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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().

Usage

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
)

Arguments

dataset

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.

by_vars

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.

Permitted Values: list of variables created by exprs() e.g. exprs(USUBJID, VISIT)

set_values_to

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.

Permitted Values: List of variable-value pairs

weight_code

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

Permitted Values: character value

height_code

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

Permitted Values: character value

Permitted Values: logical scalar

get_unit_expr

An expression providing the unit of the parameter

The result is used to check the units of the input parameters.

Permitted Values: An expression which is evaluable in the input dataset and results in a character value

filter

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.

Permitted Values: a condition

constant_by_vars

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.

Permitted Values: list of variables created by exprs() e.g. exprs(USUBJID, VISIT)

Value

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.

Details

The analysis value of the new parameter is derived as $$BMI = \frac{WEIGHT}{HEIGHT^2}$$

Examples


# 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