3 - Tambascia - SDTM fundamentals - BIAS 14032014.ppt ...€¦ · CDISC SDTM Beginner's Workshop...

CDISC SDTM Beginner's Workshop 24/03/201429/08/2012

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Biometristi Italiani Associati – Seminario BIAS –CDISC SDTM and ADaM: Moving from theory to

practice SAS Institute – Milano 14/03/2014

Nicola Tambascia

Statistical Programming

Accovion GmbH

SDTM fundamentals

SDTM fundamentals 2

àStudy

àData

àTabulation

àModel

SDTM defines a standard structure for study data tabulations that are to be submitted as part of a product application to regular authority such as FDA. It based on material prepared by the Submissions Data Standard (SDS) Team of the CDISC.

SDTM IG Version

SDTM Version Accepted by FDA

3.1.1 1.13.1.2 1.23.1.3 1.33.2 1.4

What is SDTM?


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SDTM fundamentals 3

Application/Interfaces of CDISC Standards

SDTM fundamentals 4

SDTM - Basic ConceptsDomains

Domain Classes

Domain Variables

Controlled Terminology (CT)

Metadata (define.xml)


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SDTM fundamentals 5

DomainsDomain = collection of observations with a common topic

• 1 Domain = 1 submission dataset (e.g., LB.XPT)

• Vertical structure

• 2 character domain name (e.g., LB)à 2 character variable name prefix (e.g. LBTEST)

• CDISC standard domains vs. custom domains

• Domain is assigned to 1 General Observation Classà Common variables per class (e.g., --TEST for Findings)

Laboratory Test

Standard Unit

Result in Standard Unit

Hemoglobin mg/dl 10

Hematocrit % 35

Hemoglobin (mg/dL)

Hematocrit (%)

10 35

NOT:

SDTM fundamentals 6

Findings Variables Extract from SDTM 1.3


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SDTM fundamentals 7

Domain ClassesInterventions

Events

Findings, Findings About

Special Purpose/Other• Demographics• Comments• Subject Elements• Subject Visits

Trial Design

Relationships• Related Records to express relationships between domains• Supplemental Qualifiers

SDTM fundamentals 8

Classes in SDTM V1.3§ 3 general observation classes and 1 special purpose class

provide the general structure for study data.

Classes

§ Planned in protocol milestones or independent occurrences taking place during the course of a trial

§ Prior to trial, e.g. medical history

§ Pre-planned data, e.g. randomization or study completion

§ Unplanned incidents, e.g. adverse events

§ Defined in protocol and applied during trial or preceding coincident to the study assessment

§ Investigational/ therapeutic treatments

§ Study/concomitant medications

§ Substances that are self administered by the subject, e.g. tobacco or alcohol

EVENTS INTERVENTIONS FINDINGS SPECIAL PURPOSE

§ Observations resulting from planned evaluations that are captured during the trial

§ Observations from planned/unplanned evaluations

§ Pharmacokinetics

§ Laboratory tests/ECG tests

§ Questionnaires

§ Additional subject level data that do not conform to one of the 3 general observation classes

§ Subject elements and visits

§ Comments

§ Demographics

For more information, please refer to the SDTM IG 3.1.3; sections 2.3, 2.4, 4, 5, 8.6.1


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SDTM fundamentals9

Domains in SDTM IG V3.1.3

Events

Interventions

Findings

Classes Domains

Adverse Events (AE) Disposition (DS) Medical History

(MH)

Exposure (EX) Concomittant Medication (CM)

Substance Use(SU)

Laboratory Data (LB)

Vital Signs (VS)

Physical Examination (PE)

Inclusion/ Exclusion (IE)

SubjectCharacteristics

(SC)

ECG (EG)

Demogrphics(DM) Comments (CO) Subject Elements

(SE)

Questionnaires (QS)

PK Parameters (PP)

PK Concentrations

(PC)

Microbiology Specimen (MB)

Protocol Deviations (DV)

Clinical Events (CE)

Subject Visits (SV)

Trial Elements (TE) Trial Arms (TA) Trial Summary

(TS) Trial Visits (TV) Trial Inclusion/ Exclusion (TI)

