a brief introducon to cdisc – sdtm and data mapping · (lab) protocol representation (pr)...
TRANSCRIPT
5/3/10 2
Agenda
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• FlowofClinicalTrialsData
• TheProblem
• IntroducingCDISC
• UnderstandingSDTM
• ConceptsofDataMapping
• References
5/3/10 3
FlowofClinicalTrialsData
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Protocol
CRF Design
Actual Trial (Patient data collected in CRFs)
CDM (Patient data in CRFs converted
to Raw Datasets)
Raw Datasets Create Analysis Datasets
Create TLFs
FDA Submission/Review
5/3/10 4
TheProblem
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Protocol
CRF Design
Actual Trial (Patient data collected in CRFs)
CDM (Patient data in CRFs converted
to Raw Datasets)
Raw Datasets Create Analysis Datasets
Create TLFs
FDA Submission/Review
LACK OF STANDARDS
5/3/10 6
Introduc/ontoCDISC
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Non‐profitorganiza7onin2000
ClinicalDataInterchangeStandardsConsor7um
(CDISC)
1. Developmentofindustrystandardstosupportthea) electronicacquisi7onb) exchangec) submissionandd) archivingofclinicaltrialsdata
2. Developmentofglobal,plaYormindependentstandards5. Improvedataqualityandaccelerateproductdevelopment
5/3/10 7
CDISCStandards
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StudyDataTabula/onModel(SDTM) AnalysisDataModel
(ADaM) Opera/onalDataModel(ODM)
LaboratoryDataModel(LAB)
ProtocolRepresenta/on(PR)
StandardforExchangeofNonclinicalData(SEND)
CaseReportTabula/onDataDefini/onSpecifica/on(CRTDDS)–(define.xml)
TrialDesignModel(TDM)ClinicalDataAcquisi/on
StandardsHarmoniza/on(CDASH)
5/3/10 8
UnderstandingSDTM
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Analysis Data Model (ADaM) Operational Data Model
(ODM) Laboratory Data Model
(LAB)
Protocol Representation (PR)
Standard for Exchange of Nonclinical Data (SEND)
Case Report Tabulation Data Definition Specification (CRTDDS) – (define.xml)
Trial Design Model (TDM) Clinical Data Acquisition
Standards Harmonization (CDASH)
Study Data
Tabulation Model (SDTM)
• Describes contents and structure of data collected during a clinical trial • Purpose is to provide regulatory authority reviewers (FDA) a clear description of the structure, attributes and contents of each dataset and variables submitted as part of a product application
5/3/10 9
UnderstandingSDTM
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1. StudyDataTabula7onModelV1.1
2. StudyDataTabula7onModelImplementa7onGuide:HumanClinicalTrials–V3.1.1
hbp://www.cdisc.org/sdtm/
5/3/10 10
BeforeandAPer‐SDTM
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Before APer
Domains√
StandardDomainNames
Χ
StandardVariables
StandardVariableNames
Domains√
StandardDomainNames
√
StandardVariables√
StandardVariableNames
√
Χ
Χ
5/3/10 11
BeforeandAPer‐SDTM
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Before APer
•Reviewershadtofamiliarizethemselveswithuniquedomainnames,variablesandvariablenamesusedinanapplica7on‐TIMECONSUMING
•Goodpor7onofreview7mespent“cleaningupthedata”
•Inefficient,error‐prone
•StandardDomainNames=EasytoFindData
•StandardVariables/VariableNames=ImmediateFamiliaritywiththeData
•Consistency
•Minimallearningcurve
•TIMEEFFICIENT
5/3/10 12
CDISCSubmissionMetadataModel
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Sevendis7nctmetadataabributes:
1. TheVariableName
2. Adescrip7veVariableLabel,upto40characters
3. ThedataType
4. Thesetofcontrolledterminologyforthevalueorthe
presenta7onformatofthevariable(ControlledTermsor
Format)
5/3/10 13
BeforeandAPer‐SDTM
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5. TheOriginorsourceofeachvariable
6. TheRoleofthevariable,whichdetermineshowthevariable
isusedinthedataset.
7. Commentsorotherrelevantinforma7onaboutthevariable
oritsdata.
