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admiral (version 1.1.1)

derive_param_framingham: Adds a Parameter for Framingham Heart Study Cardiovascular Disease 10-Year Risk Score

Description

Adds a record for framingham score (FCVD101) for each by group (e.g., subject and visit) where the source parameters are available.

Usage

derive_param_framingham(
  dataset,
  by_vars,
  set_values_to = exprs(PARAMCD = "FCVD101"),
  sysbp_code = "SYSBP",
  chol_code = "CHOL",
  cholhdl_code = "CHOLHDL",
  age = AGE,
  sex = SEX,
  smokefl = SMOKEFL,
  diabetfl = DIABETFL,
  trthypfl = TRTHYPFL,
  get_unit_expr,
  filter = NULL
)

Value

The input dataset with the new parameter added

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 sysbp_code, chol_code and hdl_code.

by_vars

Grouping variables

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

sysbp_code

Systolic blood pressure parameter code

The observations where PARAMCD equals the specified value are considered as the systolic blood pressure assessments.

Permitted Values: character value

chol_code

Total serum cholesterol code

The observations where PARAMCD equals the specified value are considered as the total cholesterol assessments. This must be measured in mg/dL.

Permitted Values: character value

cholhdl_code

HDL serum cholesterol code

The observations where PARAMCD equals the specified value are considered as the HDL cholesterol assessments. This must be measured in mg/dL.

Permitted Values: character value

age

Subject age

A variable containing the subject's age.

Permitted Values: A numeric variable name that refers to a subject age column of the input dataset

sex

Subject sex

A variable containing the subject's sex.

Permitted Values: A character variable name that refers to a subject sex column of the input dataset

smokefl

Smoking status flag

A flag indicating smoking status.

Permitted Values: A character variable name that refers to a smoking status column of the input dataset.

diabetfl

Diabetic flag

A flag indicating diabetic status.

Permitted Values: A character variable name that refers to a diabetic status column of the input dataset

trthypfl

Treated with hypertension medication flag

A flag indicating if a subject was treated with hypertension medication.

Permitted Values: A character variable name that refers to a column that indicates whether a subject is treated for high blood pressure

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: A variable of the input dataset or a function call

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

Details

The values of age, sex, smokefl, diabetfl and trthypfl will be added to the by_vars list. The predicted probability of having cardiovascular disease (CVD) within 10-years according to Framingham formula. See AHA Journal article General Cardiovascular Risk Profile for Use in Primary Care for reference.

For Women:

FactorAmount
Age2.32888
Total Chol1.20904
HDL Chol-0.70833
Sys BP2.76157
Sys BP + Hypertension Meds2.82263
Smoker0.52873
Non-Smoker0
Diabetic0.69154
Not Diabetic0
Average Risk26.1931
Risk Period0.95012

For Men:

FactorAmount
Age3.06117
Total Chol1.12370
HDL Chol-0.93263
Sys BP1.93303
Sys BP + Hypertension Meds2.99881
Smoker.65451
Non-Smoker0
Diabetic0.57367
Not Diabetic0
Average Risk23.9802
Risk Period0.88936

The equation for calculating risk:

$$RiskFactors = (log(Age) * AgeFactor) + (log(TotalChol) * TotalCholFactor) + (log(CholHDL) * CholHDLFactor) \\ + (log(SysBP) * SysBPFactor) + Smoker + Diabetes Present - AvgRisk$$

$$Risk = 100 * (1 - RiskPeriodFactor^{RiskFactors})$$

See Also

compute_framingham()

BDS-Findings Functions for adding Parameters/Records: default_qtc_paramcd(), derive_expected_records(), derive_extreme_event(), derive_extreme_records(), derive_locf_records(), derive_param_bmi(), derive_param_bsa(), derive_param_computed(), derive_param_doseint(), derive_param_exist_flag(), derive_param_exposure(), derive_param_map(), derive_param_qtc(), derive_param_rr(), derive_param_wbc_abs(), derive_summary_records()

Examples

Run this code
library(tibble)

adcvrisk <- tribble(
  ~USUBJID, ~PARAMCD, ~PARAM, ~AVAL, ~AVALU,
  ~VISIT, ~AGE, ~SEX, ~SMOKEFL, ~DIABETFL, ~TRTHYPFL,
  "01-701-1015", "SYSBP", "Systolic Blood Pressure (mmHg)", 121,
  "mmHg", "BASELINE", 44, "F", "N", "N", "N",
  "01-701-1015", "SYSBP", "Systolic Blood Pressure (mmHg)", 115,
  "mmHg", "WEEK 2", 44, "F", "N", "N", "Y",
  "01-701-1015", "CHOL", "Total Cholesterol (mg/dL)", 216.16,
  "mg/dL", "BASELINE", 44, "F", "N", "N", "N",
  "01-701-1015", "CHOL", "Total Cholesterol (mg/dL)", 210.78,
  "mg/dL", "WEEK 2", 44, "F", "N", "N", "Y",
  "01-701-1015", "CHOLHDL", "Cholesterol/HDL-Cholesterol (mg/dL)", 54.91,
  "mg/dL", "BASELINE", 44, "F", "N", "N", "N",
  "01-701-1015", "CHOLHDL", "Cholesterol/HDL-Cholesterol (mg/dL)", 26.72,
  "mg/dL", "WEEK 2", 44, "F", "N", "N", "Y",
  "01-701-1028", "SYSBP", "Systolic Blood Pressure (mmHg)", 119,
  "mmHg", "BASELINE", 55, "M", "Y", "Y", "Y",
  "01-701-1028", "SYSBP", "Systolic Blood Pressure (mmHg)", 101,
  "mmHg", "WEEK 2", 55, "M", "Y", "Y", "Y",
  "01-701-1028", "CHOL", "Total Cholesterol (mg/dL)", 292.01,
  "mg/dL", "BASELINE", 55, "M", "Y", "Y", "Y",
  "01-701-1028", "CHOL", "Total Cholesterol (mg/dL)", 246.73,
  "mg/dL", "WEEK 2", 55, "M", "Y", "Y", "Y",
  "01-701-1028", "CHOLHDL", "Cholesterol/HDL-Cholesterol (mg/dL)", 65.55,
  "mg/dL", "BASELINE", 55, "M", "Y", "Y", "Y",
  "01-701-1028", "CHOLHDL", "Cholesterol/HDL-Cholesterol (mg/dL)", 44.62,
  "mg/dL", "WEEK 2", 55, "M", "Y", "Y", "Y"
)


adcvrisk %>%
  derive_param_framingham(
    by_vars = exprs(USUBJID, VISIT),
    set_values_to = exprs(
      PARAMCD = "FCVD101",
      PARAM = "FCVD1-Framingham CVD 10-Year Risk Score (%)"
    ),
    get_unit_expr = AVALU
  )

derive_param_framingham(
  adcvrisk,
  by_vars = exprs(USUBJID, VISIT),
  set_values_to = exprs(
    PARAMCD = "FCVD101",
    PARAM = "FCVD1-Framingham CVD 10-Year Risk Score (%)"
  ),
  get_unit_expr = extract_unit(PARAM)
)

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