Download Desing of the Clinical Data Portion of a CANDA to Facilitate Review by CDER

Design of the Clinical Data Portion of a CANDA to Facilitate Review by CDER
Kay Obenshain, SAS Institute, Inc., Cary, NC
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Figure 1. Main Library window of SASIPH-Clinical® Software
support. Personnel from the PTC and other groups
at SAS Institute graciously participated in the design
of the current CANDA.
This paper presents the design of the clinical data
portion of a CANDA that was submitted to the
Division of Metabolic and Endocrine Drug Products
at the FDA's Center for Drug Evaluation and
Research (CDER) in 1995. SAS/PH·Clinical®
software Version 2.0 (PHC) was customized to
provide an interface to data presented in the
integrated summary of efficacy and safety (ISElISS)
sections of the New Drug Application (NDA). The
focus of this paper is on the technical aspects of
designing the PHC portion of the CANDA, referred
to here as the current CANDA.
PHC is a graphical user interface, so what is there to
design? PHC accepts multiple types of data
structures to accommodate the needs of a variety of
users. In order to allow as comprehensive a range
of data structures as possible, PHC requires data to
be "defined" to the product. PHC provides tools to
define data and to build objects for use in data
exploration. Thus, PHC can be customized
specifically for individual databases and users. The
current CANDA was designed by customizing PHC
for the ISElISS database.
INTRODUCTION
SAS/PH-Cliliical (PHC) provides tools for interactive
review of clinical trials data on a desktop computer.
PHC can be used as an in-house drug development
tool as well as for CANDA submissions.
Readers familiar with PHC know that there are many
ways to use the product. This paper presents the
use of PHC as an interface to one sponsor's data for
a single CANDA submission. It mayor may not be
relevant to another sponsor or different data from
the same sponsor.
PHC is a product of the PharmaTechnology Center
at SAS Institute (PTC). When a customer licenses a
PTC product, it is the beginning of a partnership
between the PTC and the customer. Working with
existing groups at SAS Institute, PTC offers support
services such as consulting, training, and user
Rather than present confidential data, examples in
this paper show fictitious data, protocol and variable
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nan:'es, e~c. The purpose of this paper is to present
basl~ design elements, as clearly and concisely as
possible. Details that are important but do not playa
key role in the current CANDA design are simplified
or, in the case of functions and dictionaries, not
addressed.
description of data included in PH-Studies appears
in the "Data Files" section of this paper.
Advantages of this particular arrangement of data
include more rapid data access and increased
flexibility in data structure.
OBJECnVE
Customize SAS/PH-Clinical to allow a user to:
•
view all data presented in ISElISS tables and
listings, in chronological order
•
select any patient and follow his data through
several studies in a single view
•
subset ISElISS data to arrive at initial data of
interest
•
reproduce descriptive statistics presented in
ISElISS tables
Expressions
An expression is SAS code, represented by an
object that can be "opened" to subset data. The SAS
code is transparent to the user. As an example, the
Expression "Intent to Treat Population" consists of
the code: "ITTPOP 1". The user only sees the
name of the expression, "Intent to Treat Population."
When "Intent to Treat Population" is opened, PHC
displays data only from patients in the intent-to-treat
population.
=
Expressions were created and then saved in folders
(described below) according to the expression
category. Categories of Expressions include
Protocols, Study Groupings, Population Indicators,
Treatment Groupings, Discontinuation (Reason for),
and Adverse Event.
METHODS·
Designing the current CANDA involved:
•
building objects for data exploration
•
providing metadata (data about the clinical data)
to PHC
METHODS: BUILDING OBJECTS
Objects called studies, expressions, variable groups,
and folders were built by invoking PHC facilities to
"edit" each object Detailed descriptions of these
objects appear below.
The predefined expressions consist of SAS
operators and operands that identify individual
patients. A user can open a predefined expression
to subset ISEIISS data and arrive at particular
patients of interest.
Objects called PH-Templates are supplied as part of
PHC. A PH-Template is a mechanism for a
non-programmer to create a generic report by
running SAS® code. No PH-Template was altered in
any way for the current CANDA, and all
PH-Templates supplied with PHC were included in
the CANDA submission.
An expression may be applied "By Patient" or
"By RoW". Each predefined expression in the
current CANDA should be applied "By Patient". An
example of an expression to apply "By Row" would
consist of SAS code to identify assessments
collected multiple times per patient.
Variable Groups
A variable group was created and associated with
each PH-Study. The variable group for the study
Patient Data has three main branches: Patient
Background & Status, Efficacy, and Safety. Each
main branch has at least one additional level of
sub-branches. The Patient Background & Status
branch contains the sub-branches Population,
Treatment/Exposure, Disposition, Demographics,
Medical Conditions, and Concomitant Medications.
