R: transform

transform_blq {pharmr}

R Documentation

transform_blq

Description

Transform for BLQ data

Transform a given model, methods available are m1, m3, m4, m5, m6 and m7 (1). The blq information can come from the dataset, the lloq option or a combination. Both LLOQ and BLQ columns are supported. The table below explains which columns are used for the various cases:

+————-+————-+————+——————-+—————+——————-+ | lloq option | LLOQ column | BLQ column | Used as indicator | Used as level | Note | +=============+=============+============+===================+===============+===================+ | Available | NA | NA | DV < lloq | lloq | | +————-+————-+————+——————-+—————+——————-+ | NA | Available | NA | DV < LLOQ | LLOQ | | +————-+————-+————+——————-+—————+——————-+ | NA | NA | Available | BLQ | nothing | Only for M1 and M7| +————-+————-+————+——————-+—————+——————-+ | NA | NA | NA | NA | NA | No BLQ handling | +————-+————-+————+——————-+—————+——————-+ | NA | Available | Available | BLQ | LLOQ | DV column not used| +————-+————-+————+——————-+—————+——————-+ | Available | NA | Available | BLQ | lloq | | +————-+————-+————+——————-+—————+——————-+ | Available | Available | NA | DV < lloq | lloq | Column overridden | +————-+————-+————+——————-+—————+——————-+ | Available | Available | Available | DV < lloq | lloq | Columns overridden| +————-+————-+————+——————-+—————+——————-+

BLQ observations are defined as shown in the table above. If both a BLQ and an LLOQ column exist in the dataset and no lloq is specified then all dv values in rows with BLQ = 1 are counted as BLQ observations. If instead an lloq value is specified then all rows with dv values below the lloq value are counted as BLQ observations. If no lloq is specified and no BLQ column exists in the dataset then all rows with dv values below the value specified in the DV column are counted as BLQ observations.

M1 method: All BLQ observations are discarded. This may affect the size of the dataset. M3 method: Including the probability that the BLQ observations are below the LLOQ as part of the maximum likelihood estimation. For more details see :ref:⁠(1)<ref_article>⁠. This method modifies the Y statement of the model (see examples below). M4 method: Including the probability that the BLQ observations are below the LLOQ and positive as part of the maximum likelihood estimation. For more details see :ref:⁠(1)<ref_article>⁠. This method modifies the Y statement of the model (see examples below). M5 method: All BLQ observations are replaced by level/2, where level = lloq if lloq is specified. Else level = value specified in LLOQ column (see table above). This method may change entries in the dataset. M6 method: Every BLQ observation in a consecutive series of BLQ observations is discarded except for the first one. The remaining BLQ observations are replaced by level/2, where level = lloq if lloq is specified. Else level = value specified in LLOQ column (see table above). This method may change entries in the dataset as well as the size of the dataset. M7 method: All BLQ observations are replaced by 0. This method may change entries in the dataset.

Current limitations of the m3 and m4 method:

Does not support covariance between epsilons
Supports additive, proportional, combined, and power error model

_ref_article:

(1) Beal SL. Ways to fit a PK model with some data below the quantification limit. J Pharmacokinet Pharmacodyn. 2001 Oct;28(5):481-504. doi: 10.1023/a:1012299115260. Erratum in: J Pharmacokinet Pharmacodyn 2002 Jun;29(3):309. PMID: 11768292.

Usage

transform_blq(model, method = "m4", lloq = NULL)

Arguments

`model`	(Model) Pharmpy model
`method`	(str) Which BLQ method to use
`lloq`	(numeric (optional)) LLOQ limit to use, if NULL Pharmpy will use the BLQ/LLOQ column in the dataset

Value

(Model) Pharmpy model object

Examples

## Not run: 
model <- load_example_model("pheno")
model <- transform_blq(model, method='m4', lloq=0.1)
model$statements$find_assignment("Y")

## End(Not run)