Drug Accountability

(DA)

Microbiology Susceptibility

Test (MS)

Special Purpose

Trial Design

Relationship Related Records (RELREC)

SupplementalQualifiers(SUPP--)

Findings about Events and Interventions (FA)

SDTM fundamentals 10

Class – InterventionsInvestigational, therapeutic andother treatments/substances administered

CDISC Standard Domains• Exposure (EX)

àStudy Drug Treatment

• Concomitant Medication (CM)

• Substance Use (SU) àE.g., Tobacco, Alcohol


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Sample EX Domain



Class – EventsIncidents independent of planned study evaluations

Protocol milestones (e.g., randomization, completion)

CDISC standard domains

• Adverse Events (AE)

• Disposition (DS)à Protocol milestones (e.g., informed consent, study completion)

• Medical History (MH)

• Deviations (DV) à Major/minor Protocol Deviations


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Sample AE Domain



Class – FindingsObservations resulting from planned evaluations

CDISC Standard Domains• ECG (EG)

• Incl/Excl Exceptions (IE)

• Labs (LB)

• Physical Exam (PE)

• PK Concentrations (PC)

• Questionnaires (QS)

• Subj. Characteristics (SC)

• Vital Signs (VS)

• Drug Accountability (DA)

• PK Parameters (PP)

Majority of data in findings structure• Test Code (- -TESTCD) , Name (- -TEST), Result (- -ORRES)


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Sample VS Domain



Findings about Events or Interventions

Use Cases• Different timing than event/intervention

à Details collected in Findings" structure (occurrence at a fixed date/visit)

• Details on events/interventions which have qualifiers of their ownà E.g., units, methods

• Details on underlying disease when not collected as MHà FAOBJ=<underlying disease>

• Related symptoms or therapies• Occurrence of pre-specified AEs

à AEOCCUR=‘N‘ not allowed in AE domain

Combination of FAOBJ and FATESTCDà FAOBJ: Name of clinical event or conditionà FATESTCD: characteristic of event/condition

Class - Findings About


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Findings About (FA) - Sample

CE

FA

Express relationship in RELREC


Class – Special PurposeDemographics (DM)

Comments (CO)• Separate comment page + comments on domain pages

Subject Elements

Subject Visits


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Demographics (DM)Structure 1 record per subject• General information on subject / treatment


Comments (CO)Captures unstructured free-text comments

• Dedicated comments CRF page (discouraged by CDASH)

• Other CRF pages referring to a specific domain


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Class – Trial DesignPurpose

Concept

Trial Arms (TA)

Trial Elements (TE)

Trial Visits (TV)

Trial Inclusion/Exclusion (TI)

Trial Summary (TS)


Trial Design Datasets - PurposeStandardized description of trial designs• Enables quick familiarization with trial design

• Facilitates comparison of different trials

• Enables search for trial design features in data warehouse

Linked with other SDTM domains

• Define arm and arm codes referenced in Demography (DM)

• Define visits used in findings datasets

• Define inclusion/exclusion criteria (only exceptions in IE)


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Trial Design Datasets – Purpose cont.Planned design vs. actual trial observations• Elements: TE vs. SE, Visits: TV vs. SV

• Inclusion: TI vs. IE

Trial design datasets contain planned design per protocol

Subject observation datasets contain observation as occurred in study • incl. unscheduled elements/visits

• Include observed observations onlyàPremature end


Trial Design Data Sets - Concept

Elements: Building Blocks

(Screen, Drug A, Drug B,

Open Drug A, Rescue) Branches

Arms:

Epochs:


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Trial Arms (TA)

Open Drug X => Open Drug A


Trial Elements (TE)


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Trial Visits (TV)Clinical Encounters Usually Defined in Protocol

May Start and End in Different Elements

VISITNUM, VISIT, VISITDY in TVà Controlled terminology for planned visits in findings datasets

Sample VS Domain in MSG sample submission package: tv.xpt


Trial Inclusion/Exclusion (TI)Criteria as defined in protocol

Versioning of criteria due to protocol amendments

IE


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Trial Summary (TS)Basic information about the study in vertical format

