sdtm modelling: from study protocol to sdtm-compliant datasets

SDTM MODELLING: FROM STUDY PROTOCOL TO SDTM-COMPLIANT DATASETS

- Biometristi Italiani Associati – Seminario BIASCDISC SDTM and ADaM: Moving from theory to practiceSAS Institute – Milano - 14/03/2014

Angelo TinazziCytel Inc., Wilmington Del. USASuccursale de Meyrin – Geneva – [email protected]

Cytel Inc. - Confidential 2[A. Tinazzi]

SDTM MODELLING: FROM STUDY PROTOCOL TO COMPLIANTS DATASETS

Disclaimer

The information contained in this presentation is based on personal

research of the author and does not necessarily represent Cytel Inc..



Let’s migrate

Phase III study First Relapsed or Refractory Acute Myeloid

Leukemia Two arms - Blinded study

Case StudyLet’s migrate

Migration Approach

Gap Analysis

Understanding datasets

Modelling the migration

Migration

Finalize, Val, Document

Conclusions



Let’s migrate

Prior and “follow-up” cancer treatmentTumor Response (efficacy) including response to prior therapies

Combination TherapiesFollow-upOther various findings

Main Data Challenges

SDTM IG V 3.1.2 with Amendment 1 was used

Let’s migrate

Migration Approach

Gap Analysis



Migration


Conclusions



Migration Approach

Gap analysis Understanding source datasets Modelling the MigrationMigrationFinalize, Validate and Document

Let’s migrate

Migration Approach

Gap Analysis



Migration


Conclusions



Gap Analysis Initiated prior to commencing migration activities How to perform gap analysis

Itemization and evaluation of files to support migration activities Document inventory

Study documents

CDISC Standards

Company Standards / Company Implementation Guidance

Validate sample CRF fields versus source data External data requirements e.g. central labs Comparison of protocol amendments/versions against CRF

versions Clarifies the scope and challenges of migration activities Identifies differences in data collection formats

Let’s migrate

Migration Approach

Gap Analysis



Migration


Conclusions



Understanding Source Datasets

Determine if data Need to be submitted (e.g. «Any AE» information) Can be used as it is (structure-wise) Needs to be transposed and brought to a normalized

structure Need detailed pre-processing

Validate the data for any missing/partial values e. g. format of date variable

Let’s migrate

Migration Approach

Gap Analysis



Migration


Conclusions



Understanding Source DatasetsData domains first ‘pruning’

AE

AEAER CMCMR

CMPR

PRAML

BPP

CG

NLMULVEF

MARA

VS

PMBSAIFVPR

IFCRE

NCNC

NPTNSCT

EG

PE

SS

RESPLB

Let’s migrate

Migration Approach

Gap Analysis



Migration


Conclusions

Events Findings Interventions Special Domains

ET

CD

RA

PRAMLTX

RD

CD

RA

PRAMLTX

RD



Understanding Source DatasetsData domains first ‘pruning’ – Multiple sourcesSDTM Raw Datasets

AE AE AEAER

CM CMCMR CMPRIOR PRAML BPP

DM DEMO SCEL DS

DS DEMO DS RD ET

EX IFVPR IFCRE

IE IE (only violated criteria)

MH MH CH PSC DX

VS VS PMBSA

YG NCNC NPTN SCT

ZG CG MARA LVEF NLMU

ZR PRAMLTX CD RD RA

VS VS PMBSA

<Not submitted> ETH

Let’s migrate

Migration Approach

Gap Analysis



Migration


Conclusions



Modelling the Migration

The annotated CRF provides the migration team with a clear presentation of SDTM variables

Completed following the GAP analysis and prior to migration

Experience needed to create the annotated CRF Knowledge of the SDTM Implementation Guide and

Metadata Submission Guidelines (chapter 4 – Guidelines for Annotating CRFs)

Annotated CRF Let’s migrate

Migration Approach

Gap Analysis



Migration


Conclusions




Upon receiving all required information, start defining mapping rules.