The Safety branch contains sub-branches Adverse
Events, Laboratory Results, and Vital Signs.
PH-Studies
A "study" in PHC is a set of data files, which mayor
may not correspond to a single clinical
study/protocol/trial. In this paper, a PHC "study" is
referred to as a PH-Study to distinguish it from a
clinical study .
In the current CANDA. each PH-Study contains data
from all clinical studies summarized in ISElISS.
Data were arranged in four PH-Studies: Patient
Data, Blood Chemistry Data, Hematology Data, and
Urinalysis Data. Only one PH-Study should be
opened at a time in the current CANDA
Folders
Folders were created in the Main Library window for
PH-Studies, expressions, and variable groups.
Sub-folders were created within folders, e.g., the
folder containing predefined expressions contained
one folder for each category of predefined
expressions (Figure 1).
Patient Data contains all ISElISS data, with a caveat
on lab data. Only main laboratory test results, in
standard units are in Patient Data. PH-Studies
Blood Chemistry Data, Hematology Data, and
Urinalysis Data contain complete laboratory data,
with results in "raw" and standard units. A detailed
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METHODS: PROVIDING METADATA
Keys are employed to join data from different files.
An integrated database containing data presented in
As a simple example, labs and vital signs were
the ISEIISS consisted of SAS data sets. The
database was "defined" to PHC by providing data
about the data, or metadata, which determines how
PHC displays, joins, and partitions data. Definition
of the ISElISS database took place in the Study
Definition environment of PHC. Entities called data
files, keys, and variables were defined'to PHC, and
attributes were aSSigned to each entity.
collected on specific visit days, and the variables
PATIENT and VISIT exist in lab and vital sign data
sets. The keys PATIENT and VISIT can link data
from these two data sets so that labs and vital signs
can be merged and displayed side by side in a data
table by PATIENT and VISIT as if they were from the
same data file ..
Keys may also determine the level at which data
vary within a data file. As an example, in Patient
Data, in a laboratory data set, the variable DTEST
(name of lab test) was defined as a key because lab
data vary on the DTEST level within VISIT. When a
user requests a lab data table, lab test results are
automatically listed by PATIENT, VISIT, and DTEST.
Data Files
Data files defined to PHC are the SAS data sets in
the ISElISS database. The process of data
definition does not alter the data sets, and a user
cannot alter data files outside the Study Definition
environment. Each data file was assigned a function
and one or more keys.
In Patient Data, keys to joih files are PATIENT and
VISIT; and keys to determine level vary with each
file. In the lab studies, the key to join files is
PATIENT; and keys that determine level for lab files
are DTEST and VISIT. .
All data sets in the integrated database were defined
to the PH-Study Patient Data, with a caveat on lab
data described below. Some of the data sets
defined to Patient Data are also defined to the three
separate lab PH-Studies (Blood Chemistry,
Hematology, and Urinalysis). Data sets defined to
all four PH-Studies are those with patient
background & status information.
Additional functionality of keys, beyond PHC
Certain keys in the current CANDA have an
additional function that is not required by PHC, but is
an important element of the design. The keys
PATIENT and VISIT serve as protocol identifiers, as
described below.
Rather than have all lab data in one huge SAS data
set, it was decided to slice the data set both
hOrizontally and vertically before defining lab data to
PHC. Decreasing the size of data files horizontally
and/or vertically is a way to maximize PHC
performance.
In addition to its role as a PH-Study key, PATIENT
provides protocol information about each patient.
A patient could participate in a maximum of three
protocols, one of each type. The three protocol types
are short-term controlled, long-term controlled, and
long-term open label. Patients could enroll in one
(and only one) protocol of each type. A different
patient identifier was assigned in each protocol.
Thus, patients could have up to three different
patient identifiers during their progreSSion through
protocols.
Organization of data within PH-StUdies
Patient Data contains a hematology file, a blood
chemistry file, and a urinalysis file. Blood Chemistry
contains a blood chemistry file, Hematology contains
a hematology file, and Urinalysis contains a
urinalysis file. Lab files in Patient Data are a subset
of variables in the corresponding file in lab
PH-StUdies.
The PATIENT key consists of three parts:
• single letter code for first protocol entered
•
patient # in first protocol
•
single letter code for extension protocol(s)
A decode table was defined to decipher first and
extension protocol numbers. The decode table is
simply a hardcopy table, separate from PHC.
Lab data sets defined to Patient Data have the same
number of observations as those in the individual lab
PH-Studies, but Patient Data contains only the main
laboratory test results, in standard units. The lab
PH-Studies contain all lab data that is in Patient
Data, but also contain additional flag variables and
"raw" lab data.
