This document provides an overview of CDISC (Clinical Data Interchange Standards Consortium) and SDTM (Standard Data Tabulation Model). It defines these standards, their purpose in establishing common data formats for clinical research, and key concepts in SDTM like domains, variables, qualifiers and time standards. The document also provides examples of how SDTM organizes data from a clinical trial, including adverse events, trial design, and standards for related records.

1. CDISC, SDTM
guidelines.
Genelife Clinical Research Pvt. Ltd.
By,
Ankita Vaidya,
Biostatistician.

2. Definitions
• CDISC : Clinical Data Interchange Standard Consortium.
• SDTM : Standard Data Tabulation Model.

3. CDISC- Introduction
• CDISC is a global, open, multi-disciplinary, non-profit organization that has established
standards to support the acquisition, exchange, submission and archive of clinical
research data and metadata.
• The CDISC mission is to develop and support global, platform-independent data
standards that enable information system interoperability to improve medical research
and related areas of health-care.
• CDISC standards are vendor-neutral, platform-independent and freely available via the
CDISC website.
• Leads the development of standards that improve efficiency while supporting the
scientific nature of clinical research.

4. SDTM- Introduction
• SDTM defines a standard structure for study data tabulations (datasets) that are to
be submitted as part of a product application to a regulatory authority such as the
Drug Controller General Of India (DCGI) or United States Food and Drug
Administration (USFDA)
• SDTM provides the general framework for describing the organization of
information collected during human and animal studies and submitted to regulatory
authorities.

5. Overview of CDISC standards
Protocol
CRF Operational database
PRM CDASH ODM
Tabulation datasetsAnalysis datasetsResults
SDTMADaM

6. Concepts and Terms
• SDTM model is built around the concept of observations, which consist of
discrete pieces of Information collected during a study.
• Observations are normally corresponds to a row in a dataset. A collection of
observations on a particular topic is considered as domain.
• Each observation can be described by a series of named variable. Variable can
be classified according to its role
• A role describe the type of Information conveyed by the variable.
• SDTMIG describes the general conceptual model for preparing clinical study
data that is submitted to regulatory authorities.

7. • SDTM Variable Classification:
1. Identifier : These are the variable which identifies the study, subject
involved, domain & sequence number.
2. Topic :This specifies the focus of the observations.
3. Timing : Variables which describe the timing of an observation.
4. Qualifier : Contains additional text, values or results which helps
describes the observation.
5. Rule : This explains the calculation involved to derived date i.e.
times or visits.
Classification of SDTM Variables.

8. • Qualifier is further categorized as :
1. Grouping Qualifier : are used to group together a collection of observations
within same domain. Ex. LABCAT
2. Result Qualifier :describe the specific results associated with the topic variable.
They answer the question raised by the topic variable. Results qualifiers are
ORRES, STRESC & STRESN.
3. Synonym Qualifiers : specify an alternative name for a particular variable in an
observation. E.g. MODIFY & DECOD, which are equivalent terms for a TRT or
term topic variable.
4. Record Qualifier : define additional attributes of the observation record as a
whole for e.g. SAE variables in the AE domain. AGE,SEX in DM domain.
5. Variable Qualifier : are used to further modify or describe a specific variable
within an observation. E.g. DOSU which is variable qualifier of Dose.
Classification of qualifier variables

9. • “Suppose subject 01001 had mild nausea starting on study day 6” is an
observation belonging to the Adverse Events domain in clinical trial.
• The Topic Variable value is the term of adverse event, “Nausea”
• The Identifier Variable is the subject identifier, “01001”
• The Timing variable is the study day of the start of the event, which
captures the information, “Starting on study day 6”.
• The Record Qualifier is severity, the value for which is “Mild”.
Example

10. • Observations about study subjects are normally collected for all subjects
in a series of domain.
• Each domain dataset is distinguished by a unique two character code.
• Which is stored in the SDTM variable named DOMAIN, is used in four
ways : as the dataset name, the value of the domain variable in that
dataset, as a prefix for most variables in dataset, as a value in
RDOMAIN.
• Each dataset is described by metadata. The metadata are defined in data
definition document named “define”.
Domain

11. • The variable name (limited to 8 character).
• A descriptive variable label, limited up to 40 characters, which should be
unique for each variable in the dataset.
• The data type i.e. character or numeric.
• The set of controlled terminology for the value or the presentation format
of the variable.
• The origin or source of each variable.
• The role of the variable (Identifier, Topic, Timing, Qualifiers).
• Comments or other relevant information about the data.
Submission metadata model uses seven distinct
metadata attributes.

