1 THEME DATA SHARING WP CDISC Presented by Mary Thiongo & - - PowerPoint PPT Presentation

THEME DATA SHARING

WP CDISC

Presented by Mary Thiongo & Harry van Loen 4th ADMIT workshop, ITM Belgium, 30 NOV-4 DEC 2015

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Contents

 CDISC

Introduction

 SDTM

1. Introduction 2. Background 3. Objective 4. SDTM concept

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Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015

Contents

 CDASH

1. Introduction 2. Value of CDASH 3. CDASH Model 4. CDASH Metadata Tables 5. CDASH Implementation

 ADMIT – CDISC - considerations

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Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015

CDISC

 CDISC

 Clinical Data Interchange Standards Consortium  Introductional VIDEO  WEBSITE: http://www.cdisc.org

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Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015

SDTM

• 1. Introduction

Study Data Tabulation Model :  organize data

 facilitate overall data management

 improve regulatory review and approval

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Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015

SDTM

• 2. Background

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Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015

1999 2001 2002 2004 Submission Data Model (SDM) focus only ‘safety’ Submission Data Domain Model Study Data submission Model v1.0 (SDTM)  focus ‘all study’ 2015 SDTM v 1.4 FDA recognizes SDTM

SDTM

• 3. Objective

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Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015

Data submission SDTM datasets

and

SDTM metadata

SDTM

• 4. SDTM Concept

4.1 SDTM documentation:

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Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015

Study Tabulation Data Model SDTM Implementation Guide Controlled Terminology Case Report Tabulation Data Definition Specification (‘define.’)

SDTM dataset(s) SDTM metadata

SDTM

4.2 SDTM basics :

Observation(s)  correspond to row in dataset

(~record (s))

Variable(s)

 correspond to column in dataset

Domain/Class  group of related observations

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Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015

SDTM

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Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015

 Example data set (AE):

Domain: Adverse Events (AE) Variables Observation (s)

SDTM

 4.2.1 Domains & Classes  listed in SDTM IG doc v3.1.2 p. 13

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Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015 INTER VENTIONS CLASS EVENTS CLASS

Adverse Events AE Medical History MH Demo graphics DM

FINDINGS CLASS

Vital Signs VS Phyical Exam PE Con Med CM Substance use SU

GENERAL OBSERVATION CLASSES SPECIAL PURPOSE DOMAINS

Trial Summary TS

TRIAL DESIGN DOMAINS

Trial Visits TV Related Records RELREC

RELATIONSHIP

Supplemental qualifierss SUPP- - Subject Visits SV

. . . . . . . . . . . . . . .

two character domain code: AE, DM…

SDTM

 4.2.1 Domains & Classes  listed in SDTM IG doc v3.1.2 p. 13

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Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015 INTER VENTIONS CLASS EVENTS CLASS

Adverse Events AE Medical History MH Demo graphics DM

FINDINGS CLASS

Vital Signs VS Phyical Exam PE Con Med CM Substance use SU

GENERAL OBSERVATION CLASSES SPECIAL PURPOSE DOMAINS

Trial Summary TS

TRIAL DESIGN DOMAINS

Trial Visits TV Related Records RELREC

RELATIONSHIP

Supplemental qualifierss SUPP- - Subject Visits SV

. . . . . . . . . . . . . . .

two character domain code: AE, DM…

SDTM

 4.2.1 Domains & Classes  listed in SDTM IG doc v3.1.2 p. 13

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Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015 INTER VENTIONS CLASS

Con Med CM Substance use SU

. . .

two character domain code: AE, DM…

• 1. Concomitant medication- CM  Medication prior and during

study

• 2. Substance Use- SU  Substances (alcohol, coffee, smoking..)

affecting efficay & safety

• 3. Exposure-EX  Study treatment (e.g. placebo,

investigational products  Following domains/SDTM datasets:

SDTM

 4.2.1 Domains & Classes  listed in SDTM IG doc v3.1.2 p. 13

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Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015 INTER VENTIONS CLASS EVENTS CLASS

