Feature request: New logslope & c1 impute_start methods #350

DESCRIPTION

@@ -5,7 +5,9 @@ Version: 0.11.0.9000
 Authors@R: c(
     person("Bill", "Denney", email="wdenney@humanpredictions.com", role=c("aut", "cre"), comment=c(ORCID="0000-0002-5759-428X")),
     person("Clare", "Buckeridge", email="clare.buckeridge@pfizer.com", role="aut"),
-    person("Sridhar", "Duvvuri", role="ctb"))
+    person("Sridhar", "Duvvuri", role="ctb"),
+    person("Gerardo Jose", "Rodriguez", , "gerardo.jrac@gmail.com", role = "aut", comment = c(ORCID = "0000-0003-1413-0060"))
+    )
 Imports:
     checkmate,
     dplyr (>= 0.5.0),

NAMESPACE

@@ -90,8 +90,10 @@ export(PKNCA.choose.option)
 export(PKNCA.options)
 export(PKNCA.options.describe)
 export(PKNCA.set.summary)
+export(PKNCA_impute_method_start_c1)
 export(PKNCA_impute_method_start_cmin)
 export(PKNCA_impute_method_start_conc0)
+export(PKNCA_impute_method_start_logslope)
 export(PKNCA_impute_method_start_predose)
 export(PKNCAconc)
 export(PKNCAdata)

NEWS.md

@@ -18,6 +18,8 @@ the dosing including dose amount and route.
 
 * `PKNCAconc()` and `PKNCAdose()` can now accept unit specifications as either
   column names or units to use (#336).
+* New default PKNCA impute start methods for C1 and IV bolus logslope to add for 
+  intervals without a start concentration
 * PKNCA options can now use `tmax` as a reference for BLQ handling by using new
   names in the `conc.blq` argument (`before.tmax`,`after.tmax`)
 

R/impute.R

@@ -120,6 +120,53 @@ PKNCA_impute_method_start_predose <- function(conc, time, start, end, conc.group
   ret
 }
 
+#' @describeIn PKNCA_impute_method Imputes based on a logarithmic slope on the
+#'   first points at time zero concentration (usually in IV bolus at dose time).
+#'   If this imputation is used for NCA calculations, back-extrapolation percent
+#'   will not be calculated or will be calculated as zero.
+#' @export
+PKNCA_impute_method_start_logslope <- function(conc, time, start, end, ..., options = list()) { # nolint
+
+  ret <- data.frame(conc = conc, time = time)
+  mask_start <- time %in% start
+  if (!any(mask_start)) {
+    all_concs <- conc[time >= start  &  time <= end]
+    all_times <- time[time >= start  &  time <= end]
+    if (!all(is.na(all_concs))) {
+      c0 <- pk.calc.c0.method.logslope(conc = all_concs,
+                                       time = all_times,
+                                       time.dose = start)
+      if (!is.na(c0)) {
+        ret <- rbind(ret, data.frame(time = start, conc = c0))
+        ret <- ret[order(ret$time), ]
+      }
+    }
+  }
+  ret
+}
+
+#' @describeIn PKNCA_impute_method Shift the following concentration to a start
+#'   to become the time zero concentration (rarely used; non-monodecay IV bolus).
+#'   If this imputation is used for NCA calculations, back-extrapolation percent
+#'   will not be calculated or will be calculated as zero.
+#' @return A data frame with imputed start concentration.
+#' @export
+PKNCA_impute_method_start_c1 <- function(conc, time, start, end, ..., options = list()) { # nolint
+  ret <- data.frame(conc = conc, time = time)
+  mask_start <- time %in% start
+  if (!any(mask_start)) {
+    assert_conc_time(conc, time)
+    all_concs <- conc[time >= start  &  time <= end]
+    all_times <- time[time >= start  &  time <= end]
+    c1 <- pk.calc.c0.method.c1(conc = all_concs,
+                               time = all_times,
+                               time.dose = start)
+    ret <- rbind(ret, data.frame(time = start, conc = c1))
+    ret <- ret[order(ret$time), ]
+  }
+  ret
+}
+
 #' Separate out a vector of PKNCA imputation methods into a list of functions
 #'
 #' An error will be raised if the functions are not found.

tests/testthat/test-impute.R

@@ -92,6 +92,90 @@ test_that("PKNCA_impute_method_start_cmin", {
 
 })
 