The mapping rules should be defined from source datasets (raw data) to target datasets (SDTM)

Key components SDTM standards and Controlled Terminology files Study documents including original Annotated CRF Standard template for specifications Standard mapping rules to be used (e.g. ISO date

conversion, rename, derive etc.)

Additional Specifications Let’s migrate

Migration Approach

Gap Analysis



Migration


Conclusions




Adapt study terminology to standard CDISC (NCI) terminology (CT) The mapping needs to be described in the define.xml

CT not only restricted to only those values that are available in the data

All entries capitalized for CDISC CT ‘Spelling’ as per external dictionary (e.g. MedDRA)

Controlled Terminology Let’s migrate

Migration Approach

Gap Analysis



Migration


Conclusions




Mapping to CDISC (NCI) Controlled Terminology

e.g. Concomitant Medications route


Migration Approach

Gap Analysis



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Conclusions

Source CDISC/NCI CT

INFUSION PARENTERALAdministration by injection, infusion, or implantation

MOUTH/THROAT ORALAdministration to or by way of the mouth

TOPICAL-EYE OPHTHALMIC

TOPICAL PO TOPICAL




Mapping to CDISC (NCI) Controlled Terminology

e.g. Laboratory Unit


Migration Approach

Gap Analysis



Migration


Conclusions

CDISC/NCI CT Source

10^9/L X 10 9/L X1000/MM3 X10^3/MM3

10^6/L X10 6/UL X10^3/ML

umol/L MICROMOL/L




Domain that contains a clear representation of the design of a clinical trialCreated prior to CRF annotation and data migrationExperience needed to create the trial design data set:

SDTM Trial Design Concepts Experience with key clinical documents (e.g. Protocol, SAP, Data Sets, CSR)

Trial Design Let’s migrate

Migration Approach

Gap Analysis



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Conclusions




Subject Reference Start (RFSTDTC) / End Date (RFENDTC) E.g. first / last dose

Planned (ARM/ARMCD) vs Actual Arm (ACTARM/ACTARMCD)

DM Let’s migrate

Migration Approach

Gap Analysis



Migration


Conclusions




Relative to Subject Reference Date (RFSTDTC) Standard Derivation

Relative Study Days –DY –STDY --ENDY Let’s migrate

Migration Approach

Gap Analysis



Migration


ConclusionsIf (--STDTC<DM.RFSTDTC) then –STDY=--STDTC-DM.RFSTDTCElse –STDY=(--STDTC-DM.RFSTDTC)+1

SDTM does not allow for Study day 0




Prior anti-cancer therapies in CM

Mapping Details – Categories in standard domains

The new PR domain available in IG 3.2 may be used to store Surgery or other procedures

Let’s migrate

Migration Approach

Gap Analysis



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Conclusions




Check that none of the existing published domains will fit the need

Use existing models as prototype or choose the appropriate general observation class

How to determine where data belong in the SDTM

IG v3.1.3 section 8.6 Assign a 2–letter domain code. Possible convention:

Z- for findings Y- for interventions X- for events

Mapping Details – New Domains Let’s migrate

Migration Approach

Gap Analysis



Migration


Conclusions




Other Findings (ZG) Survival Status (ZS) Tumor Response (ZR) Other non-protocol cancer therapies (YG)


Migration Approach

Gap Analysis



Migration


Conclusions

New SS (Subject Status) domain available in IG 3.2




Other non-protocol cancer therapies (YG)


Migration Approach

Gap Analysis



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Conclusions

The Interventions class captures investigational, therapeutic and other treatments that are administered to the subject (with some actual or expected physiological effect) either as specified by the study protocol (e.g., exposure to study drug), coincident with the study assessment period (e.g., concomitant medications), or self-administered by the subject (such as use of alcohol, tobacco, or caffeine).

