This article describes creating an ADOE ADaM with Ophthalmology Exam Analysis data for ophthalmology endpoints. It is to be used in conjunction with the article on creating a BDS dataset from SDTM. As such, derivations and processes that are not specific to ADOE are absent, and the user is invited to consult the aforementioned article for guidance.
As the current release of {admiralophtha}
does not
contain any functionality specific to ADOE, this article only showcases
how to map parameters from OE in order to set up the basic structure of
ADOE. For the following steps, the user is invited to consult the
above-linked article on BDS datasets. This article will be updated for
future releases to showcase and explain any
{admiralophtha}
-specific functionality.
Note: All examples assume CDISC SDTM and/or ADaM format as input unless otherwise specified.
{admiralophtha}
suggests to populate ADOE with general
miscellaneous ophthalmology parameters. Any efficacy endpoint-related
parameters (eg. BCVA tests) should be placed in separate datasets (eg.
ADBCVA).
As with all BDS ADaM datasets, one should start from the OE SDTM,
where only the general ophthalmology records are of interest. For the
purposes of the next two sections, we shall be using the
{admiral}
OE and ADSL test data. We will also require a
lookup table for the mapping of parameter codes.
Note: to simulate an ophthalmology study, we add a
randomly generated STUDYEYE
variable to ADSL, but in
practice STUDYEYE
will already have been derived using
derive_var_studyeye()
.
data("oe_ophtha")
data("admiral_adsl")
# Add STUDYEYE to ADSL to simulate an ophtha dataset
adsl <- admiral_adsl %>%
as.data.frame() %>%
mutate(STUDYEYE = sample(c("LEFT", "RIGHT"), n(), replace = TRUE)) %>%
convert_blanks_to_na()
oe <- convert_blanks_to_na(oe_ophtha) %>%
ungroup()
# ---- Lookup table ----
# Assign PARAMCD, PARAM, and PARAMN
param_lookup <- tibble::tribble(
~OETESTCD, ~OECAT, ~OESCAT, ~AFEYE, ~PARAMCD, ~PARAM, ~PARAMN,
"CSUBTH", "OPHTHALMIC ASSESSMENTS", "SD-OCT CST SINGLE FORM", "Study Eye", "SCSUBTH", "Study Eye Center Subfield Thickness (um)", 1, # nolint
"CSUBTH", "OPHTHALMIC ASSESSMENTS", "SD-OCT CST SINGLE FORM", "Fellow Eye", "FCSUBTH", "Fellow Eye Center Subfield Thickness (um)", 2, # nolint
"DRSSR", "OPHTHALMIC ASSESSMENTS", "SD-OCT CST SINGLE FORM", "Study Eye", "SDRSSR", "Study Eye Diabetic Retinopathy Severity", 3, # nolint
"DRSSR", "OPHTHALMIC ASSESSMENTS", "SD-OCT CST SINGLE FORM", "Fellow Eye", "FDRSSR", "Fellow Eye Diabetic Retinopathy Severity", 4, # nolint
)
Following this setup, the programmer can start constructing ADOE. The
first step is to subset OE to only general ophthalmology parameters.
Then, one can merge the resulting dataset with ADSL. This is required
for two reasons: firstly, STUDYEYE
is crucial in the
mapping of AFEYE
and PARAMCD
’s. Secondly, the
treatment start date (TRTSDT
) is also a prerequisite for
the derivation of variables such as Analysis Day (ADY
).
adsl_vars <- exprs(TRTSDT, TRTEDT, TRT01A, TRT01P, STUDYEYE)
adoe <- oe %>%
filter(
OETESTCD %in% c("CSUBTH", "DRSSR")
) %>%
derive_vars_merged(
dataset_add = adsl,
new_vars = adsl_vars,
by_vars = get_admiral_option("subject_keys")
)
The next item of business is to derive AVAL
,
AVALU
, and DTYPE
. In this example, due to the
small number of parameters their derivation is trivial.
AFEYE
is also created in this step using the function
derive_var_afeye()
. To determine the affected eye, this
function compares OELAT
to the STUDYEYE
variable created from the previous step.
The user is invited to consult the article on creating a BDS dataset from SDTM to learn how to add standard BDS variables to ADOE.
ADaM | Sample Code |
---|---|
ADOE | ad_adoe.R |