Adverse Events AE Medical History MH Demo graphics DM

FINDINGS CLASS

Vital Signs VS Phyical Exam PE Con Med CM Substance use SU

GENERAL OBSERVATION CLASSES SPECIAL PURPOSE DOMAINS

Trial Summary TS

TRIAL DESIGN DOMAINS

Trial Visits TV Related Records RELREC

RELATIONSHIP

Supplemental qualifierss SUPP- - Subject Visits SV

. . . . . . . . . . . . . . .

two character domain code: AE, DM…

SDTM

 4.2.1 Domains & Classes  listed in SDTM IG doc v3.1.2 p. 13

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Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015

two character domain code: AE, DM…

• 1. Adverse Events-AE  Medical events during study
• 2. Disposition-DS  Protocol milestones (e.g. randomization),

completion status & reason discontinuation

• 3. Medical History-MH  Medical events before and at start
• f study

EVENTS CLASS

Adverse Events AE Medical History MH

. . .

• 4. Protocol Deviations-DV  Protocol deviations during study
• 5. Clinical Events-CE  Medical events during study but not

classified as AEs e.g. efficacy endpoints like malaria in study

• n malaria

 Following domains/SDTM datasets:

SDTM

 4.2.1 Domains & Classes  listed in SDTM IG doc v3.1.2 p. 13

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Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015 INTER VENTIONS CLASS EVENTS CLASS

Adverse Events AE Medical History MH Demo graphics DM

FINDINGS CLASS

Vital Signs VS Phyical Exam PE Con Med CM Substance use SU

GENERAL OBSERVATION CLASSES SPECIAL PURPOSE DOMAINS

Trial Summary TS

TRIAL DESIGN DOMAINS

Trial Visits TV Related Records RELREC

RELATIONSHIP

Supplemental qualifierss SUPP- - Subject Visits SV

. . . . . . . . . . . . . . .

two character domain code: AE, DM…

SDTM

 4.2.1 Domains & Classes  listed in SDTM IG doc v3.1.2 p. 13

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Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015

two character domain code: AE, DM…

• 1. ECG –EG  ECG data
• 2. Inclusion/Exclusion criteria not met-IE  criteria that are

not met

• 3. LAB Test Results –LB  Lab data of study (incl. central

LAB or CRO)

• 4. Physical Examination-PE  General physical exam data
• 5. Questionnaire-QS  Questionnaire, diary data

FINDINGS CLASS

Vital Signs VS Phyical Exam PE

. . .

 Following domains/SDTM datasets:

SDTM

 4.2.1 Domains & Classes  listed in SDTM IG doc v3.1.2 p. 13

(cont.)

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Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015

two character domain code: AE, DM…

• 6. Subject Characteristics–SC  Subject related data not in
• ther domains e.g. subject intials, eye colour,…
• 7. Vital Signs -VS  Blood Pressure, Height, Weight,

Pulse,Body temperature & BMI

• 8. Drugs Accountability –DA  Accountability of study drug :

receipt, dispensing, return, packaging

• 9. Microbiology Specimen-MB Microorganisms species

data, growth status

• 10. Microbiology Susceptability-MS  Any findings not in MB

FINDINGS CLASS

Vital Signs VS Phyical Exam PE

. . .

 Following domains/SDTM datasets:

SDTM

 4.2.1 Domains & Classes  listed in SDTM IG doc v3.1.2 p. 13

(cont.)

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Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015

two character domain code: AE, DM…

• 11. Pharmacokinetic Concentrations –PK  Tissue related data

(serum, blood) – concentrations of study drug & metabolites

• 12. Pharmacokinetic Parameters –PP  Parameters on the

time~concentration curve

FINDINGS CLASS

Vital Signs VS Phyical Exam PE

. . .