SDTM IG v3.1.3 Section 2.4




Other non-protocol cancer therapies (YG)Mapping Details – New Domains Let’s migrate

Migration Approach

Gap Analysis



Migration


Conclusions

STUDYID USUBJID DOMAIN YGSEQ YGSPID YGSTDTC YGENDTC

XXXX YYYYYY YG 1 1 2011-01-12 2011-02-20

XXXX YYYYYY YG 2 1 2011-01-12 2011-02-25

YGTRT YGCAT YGSCAT

FTC PLUS SORAFENIB SUBSEQUENT NON-PROTOCOL AML TREATMENTS

CHEMOTHERAPY

CLAG-M THERAPY SUBSEQUENT NON-PROTOCOL AML TREATMENTS

CHEMOTHERAPY

Interventions Qualitfiers

2.2.1

Select and include the relevant Qualifier variables from the identified general observation




Other non-protocol cancer therapies (YG)


Migration Approach

Gap Analysis



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Conclusions

Solicited information in the CRF




The Disposition dataset provides an accounting for all subjects who entered the study and may include protocol milestones, such as randomization, as well as the subject's completion status or reason for discontinuation for the entire study or each phase or segment of the study, including screening and post-treatment follow-up. Sponsors may choose which disposition events and milestones to submit for a study. See ICH E3, Section 10.1 for information about disposition events.

Mapping Details – Disposition (DS)SDTM IG v3.1.3 Section 6.2.2

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Migration Approach

Gap Analysis



Migration


Conclusions




Mapping Details – Disposition (DS) Let’s migrate

Migration Approach

Gap Analysis



Migration


Conclusions

Decide what to store in DS Protocol Milestone vs Disposition Event




AE, CM, DM, DS, EX, LB, MH, VS, YG, ZG, ZR, ZR

Domains Requiring Supplemental Qualifier Let’s migrate

Migration Approach

Gap Analysis



Migration


Conclusions

SUPPDM

SUPPCM




RELREC AE <---> CM ZR <---> CM ZR <---> YG

Supplemental Qualifier (SUPPXX) One per each domain where supplemental qualifiers

are required It should be not used as a waste basket

Identifying Relationship Let’s migrate

Migration Approach

Gap Analysis



Migration


Conclusions

FDA CDER Common Data Standards Issues Document




Identifying Relationship – ZR vs CM

The link requires also USUBJID (here hiden)

Let’s migrate

Migration Approach

Gap Analysis



Migration


Conclusions

ZR contains also tumor response to prior anti-cancer therapies stored in CM e.g. chemotherapy




Identifying Relationship – ZR vs CM

CM

RELREC

ZR


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Migration Approach

Gap Analysis



Migration


Conclusions




Because study arms are combining two treatments, there was the need of collecting relationship and action taken related to the two drugs. The experimental drug make use of AEACN and AEREL in AE, while for the combination drug Supplemental Qualifiers were required

Identifying Relationship – SUPPAE


AE

SUPPAE

Let’s migrate

Migration Approach

Gap Analysis



Migration


Conclusions




Split Domains if needed (dataset size >1GB) By Category (--CAT) or sub-category (--SCAT)

e.g. LBCAT in LB (HEMATOLOGY CHEMISTRY, etc.)

Imputations are not allowed in SDTMe.g. laboratory results such as ‘<50’ assigned to LBORRES (char variable) while LBORRESN (numeric version) will be empty assumption for ‘<‘50’ in ADaM

Additional points to consider Let’s migrate

Migration Approach

Gap Analysis



Migration


Conclusions

FDA CDER common data standard issues document



Migration

Understanding Specifications Developing migration programs (e.g. SAS) Transformation type

Auto Convert Data Types e.g. numeric to text Rename Convert Values e.g. Adaptation of CT Convert ISODate Concatenate e.g. in DSTERM main term plus details Compute (any user-defined SAS® code logic)

Identify derivations common to all domainse.g. COMVAR temp dataset to store keys, important date

