(),
derive_param_map(),
derive_param_qtc(),
derive_param_rr(),
derive_param_wbc_abs(),
derive_summary_records()
# Example 1: Derive BMI where height is measured only once using constant_by_vars
advs <- tibble::tribble(
~USUBJID, ~PARAMCD, ~PARAM, ~AVAL, ~AVISIT,
"01-701-1015", "HEIGHT", "Height (cm)", 147, "SCREENING",
"01-701-1015", "WEIGHT", "Weight (kg)", 54.0, "SCREENING",
"01-701-1015", "WEIGHT", "Weight (kg)", 54.4, "BASELINE",
"01-701-1015", "WEIGHT", "Weight (kg)", 53.1, "WEEK 2",
"01-701-1028", "HEIGHT", "Height (cm)", 163, "SCREENING",
"01-701-1028", "WEIGHT", "Weight (kg)", 78.5, "SCREENING",
"01-701-1028", "WEIGHT", "Weight (kg)", 80.3, "BASELINE",
"01-701-1028", "WEIGHT", "Weight (kg)", 80.7, "WEEK 2"
)
derive_param_bmi(
advs,
by_vars = exprs(USUBJID, AVISIT),
weight_code = "WEIGHT",
height_code = "HEIGHT",
set_values_to = exprs(
PARAMCD = "BMI",
PARAM = "Body Mass Index (kg/m^2)"
),
get_unit_expr = extract_unit(PARAM),
constant_by_vars = exprs(USUBJID)
)
#> # A tibble: 14 × 5
#> USUBJID PARAMCD PARAM AVAL AVISIT
#> <chr> <chr> <chr> <dbl> <chr>
#> 1 01-701-1015 HEIGHT Height (cm) 147 SCREENING
#> 2 01-701-1015 WEIGHT Weight (kg) 54 SCREENING
#> 3 01-701-1015 WEIGHT Weight (kg) 54.4 BASELINE
#> 4 01-701-1015 WEIGHT Weight (kg) 53.1 WEEK 2
#> 5 01-701-1028 HEIGHT Height (cm) 163 SCREENING
#> 6 01-701-1028 WEIGHT Weight (kg) 78.5 SCREENING
#> 7 01-701-1028 WEIGHT Weight (kg) 80.3 BASELINE
#> 8 01-701-1028 WEIGHT Weight (kg) 80.7 WEEK 2
#> 9 01-701-1015 BMI Body Mass Index (kg/m^2) 25.0 SCREENING
#> 10 01-701-1015 BMI Body Mass Index (kg/m^2) 25.2 BASELINE
#> 11 01-701-1015 BMI Body Mass Index (kg/m^2) 24.6 WEEK 2
#> 12 01-701-1028 BMI Body Mass Index (kg/m^2) 29.5 SCREENING
#> 13 01-701-1028 BMI Body Mass Index (kg/m^2) 30.2 BASELINE
#> 14 01-701-1028 BMI Body Mass Index (kg/m^2) 30.4 WEEK 2
# Example 2: Derive BMI where height is measured only once and keep only one record
# where both height and weight are measured.
derive_param_bmi(
advs,
by_vars = exprs(USUBJID, AVISIT),
weight_code = "WEIGHT",
height_code = "HEIGHT",
set_values_to = exprs(
PARAMCD = "BMI",
PARAM = "Body Mass Index (kg/m^2)"
),
get_unit_expr = extract_unit(PARAM)
)
#> # A tibble: 10 × 5
#> USUBJID PARAMCD PARAM AVAL AVISIT
#> <chr> <chr> <chr> <dbl> <chr>
#> 1 01-701-1015 HEIGHT Height (cm) 147 SCREENING
#> 2 01-701-1015 WEIGHT Weight (kg) 54 SCREENING
#> 3 01-701-1015 WEIGHT Weight (kg) 54.4 BASELINE
#> 4 01-701-1015 WEIGHT Weight (kg) 53.1 WEEK 2
#> 5 01-701-1028 HEIGHT Height (cm) 163 SCREENING
#> 6 01-701-1028 WEIGHT Weight (kg) 78.5 SCREENING
#> 7 01-701-1028 WEIGHT Weight (kg) 80.3 BASELINE
#> 8 01-701-1028 WEIGHT Weight (kg) 80.7 WEEK 2
#> 9 01-701-1015 BMI Body Mass Index (kg/m^2) 25.0 SCREENING
#> 10 01-701-1028 BMI Body Mass Index (kg/m^2) 29.5 SCREENING
# Example 3: Pediatric study where height and weight are measured multiple times
advs <- tibble::tribble(
~USUBJID, ~PARAMCD, ~PARAM, ~AVAL, ~VISIT,
"01-101-1001", "HEIGHT", "Height (cm)", 47.1, "BASELINE",
"01-101-1001", "HEIGHT", "Height (cm)", 59.1, "WEEK 12",
"01-101-1001", "HEIGHT", "Height (cm)", 64.7, "WEEK 24",
"01-101-1001", "HEIGHT", "Height (cm)", 68.2, "WEEK 48",
"01-101-1001", "WEIGHT", "Weight (kg)", 2.6, "BASELINE",
"01-101-1001", "WEIGHT", "Weight (kg)", 5.3, "WEEK 12",
"01-101-1001", "WEIGHT", "Weight (kg)", 6.7, "WEEK 24",
"01-101-1001", "WEIGHT", "Weight (kg)", 7.4, "WEEK 48",
)
derive_param_bmi(
advs,
by_vars = exprs(USUBJID, VISIT),
weight_code = "WEIGHT",
height_code = "HEIGHT",
set_values_to = exprs(
PARAMCD = "BMI",
PARAM = "Body Mass Index (kg/m^2)"
),
get_unit_expr = extract_unit(PARAM)
)
#> # A tibble: 12 × 5
#> USUBJID PARAMCD PARAM AVAL VISIT
#> <chr> <chr> <chr> <dbl> <chr>
#> 1 01-101-1001 HEIGHT Height (cm) 47.1 BASELINE
#> 2 01-101-1001 HEIGHT Height (cm) 59.1 WEEK 12
#> 3 01-101-1001 HEIGHT Height (cm) 64.7 WEEK 24
#> 4 01-101-1001 HEIGHT Height (cm) 68.2 WEEK 48
#> 5 01-101-1001 WEIGHT Weight (kg) 2.6 BASELINE
#> 6 01-101-1001 WEIGHT Weight (kg) 5.3 WEEK 12
#> 7 01-101-1001 WEIGHT Weight (kg) 6.7 WEEK 24
#> 8 01-101-1001 WEIGHT Weight (kg) 7.4 WEEK 48
#> 9 01-101-1001 BMI Body Mass Index (kg/m^2) 11.7 BASELINE
#> 10 01-101-1001 BMI Body Mass Index (kg/m^2) 15.2 WEEK 12
#> 11 01-101-1001 BMI Body Mass Index (kg/m^2) 16.0 WEEK 24
#> 12 01-101-1001 BMI Body Mass Index (kg/m^2) 15.9 WEEK 48