 Following domains/SDTM datasets:

• 13. Findings About –FA  Findings related to Events and

Interventions not represented within Events/Interventions (e.g. AE severity changing over time)

SDTM

 4.2.1 Domains & Classes  listed in SDTM IG doc v3.1.2 p. 13

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Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015 INTER VENTIONS CLASS EVENTS CLASS

Adverse Events AE Medical History MH Demo graphics DM

FINDINGS CLASS

Vital Signs VS Phyical Exam PE Con Med CM Substance use SU

GENERAL OBSERVATION CLASSES SPECIAL PURPOSE DOMAINS

Trial Summary TS

TRIAL DESIGN DOMAINS

Trial Visits TV Related Records RELREC

RELATIONSHIP

Supplemental qualifierss SUPP- - Subject Visits SV

. . . . . . . . . . . . . . .

two character domain code: AE, DM…

SDTM

 4.2.1 Domains & Classes  listed in SDTM IG doc v3.1.2 p. 13

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Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015

two character domain code: AE, DM…

• 1. Demographics–DM  Date of birth, Age, Race, Ethnic origin

& values of ARM (study treatment)

• 2. Comments - CO  To collect free text from other domains or

CRF comments pages

• 3. Subject Elements–SE  actual timing of the study

elements (screening, randomization, Follow up...)

• 4. Subject Visits -SV  actual timing of the subject visits

 Following domains/SDTM datasets:

Demo graphics DM

SPECIAL PURPOSE DOMAINS

Subject Visits SV

. . .

SDTM

 4.2.1 Domains & Classes  listed in SDTM IG doc v3.1.2 p. 13

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Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015 INTER VENTIONS CLASS EVENTS CLASS

Adverse Events AE Medical History MH Demo graphics DM

FINDINGS CLASS

Vital Signs VS Phyical Exam PE Con Med CM Substance use SU

GENERAL OBSERVATION CLASSES SPECIAL PURPOSE DOMAINS

Trial Summary TS

TRIAL DESIGN DOMAINS

Trial Visits TV Related Records RELREC

RELATIONSHIP

Supplemental qualifierss SUPP- - Subject Visits SV

. . . . . . . . . . . . . . .

two character domain code: AE, DM…

SDTM

 4.2.1 Domains & Classes  listed in SDTM IG doc v3.1.2 p. 13

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Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015

two character domain code: AE, DM…

• 1. Trial Arms–TA Planning of the Arms (study treatment)
• 2. Trial Elements - TE  Planning of the study elements

(screening, randomization, Follow up...)

• 3. Trial Visits–TV  The planned visits
• 4. Trial Inclusion/Exclusion criteria - TI  in/exclusion

criteria for the trial  Following domains/SDTM datasets:

Trial Summary TS

TRIAL DESIGN DOMAINS

Trial Visits TV

. . .

• 5. Trial Summary- TS  basic trial information, such as trial

phase, protocol title, design objectives

SDTM

 4.2.1 Domains & Classes  listed in SDTM IG doc v3.1.2 p. 13

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Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015 INTER VENTIONS CLASS EVENTS CLASS

Adverse Events AE Medical History MH Demo graphics DM

FINDINGS CLASS

Vital Signs VS Phyical Exam PE Con Med CM Substance use SU

GENERAL OBSERVATION CLASSES SPECIAL PURPOSE DOMAINS

Trial Summary TS

TRIAL DESIGN DOMAINS

Trial Visits TV Related Records RELREC

RELATIONSHIP

Supplemental qualifierss SUPP- - Subject Visits SV

. . . . . . . . . . . . . . .

two character domain code: AE, DM…

SDTM

 4.2.1 Domains & Classes  listed in SDTM IG doc v3.1.2 p. 13

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Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015

two character domain code: AE, DM…

• 1. Relating datasets -RELREC To identify relationships

between datasets

• 2. Supplemental Qualifiers – SUPP- -  To collect all non-

standard data from the other domains  Following domains/SDTM datasets:

Related Records RELREC

RELATIONSHIP

Supplemental qualifierss SUPP- -

SDTM

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Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015

 4.2.2 Variable(s)  listed in SDTM doc v1.4 p. 9-35

SDTM

 Variable(s)

 classification by role

 3 core categories:

presence can be null Required: always no

Expected:

always yes Permissible: if collected yes 27

Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015

Identifier

• Study  STUDYID
• Subject USUBJID
• Domain  DOMAIN
• Sequence  - -SEQ

Topic Qualifier Timing

To identify the

• bservation

To specify the focus e.g.

