Exclude manual point half-life values calculated to be negative

NEWS.md

@@ -13,6 +13,8 @@ the dosing including dose amount and route.
 * `NA` results from calculating `c0` will now add an exclusion reason.
 * AUC for intravenous dosing (all the `auciv*` parameters) now more robustly
   calculate `c0` and does not raise an error when `is.na(c0)` (#353).
+* Manual calculation of half.life no longer allows negative half-live values
+  (#373).
 
 ## New Features
 
@@ -23,6 +25,10 @@ the dosing including dose amount and route.
 * A new parameter `count_conc_measured` was added to enable quality checks,
   typically on AUC measurements. An associated exclusion function,
   `exclude_nca_conc_count_measured()` was also added.
+* The `PKNCAconc()` arguments of `include_half.life` and `exclude_half.life` now
+  allow `NA` values. If all values are `NA`, then no inclusion or exclusion is
+  applied (the interval is treated as-is, like the argument had not been given).
+  If some values are `NA` for the interval, those are treated as `FALSE`.
 
 # Minor changes (unlikely to affect PKNCA use)
 

R/half.life.R

@@ -168,6 +168,9 @@ pk.calc.half.life <- function(conc, time, tmax, tlast,
     if (nrow(data) > 0) {
       fit <- fit_half_life(data=data, tlast=ret$tlast, conc_units=conc_units)
       ret[,ret_replacements] <- fit[,ret_replacements]
+      if (ret$half.life <= 0) {
+        attr(ret, "exclude") <- "Negative half-life estimated with manually-selected points"
+      }
     } else {
       warning("No data to manually fit for half-life (all concentrations may be 0 or excluded)")
       ret <-

R/pk.calc.all.R

@@ -475,13 +475,15 @@ pk.nca.interval <- function(conc, time, volume, duration.conc,
       }
       # Apply manual inclusion and exclusion
       if (n %in% "half.life") {
-        if (!is.null(include_half.life)) {
-          call_args$conc <- call_args$conc[include_half.life]
-          call_args$time <- call_args$time[include_half.life]
+        if (!is.null(include_half.life) && !all(is.na(include_half.life))) {
+          include_tf <- include_half.life %in% TRUE
+          call_args$conc <- call_args$conc[include_tf]
+          call_args$time <- call_args$time[include_tf]
           call_args$manually.selected.points <- TRUE
-        } else if (!is.null(exclude_half.life)) {
-          call_args$conc <- call_args$conc[!exclude_half.life]
-          call_args$time <- call_args$time[!exclude_half.life]
+        } else if (!is.null(exclude_half.life) && !all(is.na(exclude_half.life))) {
+          exclude_tf <- exclude_half.life %in% TRUE
+          call_args$conc <- call_args$conc[!exclude_tf]
+          call_args$time <- call_args$time[!exclude_tf]
         }
       }
       # Do the calculation

tests/testthat/test-half.life.R

@@ -18,7 +18,7 @@ test_that("pk.calc.half.life", {
                       allow.tmax.in.half.life=TRUE,
                       adj.r.squared.factor=0.0001,
                       check=FALSE)$half.life
-                 
+
   expect_equal(v2, 1)
 
   # Ensure that min.hl.points is respected
@@ -56,7 +56,7 @@ test_that("pk.calc.half.life", {
                                    check=FALSE)$half.life,
                  1.000346,
                  tolerance=0.00001))
-  
+
 
   # Make sure that when tmax and tlast are given that they are
   # automatically included and not recalculated
@@ -171,6 +171,25 @@ test_that("half-life manual point selection", {
   )
   expect_true(all(is.na(unlist(manual_blq))),
               info="All BLQ with manual point selection gives all NA results")
+
+  excluded_result <-
+    data.frame(
+      lambda.z = -log(2),
+      r.squared = 1,
+      adj.r.squared = 1,
+      lambda.z.time.first = 1L,
+      lambda.z.n.points = 3L,
+      clast.pred = 8,
+      half.life = -1,
+      span.ratio = -2,
+      tmax = 3L,
+      tlast = 3L
+    )
+  attr(excluded_result, "exclude") <- "Negative half-life estimated with manually-selected points"
+  expect_equal(
+    pk.calc.half.life(conc = 2^(1:3), time = 1:3, manually.selected.points = TRUE),
+    excluded_result
+  )
 })
 
 test_that("two-point half-life succeeds (fix #114)", {

tests/testthat/test-pk.calc.all.R

@@ -333,6 +333,53 @@ test_that("half life inclusion and exclusion", {
   expect_false(identical(myresult$result, myresult_incl$result))
 })
 
