How to validate sdtm suppqual

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How to validate SDTM SUPPQUAL Data setMay 24th, 2010 by Kevin Lee

Covance Periapproval Services

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GM, every1

(Good Morning, Everyone)


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What will be discussed

The Introduction of SUPPQUALThe Issues in validating SUPPQUALThe RecommendationSDTM+SUPP procedureOverall steps for Validation ConcernsConclusion


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Introduction of SUPPQUAL

The SDTM does not allow any new variables beside ones assigned to each SDTM domain. So, the supplemental data set is introduced to supplement each SDTM domain. Its type:• a single SUPPQUAL dataset• The separate supplementary data sets (SUPP)

such as SUPPDM, SUPPAE, and SUPPEX.


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Structure of SUPPQUALName Label Type Role Codelist Mandatory

STUDYID Study Identifier Text Identifier NONE Req

RDOMAIN Related Domain Abbreviation

Text Identifier DOMAIN Req

USUBJID Unique Subject Identifier Text Identifier NONE Req

IDVAR Identifying Variable Text Identifier NONE Req

IDVARVAL Identifying Variable Value Text Topic NONE Req

QNAM Qualifier Variable Name Text Record Qualifier NONE Req

QLABEL Qualifier Variable Label Text Record Qualifier NONE Req

QVAL Data Value Text Qualifier NONE Req

QORIG Origin Text Qualifier NONE Req

QEVAL Evaluator Text Qualifier NONE Perm


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The Relation of SUPPQUAL to each domain

The SUPPQUAL data set is linked back to a parent record using RDOMAIN, USUBJID, IDVAR and IDVARVAL. IDVAR and IDVARVAL is usually the sequence number (ex. AESEQ, VSSEQ and so on) except DM and SV.


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The Issues in Validating SUPPQUAL

Some of SUPPQUAL variables could be originally captured as numeric – for example, QVAL and IDVARVAL. SUPPQUAL data set could be very large• For example, DM – 417KB, but SUPPQUAL –

858,529KB• The running Time in PC could be 0.5 to 1 hour.It is really difficult to visually link the SUPPQUAL data back to a parent record for the review.


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The recommendation

For QVAL and IDVARVAL• Consistent conversion from numeric to character

type – using the same format on input statement• All the converted variables should be left-

aligned.Better hardware (Unix is known more than 2 time faster than PC) Create the separate SUPP for each domain for easier validation, not just a single SUPPQUAL. Set up the friendly environment for the validation –SDTM+SUPP procedure/data sets.


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Advantage to create individual SUPP data sets

The supplementary data sets won’t be as big as a single SUPPQUAL, so it takes less time to review, to update, and to validate.


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The Advantages to create SDTM+SUPP data sets

SDTM+SUPP keeps all the variables related to SDTM domain. Much easier to link back to a parent record of the supplementary variables.Much easier when creating ADaM Data set.


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The Flow Chart of Data

SAS Raw Data Sets

(EXPOSURE)

ADaM(ADEX)

SDTM+SUPPProcedure

SDTM+SUPP(EX)

SDTM(EX)

SUPP(SUPPEX)

SDTM+SUPPProcedure


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The Options to validate SUPPQUAL

Validate all 3 of them - EX in SDTM+SUPP, EX and SUPPEX. Validate only 2 SDTM data sets – EX and SUPPEXValidate only EX in SDTM+SUPP

Our recommendation is to validate all 3 of them. However, the best way to validate is to start validating EX in SDTM+SUPP in the initial stage and validating all 3 of them in the later stage of the trials.


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The advantages in validating SDTM+SUPP data sets

much easier to validate the numeric supplementary variables.Less time to validate.If there are any issues in the supplementary variables, it is much easier to link back to parent records for the review.


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The automatic procedure to create SDTM and SUPP

The flag document (the best option is to create the flag variable column in Define document)The macro that split SDTM and SUPP from SDTM+SUPP according to the flag document.


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Domain Name Label Type Role Codelist Core Origin Suppqual Flag

EX STUDYID Study Identifier Char Identifier NONE Req CRF

EX DOMAIN Domain Abbreviation Char Identifier DOMAIN Req Derived

EX USUBJID Unique Subject Identifier Char Identifier NONE Req Sponsor Defined

EX EXSEQ Sequence Number Num Identifier NONE Req Derived

EX EXTRT Name of Actual Treatment Char Topic NONE Req Derived

EX EXDOSE Dose per Administration Num Record Qualifier NONE Perm CRF

EX EXDOSU Dose Units Char Variable Qualifier DOSU Exp CRF

EX EXDOSFRQ Dosing Frequency Per Interval Char Variable Qualifier DOSFRQ Perm Derived

EX EXROUTE Route of Administration Char Variable Qualifier ROUTE Perm CRF

EX EXSTDTC Start Date/Time of Treatment Char Timing ISO8601 Perm CRF

EX VISIT Visit Name Char Timing NONE Perm Derived

EX VISITNUM Visit Number Num Timing NONE Perm Derived

EX TAETORD Order of Element within Arm Num Timing NONE Perm Derived

EX EPOCH Trial Epoch Char Timing EPOCH Perm Derived

EX EXSPID2 Vial or Component ID Char Plus NONE Perm Derived Y

EX EXSTDTI Start Date/Time of Treatment Imputed Char Plus ISO8601 Perm Derived Y

EX ELEMENT Description of Element Char Plus NONE Perm Derived Y

EX ETCD Element Code Char Plus NONE Perm Derived Y

EX STDYRLEP Start Day Rel to Epoch Num Plus NONE Perm Derived Y

The sample Define Doc


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The sample codes to create SDTM and SUPP from SDTM+SUPP

**** Create SDTM EX domain;data sdtm.ex;

set sdtmsupp.ex;drop exspid2 exstdti element etcd stdyrlep;

run;**** Create SDTM SUPPEX domain;proc transpose data=sdtmsupp.ex out=_suppex(rename=(_name_=qnam

_label_=qlabel col1=qval exseq=_exseq));by studyid domain usubjid exseq;var exspid2 exstdti element etcd stdyrlep;

run;data sdtm.suppex(drop=_exseq);

set _suppex;idvarval = trim(left(put(_exseq, best30.)));idvar = ‘EXSEQ’; qorig = ‘Derived’;

run;


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Overall steps to validate in using SDTM+SUPP

Create the Define document including the flags to indicate the supplementary variables.Create the macro that split SDTM+SUPP data sets into SDTM and SUPP. Create SDTM+SUPP data sets and using the macro and Define document, create SDTM and SUPP from SDTM+SUPP.Validate SDTM+SUPP data sets first and then SDTM and SUPP.


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Concerns for SDTM+SUPP procedure

One single SUPPQUAL is requested by a sponsor.• Special attention on the truncations.

One to many relationship between a parent record to corresponding supplementary variables• When SUPP and SDTM are split by macro,

the SAS programmer puts the procedure that the duplicate records be removed from SDTM.

• When annotating eCRF, the SAS programmer do not include one to many relationship in the SDTM+SUPP.


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Conclusions

The validation of SUPPQUAL data set takes a lot of time and resource because of its size and complexity. However, through the automatic procedure and a special attention on possible SUPPQAUL related issues, the validation will take less time and less resource.


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Contact Information

Kevin LeeCovance Periapproval Services.555 North LaneSuite 6000Conshohocken, PA(610) 832 - 5751Email:[email protected]


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Thanks and any Question???

How to validate sdtm suppqual

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