Planned study characteristics as per protocolTe

rmin

olog

y

Further details on TSVAL (Null Flavor, Code

value, Dictionary and version used


Trial Summary Codes

and even more in SDTM IG 3.1.3 Appendix C3

CT to be applied


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Subject Elements (SE)

Focus on handling of unplanned elements


Subject Visits (SV)

Focus on handling of unplanned visits


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CDISC SDTM Workshop 33

Class – RelationshipRelationships • Related Records to express relationships between domains

(RELREC)àE.g., concomitant medication applied due to specific AE

• Supplemental Qualifiers for parent domainsàE.g., Clinically Significant Flag for lab assessments



Expressing RelationshipsRelationship of multiple records in the same domain

à Same --GRPID value

à E.g., mark CM records that are part of a combo treatment

Relationships between records in different domainsà Domain RELREC

à Relationships expressed via same RELID value

à Includes contributing parent records identified viaUSUBJID, IDVAR, IDVARVAL

à Potential IDVARs: --SEQ, --GRPID

General relationships between domainsà Only 2 records in RELREC

à USUBJID, IDVARVAL are blank, --GRPID describes merge key


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RELREC SamplesRelationships between single records in different domains

General relationships between domains

• Prerequisite: all concentrations used for derivation of parameters


Sample SUPPQUAL (SUPPAE)

SUPP- - dataset may also be created for custom domainsSource: CDISC SDTM/ADaM Pilot (selected variables)


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Parent Domains & SUPPQUAL


Custom Domains vs. SUPPQUALIssue• Placement of variables not covered by standard domains

Solution• New topic (set of variables)

àCreate Custom Domain- Determine observation class (Findings, Interventions, Events)- New domain name (convention: X-, Y-, Z-)- Adapt variable names and labels accordingly

• Additional qualifier to existing domain (single variables)àCreate Supplemental Qualifier Dataset

- Naming convention: SUPP- - ( -- = Domain)- Link to parent domain record(s) via IDVAR, IDVARVAL


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Creating a Custom Domain According to SDTM IG


Domain Variables

Role Concept

Core Variable Concept

Technical Requirements

Values Controlled via Terminology


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AE Domain Class Table from SDTM IG


Domain Variables – Role ConceptIdentifier – Key Variables

• Study, Unique Subject ID, Domain Name, Sequence Number

Topic – Focus of Observation/Dataset

• E.g., Test Code for Findings, Verbatim Term for Events

Timing – Time Relevant Information

• Visits, Date/Times, Relative Study Days

Qualifier – Attributes/further Description of Topic

• Subcategories: Grouping, Result, Synonym, Record, Variable

• E.g., Type of Lab Test, Original Result, Test Name,Status=NOT DONE, LL/UL of Normal Range


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Core Variable ConceptCore=Required• Variable must be included in domain

• Variable cannot be Null

Core=Expected• Variable must be included in domain

• Variable can be Null (preferably not always)

Core=Permissible• Variable can be excluded/included in domain as needed

• Variables not populated should be omitted


Variables – Technical RequirementsRestrictions due to SAS V5 transport format• Variable names + length of --TESTCD <= 8 characters

• Variable labels + length of --TEST <= 40 characters

• Character variables <= 200 characters

Attributes (data type, label, ...) + (order) must match• SDTM specifications

• Study specific metadata (define.xml)

Additional variables =>• Custom domain or supplemental qualifiers

• (SDTM domain if variable type is included in SDTM class)


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Controlled TerminologyControlled Terminology needed for• Description of variables with a discrete list of possible values

• Vertical structure calls for standard test names and codesàFacilitates analysis across submissions

Current situation• CDISC Terminology available for some but not all variables

àE.g., N/Y, Vital Signs Test Codes (PULSE, TEMP, ...)

