ABE {replicateBE} | R Documentation |
Comparative BA-calculation for Average Bioequivalence
Description
This function performs the required calculations for the BE decision via conventional (unscaled) Average Bioequivalence based on ANOVA as recommended in the EMA’s guideline.
Usage
ABE(alpha = 0.05, path.in, path.out = tempdir(), file, set = "",
ext, na = ".", sep = ",", dec = ".", logtrans = TRUE,
print = TRUE, details = FALSE, verbose = FALSE, ask = FALSE,
data = NULL, theta1, theta2)
Arguments
alpha |
Type I Error (TIE) probability (nominal level of the test). Conventionally set to 0.05, resulting in a 100(1 – 2α) confidence interval. |
path.in |
Path to the data file for import. |
path.out |
Path to save the result file if |
file |
Name of the dataset for import (without extension). Must be a string (i.e., enclosed in single or double quotation marks). The name is case-sensitive. |
set |
Name of the sheet of an Excel-file (mandatory). Must be a string (i.e., enclosed in single or double quotation marks). The name is case-sensitive. |
ext |
File-extension enclosed in single or double quotation marks.
Acceptable are |
na |
Character string denoting missing values. Acceptable are |
sep |
Variable separator in the CSV-file. Acceptable are |
dec |
Decimal separator in the CSV-file. Acceptable are |
logtrans |
If |
print |
If |
details |
Defaults to |
verbose |
Defaults to |
ask |
Defaults to |
data |
Specification of one of the internal reference datasets ( |
theta1 |
Lower limit of the acceptance range. Defaults to |
theta2 |
Upper limit of the acceptance range. Defaults to |
Details
The model for the treatment comparison is
lm(log(PK) ~ sequence + subject%in%sequence + period + treatment, data = data)
where all effects are fixed.
Tested designs
4-period 2-sequence full replicates
TRTR | RTRT
TRRT | RTTR
TTRR | RRTT
2-period 4-sequence replicate
TR | RT | TT | RR
(Balaam’s design)4-period 4-sequence full replicates
TRTR | RTRT | TRRT | RTTR
TRRT | RTTR | TTRR | RRTT
3-period 2-sequence full replicates
TRT | RTR
TRR | RTT
3-period (partial) replicates
TRR | RTR | RRT
TRR | RTR
(extra-reference design)
Data structure
Columns must have the headers
subject
,period
,sequence
,treatment
,PK
, and/orlogPK
.
Any order of columns is acceptable.
Uppercase and mixed case headers will be internally converted to lowercase headers.-
subject
must be integer numbers or (any combination of) alphanumerics
[A-Z, a-z, -, _, #, 0-9]
-
period
must be integer numbers. -
sequence
must be contained in the tested designs (numbers or e.g.,ABAB
are not acceptable). The Test treatment must be coded
T
and the ReferenceR
.
-
Value
Prints results to a file if argument print = TRUE
(default).
If argument print = FALSE
, returns a data frame with the elements:
Design | e.g., TRTR|RTRT |
Method | ABE |
n | total number of subjects |
nTT | number of subjects with two treatments of T (full replicates only) |
nRR | number of subjects with two treatments of R |
Sub/seq | number of subjects per sequence |
Miss/seq | if the design is unbalanced, number of missings per sequence |
Miss/per | if the design is incomplete, number of missings per period |
alpha | nominal level of the test |
DF | degrees of freedom of the treatment comparison |
CVwT(%) | intra-subject coefficient of variation of the test treatment (full replicates only) |
CVwR(%) | intra-subject coefficient of variation of the reference treatment |
BE.lo(%) | lower bioequivalence limit (e.g., 80 ) |
BE.hi(%) | upper bioequivalence limit (e.g., 125 ) |
CI.lo(%) | lower confidence limit of the treatment comparison |
CI.hi(%) | upper confidence limit of the treatment comparison |
PE(%) | point estimate of the treatment comparison (aka GMR) |
BE | assessment whether the 100(1 – 2α) CI lies entirely within the acceptance range (pass|fail )
|
Warning
Files may contain a commentary header. If reading from a CSV-file,
each line of the commentary header must start with "# "
(hashmark space = ASCII 35 ASCII 32
). If reading from an Excel-file
all lines preceding the column headers are treated as a comment.
Clarification
The ‘ASCII line chart’ in the result file gives the confidence limits with filled black squares and the point estimate as a white rhombus. If a confidence limit exceeds the drawing range, it is shown as a triangle. The BE limits and 100% are given with single vertical lines. The ‘resolution’ is approximatelly 0.5% and therefore, not all symbols might be shown. The CI and PE take presedence over the limits.
Disclaimer
Program offered for Use without any Guarantees and Absolutely No Warranty. No Liability is accepted for any Loss and Risk to Public Health Resulting from Use of this R-Code.
Note
The EMA’s model assumes equal [sic!] intra-subject
variances of test and reference (like in 2×2×2 trials) –
even if proven false in one of the full replicate designs (were both
CVwT and
CVwR can be estimated).
Hence, amongst biostatisticians it is called the ‘crippled model’
because the replicative nature of the study is ignored.
Conventional unscaled ABE has to be employed for
Cmax (if widening of the
acceptance range is clinically not justifiable),
AUC0–t,
AUC0–72 (immediate
release products) and
Cmax,ss,
Cτ,ss,
partialAUC (if widening
of the acceptance range is clinically not justifiable), and
AUC0–t,
AUC0–∞,
AUC0–τ
(modified release products).
Author(s)
Helmut Schütz
References
European Medicines Agency, Committee for Medicinal Products for Human Use. Guideline on the Investigation of Bioequivalence. CPMP/EWP/QWP/1401/98 Rev. 1/ Corr **. London. 20 January 2010. online
European Medicines Agency, Committee for Medicinal Products for Human Use. Guideline on the pharmacokinetic and clinical evaluation of modified release dosage forms. EMA/CPMP/EWP/280/96 Corr1. London. 20 November 2014. online
See Also
method.A | evaluation for ABEL by a fixed effects model (ANOVA) |
method.B | evaluation for ABEL by a linear mixed effects model |
Examples
# Importing from a CSV-file, using most of the defaults: variable
# separator comma, decimal separator period, print to file.
# Note: You must adapt the path-variables. The example reads from
# the data provided by the library. Write-permissions must be granted
# for 'path.out' in order to save the result file. Here the deafault
# (R's temporary folder) is used. If you don't know where it is,
# type tempdir() in the console.
path.in <- paste0(find.package("replicateBE"), "/extdata/")
ABE(path.in = path.in, file = "DS", set = "02", ext = "csv")
# Should result in:
# BE-limits : 80.00% ... 125.00%
# Confidence interval: 97.32% ... 107.46% pass
# Point estimate : 102.26%
# Generate the data.frame of results (7-digits precision) and show
# in the console. Use an internal dataset.
x <- ABE(details = TRUE, print = FALSE, data = rds02)
print(x, row.names = FALSE)
# Assuming a NTID and assess BE with narrower limits for one
# of the internal datasets.
ABE(data = rds02, theta1 = 0.90)
# Should result in:
# BE-limits : 90.00% ... 111.11%
# Confidence interval: 97.32% ... 107.46% pass
# Point estimate : 102.26%