• Labtest name LBTEST
• AE term  AETERM
• Drug name  CMTRT

To specify results

• r traits

To specify the timing e.g.

• Lab result  LBORRES
• AE severity  AESEV
• Drug dose CMDOSE

eg.

• Lab date  LBDTC
• AE start  AESTDTC
• Drug end  CMENDTC

(Note: 5th variable ‘Rule’ referring to algoritm/method to define start/end and looping conditions, only in Trial Design model)

SDTM

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Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015

 Example data set (AE):

Identifiers Topic Qualifier

Variable

SDTM

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Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015

 Variable(s)  list metadata per domain

(1)Variable (2)Label (3)Type (4)Contro lled terms/ (5)Origin (6)Role (7)Comment STUDYID Study identifier Char CRF page Identifier DOMAIN Domain Abbreviat ion (=AE) Char AE CRF page Identifier USUBJID Unique Subject number Char CRF page Identifier AESEQ Sequence number Num Derived Identifier AETERM Reported term f or AE Char CRF page Topic AEDECOD Char Derived Qualifier (1) Field name (code) (2) Description variable (3)Variable type (4)Controlled teminology if applicable (5)Origin (6)Which role in dataset: identifier, topic, timing , qualifier (7)Comment: other relevant information

SDTM

 4. 2.3 Some rules/assumptions

• Submit only domain datasets that were collected
• Per domain:
• select required Identifier variables (e.g. STUDYID, DOMAIN,

USUBJID, --SEQ)

• include Topic variable
• include relevant Qualifier variables
• include applicable Timing variable
• set order of variables as in SDTM (tables 2.2.1;2.2.2;2.2 3)

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Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015

SDTM

 4. 2.3 Some rules/assumptions (cont.)

• Apply two character domain code to the variables

e.g. - -TRT  AETRT; MHTRT

• Variable : max 8 characters/Label: max 40 characters
• Any non-standard (SDTM) variables  SUPPQUAL

domain/dataset

• Text in uppercase ; exceptions e.g. MedDRA, units

mg/dL…)

• Date/Time = ISO 8601 YYYY-MM-DDThh:mm:ss

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Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015

Clinical Data Acquisition Standards Harmonization (CDASH)

1.0 Introduction

• Its a standard way to organize and format the

way you collect clinical trial data.

• Follow CDISC defined standards development

process

• Developed to support the streamlining of

processes within medical research.

• CDASH Standard Version 1.1
• Specifications includes 16 domains that are all therapeutic area

agnostic

• Download guide at: http://www.cdisc.org/cdash

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Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015

CDASH Published Documents

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Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015

Why CDASH?

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2.0 Value of CDASH

 Streamline the processes

 You don’t reinvent the wheel every time when

conducting a study:

 reuse of CRFs,  edit checks and output programs  Reuse of analysis programs i.e. do files.

 Makes data more usable

 Data aggregation  Data mining  Data usability

Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015

Why CDASH?

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 Sharing research data with your research partners

made easy

 Integrates the SDTM requirements into CRF  Provides traceability and more transparency to

regulators and other s who review your data.

Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015

Data collection without standard

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Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015

Data Without Standards…

ID GENDER A1 Male A2 Male A3 Female A4 Female A5 Male SUBJID SEX 0001 M 0002 F 0003 F 0004 M 0005 F USUBID SEX 00011 00012 1 00013 1 00014 00015 1 PTID GENDER 0001 1 0002 1 0003 2 0004 2 0005 1

Study #2 – dmg.xpt Study #3 – axd222.xpt Study #4 – dmgph.xpt

Name for Subject ID is never the same Name for demography dataset is variable??? Is Sex Male or Female, M or F, 1 or 2? Gender or Sex, what will this study use? Adapted from slide courtesy of Armando Oliva, M.D. and Amy Malla, FDA

Study #1 – demo.xpt

Data collection with CDASH (paper)

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• The standard CDASH CRF allow efficient data acquisition and efficient

data monitoring at the sites.