• Sponsor specific terminology in addition

• CDISC terms preferred, transition period allowed

CDISC + sponsor terminology => describe in metadata


http://www.cancer.gov/cancertopics/cancerlibrary/terminologyresources/cdisc

Controlled Terminology (Continued)


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Special Terminology: Date & DurationsISO 8601 Date/Time Format (-DTC Variables)

ISO 8601 Durations (-DUR Variables)


Metadata – define.xmlMetadata = data about data

Human-readable description to familiarize with data• What is included?

• Where does the data come from?

• Derivation rules, if applicable

Machine-readable metadata to facilitate ...

• SDTM data consistency check

• Upload into data warehouse

Preferred => mandatory format: define.xml


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Metadata – define.xml

Excerpt from the CDISC Draft Metadata Submission Guidelines define.xml Sample


Advantages of XML – Basic Technology<?xml version="1.0" encoding="ISO-8859-1"?><?xml-stylesheet type="text/xsl" href="define1-0-0.xsl"?><ODM...

<ItemGroupDef OID="DM"Name="DM"Repeating="No"IsReferenceData="No"Purpose="Tabulation"def:Label="Demographics"def:Structure="One record per subject"def:DomainKeys="STUDYID, USUBJID"def:Class="Special Purpose"def:ArchiveLocationID="Location.DM">...

style sheetreference


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define.xml Sections/ElementsData Metadata (TOC)

Variable Metadata

Variable Value Level Metadata

(Computational Algorithms)

Controlled Terminology/Code Lists

Annotated CRF

Optional: Supplemental Data Definition Document

Navigation via Bookmarks and Hyperlinks


Data Metadata


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Variable Metadata

Origins in SDTM IG 3.1.3: CRF, Derived, Assigned, eDT, Protocol, Sponsor Defined


Variable Value Level Metadata


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Controlled Terminology/Code Lists

External dictionary references incl. versions • e.g., MEDDRA, WHODRUG


CRF AnnotationDecide where data collected have to be stored in SDTM

• Target destination is based on data contentà Data on 1 CRF page may map to multiple SDTM domainsà Target data structure to be considered in the mapping

• Use standard SDTM domains where possible• Custom domains for new topics

à Decide on appropriate observation class

• Additional qualifiers for parent domains, i.e. not included in standard set of variablesà Supplemental Qualifier Domain (SUPP--)

• Issues resulting from non-extensible CDISC Controlled Terminology

Aim: Illustrate the Mapping


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Annotated CRF (blankcrf.pdf)See CDISC Metadata Submission Guidelines (SDTM)


Reading an OpenCDISC SDTM Validation Report

Structure and Layout

Case Study• Decide on

à Issues to be corrected

àAcceptable issues to be explained in study data reviewer’s guide

OpenCDISC validates for adherence to structural SDTM rules

Content validation still required

• E.g., Weight data mapped to Height not spotted by OpenCDISC


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OpenCDISC Validation Report - StructureDataset Summary

Issue Summary

Details

Rules


Remaining Issues in Study Data Reviewer‘s Guide

http://www.phusewiki.org/wiki/images/2/2d/SDRG_v1.1_2013-05-13.zipPhUSE CSS Study data reviewers guide:


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What‘s new in SDTM IG 3.2New Presentation (PDF Portfolio of files)

New Domains• Interventions Class

à Exposure as Collected (EC)à Procedures (PR)

• Events classà Healthcare Utilization (HO)

• Findings Classà Death Details (DD)à Immunogenicity Specimen Assessment (IS)à Morphology (MO)à Subject Status (SS)à Microscopic Findingy (MI)à Reproductive System Findings (RP)

• Findings Aboutà Skin Response (SR)

• Trial Designà Trial Disease Assessments (TD)

Medical Device and Associated Persons IG

New added Variables and changes to existing domainsSDTM fundamentals

Accovion GmbHHelfmann-Park 10D-65760 Eschborn, GermanyTel. +49 6196 [email protected]

www.accovion.com

Senior StatisticalProgrammer

Nicola Tambascia

Questions?