12. • Datasets containing observations are classified into 3 classes :
• Intervention: captures investigational, therapeutic treatments that are
administered to the subject (with some actual or expected physiological
effect) either as specified by the study protocol, coincident with the study
assessment period.(e.g. Concomitant medications), or other substances self
administer by the subject (e.g. alcohol, tobacco).
• Events: Captures planned protocol milestones such as randomization &
study completion & occurrences or incidents independent of planned study
evaluations occurring during a clinical trial.(e.g. AE, MH).
• Findings: Captures the observations resulting from planned evaluations to
address specific test such as laboratory tests, ECG testing.
Observation Class

13. Special purpose datasets represents additional important information.
• Demographics is the parent domain for all other observations for
subjects & should be identified with the domain code “DM”.
• Comments are collected during the conduct of study. These are
normally supplied by Principal Investigator. Collected comments
should be submitted in a single comments domain “CO”.
• The Subjects Elements Table describes the actual order of the element
that were traversed by the subject with the start date/time & end
date/time for each element.
• The Subjects Visits Table describes the actual start date/time &end
date/time for each visit of each individual subject.
Special Purpose Domain

14. • The design of a clinical trial is a plan for what assessment will be done
to the subjects & what data will be collected during the trial.
• These datasets fall under this model :
• Trial Arms (TA)
• Trial Element (TE)
• Trial Visits (TV) VISITNUM VISIT VISITDY
• Trial Inclusion/Exclusion Criteria (TI)
• Trial Summary Information (TS)
Trial Design Model.

15. • Trial Arm has the structure of one record per planned element per
arm.
• Arms describes sequence of elements in each Epoch for each arm &
thus describes the complete sequence of elements in each arm.
Here the no. of Arms is two.
Trial Arms (TA)
Screen Run-in
Drug A
Drug B

16. • ARMCD & ARM
• ARM Code it’s a required variable & its value must be in accordance
with value of ARMCD in Trial Arm (TA).
• ARMCD defines the coded value & the structure of the drug
assignment.
• For any patient which is screen failure then ARMCD is assigned as
“SCRNFAIL” & arm value is “Screen Failure”.
Continued…

17. • Planned Order of Elements with Arm:
• This represents planned order of an element in an Arm.
• Its value will not be populated for the element that are not planned for the
Arm for which subject was assigned. Thus for any value of ETCD as
“UNPLAN”, TAETORD should be blank.
• ETCD :is the code value assigned to the variable element.
• In any case if value of element entered is entirely different from the
planned element as specified in TE then this value must be replace with
text value “UNPLAN”.
TAETORD

18. • This consist the description of the element, which usually indicates the
treatment assigned during an element.
• It involves administering a planned intervention, which may be
treatment or no treatment, during a period of time.
• Elements for which the planned intervention is “no treatment” would
include elements for screening, wash-out, follow-up.
Trial Element (TE)

19. • This is the expected variable. This describes the outcome of a branch
decision point in the trial design. Branch decision point take place
between epochs & is associated with the element. “TABRANCH”
• TRANSITION Rule : this is the expected variable. If the design allow
any subject to move to other element than the next one in the
sequence, then that condition which allows the subject to do so,
populates the value for variable “TATRANS.”
Branch & Transition

20. • TESTRL (Start): Elements that involves the treatment is usually the
start of treatment.
• TEENRL (End): This rule describes how any subject moved out or
completed the element it was assigned to. End rule must be describe
referring to the Trial Element.
• TEDUR (Trial Duration) : must be populated for every record where
TEENRL is populated. Must be presented in ISO 8601 format.
• E.g. P2W is equivalent to TEENRL of 2 weeks after start of element.
Rule for start & end of element

21. • VISITNUM : Numerical sequence provided to the visit according to
protocol.
• VIST : Textual presentation of the numeric visit.
• E.g. VISITNUM is 1 then VISIT is assigned as SCREENING.
• VISITDY :Visit planned by study protocol to follow.
• E.g. planned study day structure for any study is 1,2,3,4 which
explains treatment period start from the visit 1 and goes till 4.
• TVSTRL : Trial Visit Start Rule describing when the visit starts.
• TVENRL : Trial Visit End Rule describing the end of the visit.
Trial Visit

22. • As per CDISC guidelines all timing variable must be presented in ISO
8601 format.
• ISO 8601 Format: as per FDA guidelines all the dates must follow the
following format.
• YYYY-MM-DDThh:mm:ss
Date & Time Variable

23. • A relationship between group of records for a given subjects within the
same datasets.
• A relationship between independent records for a subjects, such as a
concomitant medications taken to treatment an adverse event.
• A dependent relationship between a comment in the comments domain &
parent record in other datasets. Such as a comment recorded in
association with an adverse event.
• Related subjects datasets some studies include subjects who are related
to each other & in some cases it is important to record those
relationships.
Related Record Datasets (RELREC)

24. Conclusions.
• Since becoming the recommended standard for the submission of
clinical trial data to DCGI, FDA in marketing applications, the
SDTM has begun to be used by sponsors for their upstream
processing to support clinical study report.
• As data is increasingly delivered to the FDA in CDISC standards, the
FDA will be able to more efficiently review individual submissions.

25. Thank You
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