+test_that("include_half.life and exclude_half.life work with NAs treated as missing for all NA and as FALSE for partial NA (#372)", {
+  # Partial NA include_hl is used
+  d_conc_incl <- data.frame(conc = c(1, 0.6, 0.3, 0.25, 0.15, 0.1), time = 0:5, include_hl = c(FALSE, NA, TRUE, TRUE, TRUE, TRUE))
+  o_conc_incl <- PKNCAconc(d_conc_incl, conc~time, include_half.life = "include_hl")
+  o_data_incl <- PKNCAdata(o_conc_incl, intervals = data.frame(start = 0, end = Inf, half.life = TRUE))
+  suppressMessages(o_nca_incl <- pk.nca(o_data_incl))
+  expect_equal(as.data.frame(o_nca_incl, out_format = "wide")$half.life, 1.820879, tolerance = 0.00001)
+
+  # All FALSE include_hl is used
+  d_conc_false <- data.frame(conc = c(1, 0.6, 0.3, 0.25, 0.15, 0.1), time = 0:5, include_hl = FALSE)
+  o_conc_false <- PKNCAconc(d_conc_false, conc~time, include_half.life = "include_hl")
+  o_data_false <- PKNCAdata(o_conc_false, intervals = data.frame(start = 0, end = Inf, half.life = TRUE))
+  suppressWarnings(suppressMessages(o_nca_false <- pk.nca(o_data_false)))
+  d_nca_false <- as.data.frame(o_nca_false)
+  expect_equal(d_nca_false$PPORRES[d_nca_false$PPTESTCD %in% "half.life"], NA_real_)
+
+  # All NA include_hl is ignored
+  d_conc <- data.frame(conc = c(1, 0.6, 0.3, 0.25, 0.15, 0.1), time = 0:5, include_hl = NA)
+  o_conc <- PKNCAconc(d_conc, conc~time, include_half.life = "include_hl")
+  o_data <- PKNCAdata(o_conc, intervals = data.frame(start = 0, end = Inf, half.life = TRUE))
+  suppressMessages(o_nca <- pk.nca(o_data))
+  expect_equal(as.data.frame(o_nca, out_format = "wide")$half.life, 1.512942, tolerance = 0.00001)
+
+  # Partial NA include_hl is used
+  d_conc_excl <- data.frame(conc = c(1, 0.6, 0.3, 0.25, 0.15, 0.1), time = 0:5, exclude_hl = c(FALSE, NA, TRUE, TRUE, TRUE, TRUE))
+  o_conc_excl <- PKNCAconc(d_conc_excl, conc~time, exclude_half.life = "exclude_hl")
+  o_data_excl <- PKNCAdata(o_conc_excl, intervals = data.frame(start = 0, end = Inf, half.life = TRUE))
+  suppressWarnings(suppressMessages(o_nca_excl <- pk.nca(o_data_excl)))
+  d_nca_excl <- as.data.frame(o_nca_excl)
+  expect_equal(d_nca_excl$PPORRES[d_nca_excl$PPTESTCD %in% "half.life"], NA_real_)
+
+  # All NA exclude_hl is ignored
+  d_conc <- data.frame(conc = c(1, 0.6, 0.3, 0.25, 0.15, 0.1), time = 0:5, exclude_hl = NA)
+  o_conc <- PKNCAconc(d_conc, conc~time, exclude_half.life = "exclude_hl")
+  o_data <- PKNCAdata(o_conc, intervals = data.frame(start = 0, end = Inf, half.life = TRUE))
+  suppressMessages(o_nca <- pk.nca(o_data))
+  expect_equal(as.data.frame(o_nca, out_format = "wide")$half.life, 1.512942, tolerance = 0.00001)
+
+  # All FALSE exclude_hl is used
+  d_conc_false <- data.frame(conc = c(1, 0.6, 0.3, 0.25, 0.15, 0.1), time = 0:5, exclude_hl = FALSE)
+  o_conc_false <- PKNCAconc(d_conc_false, conc~time, exclude_half.life = "exclude_hl")
+  o_data_false <- PKNCAdata(o_conc_false, intervals = data.frame(start = 0, end = Inf, half.life = TRUE))
+  suppressWarnings(suppressMessages(o_nca_false <- pk.nca(o_data_false)))
+  d_nca_false <- as.data.frame(o_nca_false)
+  expect_equal(d_nca_false$PPORRES[d_nca_false$PPTESTCD %in% "half.life"], 1.512942, tolerance = 0.00001)
+})
+
 test_that("No interval requested (e.g. for placebo)", {
   tmpconc <- generate.conc(2, 1, 0:24)
   tmpdose <- generate.dose(tmpconc)

vignettes/v06-half-life-calculation.Rmd

@@ -81,6 +81,12 @@ as.data.frame(result_obj)
 
 # Manual Point Selection
 
+For both exclusion and inclusion methods below, the same `NA` handling rules
+apply on a per-interval basis. If all values are `NA`, then no inclusion or
+exclusion is applied (the interval is treated as-is, like the argument had not
+been given). If some values are `NA` for the interval, those are treated as
+`FALSE`.
+
 ## Exclusion of Specific Points with Curve Stripping
 
 In some cases, specific points will be known outliers, or there may be another reason to exclude specific points.  And, with those points excluded, the half-life should be calculated using the normal curve stripping methods described above.