BLQ handling drop + imputation (start_conc0) - Error: Requesting an AUC range...

[Gero1999]

Hello PKNCA team! I was wondering if this behavior is the expected by the App. I am doing a start_conc0 imputation in my extravascular study, but if simultaneously I decide to drop all my BLQ values then the App won't run. It seems like the imputed concentration is also being droped:

library(PKNCA)
conc_data <- data.frame(
    conc = c(1, 2.5, 2, 1, 0.7, 0.5, 0),
    time = 1:7,
    subject = 1
)

dose_data <- data.frame(
    dose = 100,
    time = 0,
    subject = 1,
    route = "Extravascular"
)

# Create PKNCA objects without BLQ cleaning
o_conc <- PKNCAconc(conc_data, conc ~ time | subject)
o_dose <- PKNCAdose(dose_data, dose ~ time | subject, route = "route")
o_data <- PKNCAdata(o_conc, o_dose)
o_data$intervals$impute <- "start_conc0"
o_nca <- pk.nca(o_data)
o_nca$result

# Create PKNCA objects with BLQ cleaning
o_data2 <- o_data
o_data2$options$conc.blq <- list(
    first = "drop",
    middle = "drop",
    last = "drop"
)
# Won't run: Requesting an AUC range starting (0) before the first measurement
# BLQ cleaning seems to happen after start_impute, so it doesn't work!
o_nca2 <- pk.nca(o_data2)

Do we instead want that the start imputation occurs after the BLQ cleaning?

[billdenney]

This is intended behavior, but I understand the confusion. I think that the right fix here is a documentation update to clarify the order of things. My rationale is: If you say to drop all BLQ results, then why would you try to impute a BLQ result?

Do you have a use case where you want to drop all BLQ results but you also want to impute a BLQ value or is this (useful) testing for edge cases?

[Gero1999]

We are using start_conc0 but not with the intention of imputing BLQ values but a 0 value for extravascular / infusion studies. I know we have the auc.int alternatives, but using the impute column seems to be working well for us to do special imputations for all the particular cases (EV / infusion, normal IV bolus, non-monodecaying IV bolus, multiple dose with predose...)

I personally see BLQ handling more useful as a pre-step. It is a general rule that is expected to affect all intervals, while particular impute actions are individually specified.

[Gero1999]

An issue was opened to discuss further this (#456) and a solution not needing package changes was found here.

What we basically do is to define a impute method function that does the BLQ handling. Then we can choose on which intervals and at which moment the imputation is applied