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Why CDISC SDTM/ADaM?General Benefits of Standards

• Improve communication

• Time/resource savings

• Comparison across submissions

FDA‘s eStudy Data Draft Guidance (Feb 2014)

• Written official requirement that sponsors submit study data in a standardized electronic format

• Includes HOW to submit (standard format)

• Does NOT include WHAT to submità Driven by science, to be agreed with reviewing division

• Refers to study data standards resources web page


Regulatory RequirementsSDTM + ADaM referenced in eCTD‘s Study Data Specifications V2.0

SDTM

ADaM

Details: FDA‘s web page: Electronic Common Technical Document (eCTD), Study Data Specifications

Results

Data

TraceabilityClinical Study Report

Analysis data + define (ADaM)Analysis results/data creation programs

legacy data (optional)

SDTM data + define + aCRF Option: raw data + define in legacy format

SEND (optional)


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SDTM Implementation Details Handling of free text

Handling of clinical significance data

Handling of “Check all that apply“

Splitting of domains

Unscheduled Visits

Controlled Terminology

Adding Variables to Standard Domains


Handling of Free TextNon Result Qualifiers

Options for populating supplemental qualifiers• EXLOC=OTHER, QNAM=EXLOCOTH, QVAL=UPPER ABDOMEN

• EXLOC=ABDOMEN, QNAM=EXLOCOTH, QVAL=UPPER ABDOMEN

• EXLOC=UPPER ABDOMEN; No SUPPEX

Choice driven by analysis/sponsor requirements

• Categories/grouping of locations in analysis table

Upper Abdomen


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Handling of Free Text (continued)Result Qualifiers

Options for representation in SDTM• MS Standard:

SCTEST=EYE COLOR, SCORRES=OTHER, SCSTRESC=OTHER, EYECOTH IN SUPPSC=BLUEISH GRAY

• Other Possibility:àSCTEST=EYE COLOR, SCORRES=OTHER, SCSTRESC=BLUEISH GRAY

àSCTEST=EYE COLOR, SCORRES=OTHER, SCSTRESC=GRAY, EYECOTH IN SUPPSC=BLUEISH GRAY

Choice driven by analysis/sponsor requirements• Categories/grouping of results in analysis table

Blueish Gray


Handling of Clinical Significance DataAssessment on record/test level• e.g., a certain lab test result assessed a clinically

significant by investigator

• Store flag in supplemental qualifier dataset

• Entry in SUPP-- with QNAM= --CLSIGàCan be linked to parent record

Assessment on multiple record level• e.g., overall assessment of ECG results at a certain

time point

• Separate record in parent domain

• --TEST = "Interpretation"


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Handling of "Check All that Apply"

Options• More specific naming and labeling

• Most relevant selection may be mapped to domain variable

• Driven by analysis/sponsor requirements


Multiple Responses for FindingsMultiple records per --TEST possible

Sample EG:EGTESTCD=RHYRATE, EGTEST=Rhythm and Rate, EGORRES=ATRIAL FIBRILLATION

EGTESTCD=RHYRATE, EGTEST=Rhythm and Rate, EGORRES=ATRIAL FLUTTER

--SEQ or --SPID necessary to uniquely identify a record


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Splitting of DomainsPossible reason: size issue (CDER <= 400 MB, CBER <= 1 GB)

Split on --CAT level

Allow for retrospective combination• Same DOMAIN value and suffix

• Consistent variable lengths

• --SEQ unique over all split domains

• Separate SUPP---- datasets following the same concept

Sample:QS36, SUPPQS36 with DOMAIN and RDOMAIN = QS

Ask FDA


Prespecified FlagNew qualifier variable --PRESP• Handling / marking of pre-specified term

• For use in interventions and events classes

• Rationale: higher incidences expected for pre-specified terms


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Unscheduled VisitsRepeated Measurements• e.g. to follow up on abnormal lab values

Multiple records for the same visit?

Repeated visit gets VISITNUM with Decimal?• VISITNUM=1, VISITNUM=1.01• Respective VISIT values?

à Missing value vs. “VISIT 1 – REPEAT 1“

Generic values VISIT=UNSCHEDULED, VISITNUM=9999for every unscheduled visit?

à Try to avoid already at data collection time

Consistency with TV and SV to be considered

Keys in define.xml should uniquely identify a record

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