tabulate_exposure_predictions

Description

Tablulates exposure predictions at therapeutic and supratherapuetic Cmax.

Usage

tabulate_exposure_predictions(
  data,
  fit,
  conc_col,
  treatment_predictors,
  control_predictors = NULL,
  doses,
  cmaxes,
  qtc_label = "QTc (
  ms
)",
  conc_units = "ng/mL",
  conf_int = 0.9,
  decimals = 2,
  scientific = TRUE,
  title = NULL,
  ...
)

Arguments

Name	Description
data	a dataframe of QTc dataset
fit	the lme model to use for predictions
conc_col	an unquoted column name of concentration measurements used to fit the model
treatment_predictors	list of a values for contrast. conc will update
control_predictors	list of b values for contrast
doses	vector of Doses to show prediction at
cmaxes	vector of Cmax for each dose
qtc_label	label for QTc column name, default QTc (ms)
conc_units	Units for concentration default ng/mL
conf_int	confidence interval for predictions. Default 90%
decimals	number of decimals to format numbers to. default is 2
scientific	boolean for converting to scientific notation
title	optional string for table title. Wrapped in gt::md()
...	optional additional args to gt::tab_options

Returns

a gt table of predicted dQTc/ddQTc values and their CI at tpx and or stpx dose/Cmax

Examples

data_proc <- preprocess(data)

 fit <- fit_prespecified_model(
   data_proc,
   deltaQTCF,
   ID,
   CONC,
   deltaQTCFBL,
   TRTG,
   TAFD,
   "REML",
   TRUE
 )
 pk_df <- compute_pk_parameters(
   data_proc %>% dplyr::filter(DOSE != 0),
   ID,
   DOSEF,
   CONC,
   NTLD
 )

 tabulate_exposure_predictions(
   data_proc,
   fit,
   CONC,
   list(
     CONC = 10,
     deltaQTCFBL = 0,
     TRTG = "Verapamil HCL",
     TAFD = "2 HR"),
   list(
     CONC = 0,
     deltaQTCFBL = 0,
     TRTG = "Placebo",
     TAFD = "2 HR"),
   doses <- c(120),
   cmaxes <- c(pk_df[[1, "Cmax_gm"]])
 )