5/3/10 14
Types/ClassesofDomainsinSDTM
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Interven/ons
Exposure
Conmeds
SubstUse
Findings
VitalsLabs
ECG
Incl/Excl SubjChar
Ques’aire
MicroMSv3.1.2
MicroMBv3.1.2
DrugAcctPhysExam
PKParamv3.1.2
PKConcv3.1.2
Events
AE
Devia7onsv3.1.2
Disposi7on
MedHx
ClinicalEventsv3.1.2
Demog
SpecialDomains
Comments
SUPPQUAL
TrialDesign(5Tables)
RELREC
SubjElementsv3.1.2
SubjVisitsv3.1.2
TheInterven'onsclass,capturesinves/ga/onaltreatments,therapeu/ctreatments,andsurgicalproceduresthatareinten/onallyadministeredtothesubject(usuallyfortherapeu/cpurposes)eitherasspecifiedbythestudyprotocol(e.g.,.exposure.),orprecedingorcoincidentwiththestudyassessmentperiod(e.g.,.concomitantmedica/ons.).
TheEventsclass,capturesplannedprotocolmilestonessuchasrandomiza7onandstudycomple7on(“disposi7on”),andoccurrencesorincidentsindependentofplannedstudyevalua7onsoccurringduringthetrial(e.g.,”adverseevents”)orpriortothetrial(e.g.,“medicalhistory”).
TheFindingsclass,capturestheobserva7onsresul7ngfromplannedevalua7onstoaddressspecificques7onssuchasobserva7onsmadeduringaphysicalexamina7on,laboratorytests,histopathology,ECGtes7ng,andques7onslistedonques7onnaires.
Inaddi7ontothethreegeneralobserva7onclasses,asubmissionwillgenerallyincludeasetofotherspecialpurposedatasetsofspecificstandardizedstructurestorepresentaddi7onalimportantinforma7on.
GeneralObserva/on
Classes
5/3/10 15
Categoriza/onOfVariablesinSDTM
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Variables
Roles Core/Being
GroupingQualifiersResultQualifiersSynonymQualifiersRecordQualifiersVariableQualifiers
1. Iden7fier2. Topic3. Timing4. Rule5. Qualifier‐
1. Required2. Expected3. Permissible
Iden/fier–
Iden/fiesthesubjectoftheobserva/on
Topic–
Iden/fiesthefocusoftheobserva/on
Timing–
Describesthestartandendofthe
observa/on
Qualifier–
Describesthetraitoftheobserva/on
Rule–
expressanalgorithmintheTrialDesign
model.
5/3/10 16
Categoriza/onOfVariablesinSDTM
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Variables
Roles Core/Being
GroupingQualifiersResultQualifiersSynonymQualifiersRecordQualifiersVariableQualifiers
1. Iden7fier2. Topic3. Timing4. Rule5. Qualifier‐
1. Required2. Expected3. Permissible
GroupingQualifiers–
areusedtogrouptogetheracollec/on
ofobserva/onswithinthesamedomain.
E.g.‐‐CAT,‐‐SCAT,‐‐GRPID,‐‐SPEC
ResultQualifiers–
describethespecificresultsassociatedwiththetopicvariable
forafinding.E.g.‐‐ORRES,‐‐STRESC,and
‐‐STRESN.
SynonymQualifiers–
specifyanalterna/venameforapar/cularvariableinanobserva/on.
E.g.‐‐MODIFYand‐‐DECOD,whichareequivalenttermsfora‐‐TRTor
‐‐TERMtopicvariable
RecordQualifiers–
defineaddi/onalaZributesoftheobserva/onrecordasawhole
(ratherthandescribingapar/cularvariablewithinarecord).
E.g.‐‐REASND,AESLIFE,
‐‐BLFL,‐‐POSand‐‐LOC.
VariableQualifiers–
areusedtofurthermodifyordescribeaspecificvariablewithin
anobserva/onandisonlymeaningfulinthecontextofthe
variabletheyqualify.