+test_that("PKNCA_impute_method_start_logslope", {
+  # No imputation when start is in the data
+  expect_equal(
+    PKNCA_impute_method_start_logslope(conc = 3:1, time = 0:2, start = 0, end = 2),
+    data.frame(conc = 3:1, time = 0:2)
+  )
+  # Impute when start is not in the data
+  expect_equal(
+    PKNCA_impute_method_start_logslope(conc = 3:1, time = 1:3, start = 0, end = 3),
+    data.frame(conc = c(4.5, 3:1), time = 0:3),
+    ignore_attr = TRUE
+  )
+  # Data outside the interval are ignored (before interval)
+  expect_equal(
+    PKNCA_impute_method_start_logslope(conc = c(0, 2:1), time = c(-1, 1:2), start = 0, end = 2),
+    data.frame(conc = c(0, 4, 2:1), time = c(-1, 0, 1:2)),
+    ignore_attr = TRUE
+  )
+  # No modification if no C1 -> C2 decline in samples
+  expect_equal(
+    PKNCA_impute_method_start_logslope(conc = c(1, 1, 1), time = 1:3, start = 0, end = 3),
+    data.frame(conc = c(1, 1, 1), time = 1:3),
+    ignore_attr = TRUE
+  )
+  # No modification if C1 = C2 in samples
+  expect_equal(
+    PKNCA_impute_method_start_logslope(conc = c(3, 3, 1), time = 1:3, start = 0, end = 3),
+    data.frame(conc = c(3, 3, 1), time = 1:3),
+    ignore_attr = TRUE
+  )
+  # All concentrations are NA -> does not change
+  expect_equal(
+    PKNCA_impute_method_start_logslope(conc = c(NA, NA, NA), time = 1:3, start = 0, end = 3),
+    data.frame(conc = c(NA, NA, NA), time = 1:3)
+  )
+  # All times are NA -> does not change
+  expect_equal(
+    PKNCA_impute_method_start_logslope(conc = 1:3, time = c(NA, NA, NA), start = 0, end = 3),
+    data.frame(conc = 1:3, time = c(NA, NA, NA))
+  )
+  # All concentrations are 0 -> does not change
+  expect_equal(
+    PKNCA_impute_method_start_logslope(conc = c(0, 0, 0), time = 1:3, start = 0, end = 3),
+    data.frame(conc = c(0, 0, 0), time = 1:3)
+  )
+})
+
+test_that("PKNCA_impute_method_start_c1", {
+  # No imputation when start is in the data
+  expect_equal(
+    PKNCA_impute_method_start_c1(conc = 1:3, time = 0:2, start = 0, end = 2),
+    data.frame(conc = 1:3, time = 0:2)
+  )
+  # Impute when start is not in the data
+  expect_equal(
+    PKNCA_impute_method_start_c1(conc = 1:3, time = 1:3, start = 0, end = 3),
+    data.frame(conc = c(1, 1:3), time = 0:3),
+    ignore_attr = TRUE
+  )
+  # Data outside the interval are ignored (before interval)
+  expect_equal(
+    PKNCA_impute_method_start_c1(conc = 1:3, time = c(-1, 1:2), start = 0, end = 2),
+    data.frame(conc = c(1, 2, 2:3), time = c(-1, 0, 1:2)),
+    ignore_attr = TRUE
+  )
+  # All concentrations are NA
+  expect_equal(
+    PKNCA_impute_method_start_c1(conc = c(NA, NA, NA), time = 1:3, start = 0, end = 3),
+    data.frame(conc = c(NA, NA, NA, NA), time = 0:3),
+    ignore_attr = TRUE
+  )
+  # All times are NA
+  expect_error(
+    PKNCA_impute_method_start_c1(conc = 1:3, time = c(NA, NA, NA), start = 0, end = 3),
+    "Assertion on 'time' failed: Contains missing values"
+  )
+  # All concentrations are 0
+  expect_equal(
+    PKNCA_impute_method_start_c1(conc = c(0, 0, 0), time = 1:3, start = 0, end = 3),
+    data.frame(conc = c(0, 0, 0, 0), time = 0:3),
+    ignore_attr = TRUE
+  )
+})
+
 test_that("PKNCA_impute_fun_list", {
   expect_equal(
     PKNCA_impute_fun_list(NA_character_),