• Leads to more standard SDTM datasets.

Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015

CDASH MODEL

39 Harmonize process across standards

Ensure Harmonization with other CDISC standards Uses an SDTM concept (domain variable) if available and possible. When data collected can be placed directly into SDTM variable Standardize a CDASH variable if there is not an appropriate SDTM one CDASH variable is used that can map to SDTM

Use existing controlled terminology

That supports:

• Data analysis
• Traceability
• Data mining

3.0 CDASH Model

Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015

CDASH Metadata Tables

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CDASH standards are presented in metadata tables

• Common header fields
• Domains in alphabetical order
• Eight columns in each table

4.0 . CDASH Metadata Tables

Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015

CDASH Metadata Tables

Full question text for the data collection field. Short prompt for the data collection field; could be used as the CRF label SDTMIG Variable Name OR CDASH Variable Name BRIDG Mapping Defines the purpose of Data collection field Contains standard Instructions for the clinical site

• n how to

enter data

• n the CRF.

Includes controlled terminolog y Information/ratio nale and instructions on how to implement the CRF data collection fields Contains CDASH core designations for basic data collection fields

Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015

Conformance to CDASH

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Following :

Highly recommended(H R), Recommended/co nditional (R/C) Optional(O)

Using Question test or prompt

Using controlled

terminology Following Best practice recommendation in the specifications

Conformance to CDASH

4.1 . Conformance

Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015

CDASH Domain Names

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4.2 . Domain Names

Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015

Implementing CDASH in your data stream

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 Creating new variables  Creating new domain

 Custom domains are created when they are no published

domains

 The rules for creating custom domains are described in

STDMIG

5.0. CDASH Implementation

Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015

CDASH Variables

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 Created to address the specific needs of data collection and

management.

 Not possible to collect data using same data type, controlled

terminology or format with SDTM.

 More than one variable is needed for data collection & data

management, but will be mapped into a single SDTM variable.

 When a single variable can map into more than one place in

SDTM.

Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015

CDASH Variables

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 Process of creating new variables

Confirm

• Might be in

SDTM and not in CDASH

Use existing names

• Look in SDTM
• Domains
• QNAMs
• TESTCD

Create your Own

• Use CDASH/SDTM

variable naming fragments to create with similar conventions

Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015

Activity-Creating variables

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 Using the SDTMIG V 3.1 or higher & CDASH

standard guides ver. 1.1, to complete the activity

Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015

Process of creating custom domain

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• From SDTM

Confirm there is no published domain

• Must be based on a single class:
• Finding, Intervention, Events

Determine the one General Observation class for your custom domain

• Reserved domain codes
• Use X,Y.Z 1. X=Interventions 2. Y=Events 3. Z=Finds

Create an appropriate 2 character domain code

• Adding the domain code to the generic variable

from: class, common identifier and timing fields

Create the variables Create a standard mapping into SDTM from your output

Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015

Activity- Creating custom domains

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 Using the SDTMIG V 3.1 or higher as a

reference, to complete the activity

Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015

CDISC

 ADMIT – CDISC - considerations

• ADMIT will focus on CDASH
• Examining possible cooperation with CDISC
• Exploring the 2 Days CDISC course “End-to-

End” (which has academics as target audience)

 Online courses are available

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Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015

References

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 Http://www.cdisc.org/standard/cdash/downloads/

CDASH_STD_1_1_2011_01_18.pdf

 CDISC SDTM Implementation Guide version 3.2,

November 2013

Mary Thiongo & Harry van Loen, 4th ADMIT Workshop, ITM BELGIUM, 30 NOV-4DEC2015