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CDISC submission standard
•
CDISC SDTM
unfolding the core model that is the basis
both for the specialised dataset templates
(SDTM domains) optimised for medical
reviewers
•
CDISC Define.xml
metadata describing the data exchange
structures (domains)
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Background: CDISC SDTM’s fundamental
model for organizing clinical data
Observation
Generic structure
•Unique identifiers
•Topic variable or parameter
•Timing Variables
•Qualifiers.
Interventions
Findings
Events
General classes
Subject
CM
EX
EG
IE
LB
PE
AE
DS
SDTM Domains
(dataset structures)
…
The patient/subject focused information model of the clinical ‘reality’ (general classes of
observations on subjects: interventions, findings, events). This model has been developed by
CDISC/SDS team and exist today only as a text description.
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* New in Version 3
Interventions
Events
ConMeds
Exposure AE
MedHist
Disposition
Findings
ECGPhysExam
Labs
Vitals
Demog
Other
Subj Char*
Subst Use*
Incl Excl*
RELATES*
SUPPQUAL*
Study Sum*
Study Design*
QS*, MB*
Comments*
CP*, DV*
CDISC SDTM’s Domains
From CDISC SDTM Overview & Impact to AZ, 2004, by Dan Godoy, presented
at the first CDISC/SDM meeting 20 October 2004
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Basic Concepts in CDISC SDTM
Observations and Variables
•
The SDTM provides a general framework for describing the
organization of information collected during human and animal
studies.
•
The model is built around the concept of observations, which
consist of discrete pieces of information collected during a
study. Observations normally correspond to rows in a dataset.
•
Each observation can be described by a series of named
variables. Each variable, which normally corresponds to a
column in a dataset, can be classified according to its Role.
•
Observations are reported in a series of domains, usually
corresponding to data that were collected together. A domain is
defined as a collection of observations with a topic-specific
commonality about a subject.
From the Study Data Tabulation Model document
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Basic Concepts in CDISC/SDTM
Variable Roles
•
A Role determines the type of information conveyed by the variable
about each distinct observation and how it can be used.
–
A common set of Identifier variables, which identify the study, the subject
(individual human or animal) involved in the study, the domain, and the
sequence number of the record.
–
Topic variables, which specify the focus of the observation (such as the
name of a lab test), and vary according to the type of observation.
–
A common set of Timing variables, which describe the timing of an
observation (such as start date and end date).
–
Qualifier variables, which include additional illustrative text, or numeric
values that describe the results or additional traits of the observation (such
as units or descriptive adjectives). The list of Qualifier variables included
with a domain will vary considerably depending on the type of observation
and the specific domain
–
Rule variables, which express an algorithm or executable method to define
start, end, or looping conditions in the Trial Design model.
From the Study Data Tabulation Model document
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