In addition to its role as a PHC key, VISIT provides
protocol information on the VISIT level. A decode
table defines the type of study associated with
specific ranges of VISIT values. As an example,
VISIT values in the 100's pertain to short-term
controlled studies. The decode table also includes
values for special visits such as Screening and
Keys
Keys define structure in PHC
Keys are variables in the SAS data set that define
the structure of a data file in a PH-Study. Keys were
selected in order to structure the data so that it
makes sense clinically.
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As an example, the vital signs data set, VS, contains
the "By Visit" identifier variables SC_ VS, LC_ VS,
and LO_VS. Vital sign data for patient A21 C from
visit 101 were included in analyses for protocol
66-01 only, while VS data from visit 301 were
included in analyses for protocols 66-01, 66-11, and
66-31 .
Discontinuation. The values of VISIT are assigned
so that they increase as a patient progresses
through protocols.
Variables
Attributes
. Variables were assigned attributes that determine if
they are available to a user, how they are displayed,
and how they can be used. All variables in the
ISElISS were "committed" to PHC and are available
for a user.
PATIENT
VISIT
A21C
A21C
A21C
101
201
301
_Protocol
SC VS
66-01
66-01
66-01
identifier variables_
LC VS
LO VS
66-11
66-11
66-31
The attribute "format" determines how a variable is
displayed, and "analysis type" determines how
variables are used. As an example of the latter,
ITTPOP is a numeric variable that flags patients in
the intent-ta-treat population. ITTPOP was assigned
"nominal" so that when a user
Analysis Type
requests summary statistics for ITTPOP, the only
statistic returned is "n". It would not make sense to
display mean or median ITTPOP values. ITTPOP
cannot be used for descriptive or inferential
statistics.
The "By Visit" protocol identifier variables are used
as Grouping Variables in PHC Summary Statistics,
which is analogous to "by vars" in PROC MEANS.
They are necessary to recreate cells in ISElISS
tables.
Additional functionality for variables
Certain variables in the current CANDA have an
additional function that is not required by PHC, but is
an important element of the design. Special
identifier variables were created before the data sets
were defined to PHC. These variables identify
patient number and protocol number for each type of
protocol a patient entered, and identify protocol
number(s) associated with individual observations.
All data were made available for viewing by
committing all data sets and variables. Data with
multiple records per patient are listed in ascending
order by the VISIT key, which was defired to ascend
across protocols in chronological order.
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RESULTS
Functional requirements were achieved as follows.
Requirement: view all data presented in ISElISS
tables and listings, in chronological order
Requirement: select any patient and follow his data
through several studies in a single viewing.
Pooling data from multiple protocols into Cine
PH-Study allows the user to view all the data for one
patient in the PHC Patient Profile facility.
A naming convention was adopted to identify the
three types of protocols: SC, LC, and LO represent
short-term controlled, long-term controlled, and longterm open-label studies, respectively.
Requirement: subset ISElISS data to arrive at initial
data of interest
Variables STUDY_SC, STUDY_LC, and STUDY_LO
identify the protocol a patient participated in, where
SC, LC, and LO represent the three types of
protocols. Similar variables PATID_SC, PATID_LC
and PATID_LO identify the patient number in each
type of protocol. These protocol and patient
identifier variables are located in a data set with one
record per patient, and can be used to create
expressions to apply "By Patient". Thus, they are
referred to as "By Patient" variables.
Predefined expressions can be 'opened' in PHC to
subset data. Creation of "By Patient" identifier
variables facilitated building expressions.
Requirement: reproduce descriptive statistics
presented in ISElISS tables
Cells in ISElISS tables can be reproduced by
opening expressions to arrive at the patient
population of interest, and then requesting PHC
Summary Statistics with multiple Grouping
Variables. Creation of "By Visit" identifier variables
to use as Grouping Variables facilitated use of PHC
Summary Statistics.
Protocol identifier variables were defined on a
visit-by-visit basis for each data set that contains
multiple records per patient. These variables are
referred to as "By Visit" identifier variables, to
distinguish them from the "By Patient" identifier
variables described in the preceding paragraph.
These variables identify which of the three types of
protocols data were analyzed in.
CONCLUSION
The CANDA was installed at the FDA and a training
session was held for reviewers. A guidebook with
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been 'uneventful' in that there have been no
complaints from the FDA as this paper goes to
press.
information specific to the current CANDA design
was written. Copies of the CANPA guidebook and
PHC documentation provided by SAS Institute were
presented to reviewers.
SAS and SAS/PH-Clinical are registered trademarks of
SAS Institute Inc. in the USA and other countries. ® indicates
USA reg istration.
Any reader who has spent time perusing medical
records knows that an 'uneventful' record is the kind
he would want to have. The current CANDA has
Other brand and product names are registered trademarks or
trademarks of their respective companies.
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