E.g.‐‐ORRESU,‐‐ORNHI,and‐‐ORNLO
5/3/10 17
Categoriza/onOfVariablesinSDTM
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Variables
Roles Core/Being
GroupingQualifiersResultQualifiersSynonymQualifiersRecordQualifiersVariableQualifiers
1. Iden7fier2. Topic3. Timing4. Rule5. Qualifier‐
1. Required2. Expected3. Permissible
RequiredVariables–
– Variablesneedtobeinthedomains
– Theirvaluescannotbenull
ExpectedVariables–
– Variablesneedtobeinthedomains
– Theirvaluescanbenull
PermissibleVariables–
– Variablesmaybepresentinthedomains–
canbeincludedasneeded
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AnExampleObserva7on
Qualifier
Unique Subject Identifier
Timing
Topic
Subject 123 had a serious and severe headache starting on study day 2
Categoriza/onOfVariablesinSDTM
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DatasetStructureSubject Identifier Topic Qualifier Timing
Categoriza/onOfVariablesinSDTM
AETERM USUBJID AESTDY AESEV AESER Unique Subject
Identifier
HEADACHE 123 2 SEVERE
Severity/ Intensity
Study Day of Start of Event
Reported Term for the Adverse Event
Serious Event
YES
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DatasetStructure
Categoriza/onOfVariablesinSDTM
AETERM USUBJID AESTDY AESEV AESER Unique Subject
Identifier
HEADACHE 123 2 SEVERE
Severity/ Intensity
Study Day of Start of Event
Reported Term for the Adverse Event
Serious Event
YES
Required Permissible Expected
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ExampleEventsData(MH)
Topic Identifiers
Timing
Qualifiers
Categoriza/onOfVariablesinSDTM
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Characteris/csofSDTMDomains
Domains–
1. Domain:Collec7onofobserva7onswithcommontopic.Generallyeachdomainisrepresentedbyadataset.
2. Eachdomainhasauniquetwo‐characterdomainname(e.g.,AE,CM,VS)
3. Variablesindomainbeginwiththedomainprefix:(e.g.,VSTESTCD)
5/3/10 23Copyright©2010,CytelSta7s7calSo:ware&ServicesPvt.Ltd.
AllRightsReserved.
Characteris/csofSDTMVariables
Variables–
1. VariableName:limitedto8‐chars
2. Date/7meformat–ISO8601isatextstringYYYY‐MM‐DDThh:mm:ss(notaSASformat)
3. Controlledterminology–
1. CT(**)publishedexternally(ex:MedDRAorfollowCDISC‐specificterminology)
2. CT(*)valuefromasponsor‐definedcodelist
5/3/10 24
ConceptsofDataMapping
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MappingProcess
SourceDatasets:StandardAe.g.:Client’slegacystandarddatasets
TargetDatasets:StandardBe.g.:CDISCSDTMCDISCADaMClient’snewstandards
5/3/10 25
DataMapping–Step1MappingDomains
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DEMODM
TargetDomains SourceDomains
AE
CM
AEV
COMVAR
CONMED
…..
…..
5/3/10 26
DataMapping–Step2MappingVariables
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DEMODM
TargetDomainVariables SourceDomainVariables
COMVAR
STUDYID COMVAR.STUDYID
DOMAIN
USUBJID COMVAR.USUBJID
SUBJID DM.SUBJID
RFSTDTC COMVAR._RFSTDT
RFENDTC COMVAR._RFENDTC
SITEID DM.SITEID
INVID
INVNAM
BRTHDTC DM.BRTHDTC
AGE DM.AGE
AGEU DM.AGEU
SEX DM.SEX
5/3/10 27
DataMapping–Step3MappingVariables‐Logic
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DEMODMMappingLogic
COMVAR
STUDYID COMVAR.STUDYID Direct
DOMAIN Compute
USUBJID COMVAR.USUBJID Direct
SUBJID DM.SUBJID Direct
RFSTDTC COMVAR._RFSTDT DateConversion
RFENDTC COMVAR._RFENDTC Direct
SITEID DM.SITEID Direct
INVID Notmapping
INVNAM Notmapping
BRTHDTC DM.BRTHDTC Direct
AGE DM.AGE Direct
AGEU DM.AGEU Direct
SEX DM.SEX ValueConversion
5/3/10 28
TypesofMapping
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OnetoOneMapping
Dateofbirth
SourceCRFVariables SDTMVariables
BRTHDTC
SEX SEX
Weight VSORRES
5/3/10 29
TypesofMapping
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OnetoManyMapping
VISITDATE
SourceCRFVariables SDTMVariables
‐‐DTC
‐‐DTC
‐‐DTC
5/3/10 30
TypesofMapping
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ManytoOneMapping
FUVisitDate
SourceCRFVariables SDTMVariables
STUDYDAY
BaselineVisitDate
5/3/10 31
AutomatedTool‐
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MapGenie
5/3/10 32
References
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1. Prac7calMethodsforCrea7ngCDISCSDTMDomainDataSetsfromExis7ngData‐RobertW.Graebner,Quin7les,Inc.,OverlandPark,KS
2. SDTM‐‐3.1.1Implementa7onGuide.pdf
3. StudyDataTabula7onModelv1.1.pdf
5/3/10 34
EmailAddress
AninditaBhabacharjee–
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