SAS Macros to assist in standardizing the migration process (e.g. ISO date conversion, Controlled Terminology Look-ups)

Let’s migrate

Migration Approach

Gap Analysis



Migration


Conclusions



Migration

VSVSVitalsVitals

Source Dataset Variable

Target Dataset Variables

VITALS.STUDYID VS.STUDYID Auto

VITALS.USUBJID VS.USUBJID Auto

VITALS.VISITNUM VS.VISITNUM Auto

VITALS.VISIT VS.VISIT Auto

Mapping Logic

Direct Variables Mapping Let’s migrate

Migration Approach

Gap Analysis



Migration


Conclusions



Migration

Pre-processing Mapping Let’s migrate

Migration Approach

Gap Analysis



Migration


Conclusions

VSVSVitalsVitals

Source Dataset Variables

Target Dataset Variables

VITALS.SYSBP VS.VSTESTCD Transpose- Name Auto

VITALS.DIABP VS.VSTESTCD Transpose- Name Auto

VITALS.PULSE VS.VSTESTCD Transpose- Name Auto

VITALS.RESP VS.VSTESTCD Transpose- Name Auto

VITALS.TEMP VS.VSTESTCD Transpose- Name Auto

VITALS.WEIGHT VS.VSTESTCD Transpose- Name Auto

VITALS.HEIGHT VS.VSTESTCD Transpose- Name Auto

Mapping Logic

Pre-processing



Migration

©2014 Cytel Statistical Software & Services Pvt. Ltd.

Select SDTM Version hereSelect SDTM Version here

Set various folder paths

here

Set various folder paths

here

Tools to facilitate the mapping - MapGene Let’s migrate

Migration Approach

Gap Analysis



Migration


Conclusions



Migration

Pick a source datasetPick a source dataset

Pick a target dataset (in this case SDTM)

Pick a target dataset (in this case SDTM)


Tools to facilitate the mapping - MapGeneLet’s migrate

Migration Approach

Gap Analysis



Migration


Conclusions



Migration

“Auto” mapping using smart rules“Auto” mapping

using smart rules


Tools to facilitate the mapping - MapGene Let’s migrate

Migration Approach

Gap Analysis



Migration


Conclusions



MigrationTools to facilitate the mapping - MapGene Let’s migrate

Migration Approach

Gap Analysis



Migration


Conclusions



Finalize, Validate and Document

Remove duplicates when it is clear the «Not Done» applies to a certain category of assessments

Finalize - Final ‘pruning’

SDTM IG v3.1.3 Section 4.1.5.1.2 “TESTS NOT DONE “

Let’s migrate

Migration Approach

Gap Analysis



Migration


Conclusions




Downsize variable length

Variable length should be assigned based on actual stored data to avoid to minimize file size

Exception for All variables with identical names in different SDTM domains e.g. USUBJID, STUDYID, VISIT, EPOCH --DTC variables (always $19)

Finalize - Final ‘pruning’

H Y P E R K A L E M I AAETERM

Length=14

H Y P E R K A L E M I A Length=12

“Warning” issued by Validation Check SD1081

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Migration Approach

Gap Analysis



Migration


Conclusions





Actual protocol events (SV and SE) from migrated SDTM Identify key variables / Sorting --SEQ generation Use of special characters

E.g. any ASCII code not within 32-126

Additional within domain consistency Same LBSTRESU within the same LBCAT LBSPEC LBMETHOD

Finalize – Additional Steps Let’s migrate

Migration Approach

Gap Analysis



Migration


Conclusions




SDTM can be only finalized at the time of db-lockUnplanned Visits

Numbered based on chronological order

Medical Coding to be completedUnexpected Controlled Terminology

Laboratory units to harmonize to Controlled Terminology Free text for Partial Date

XPT Generation

Finalize

Possible “Warning” / “Errors” issued by OpenCDISC•SD0080 - AE start date is after the latest Disposition date•SD0081 - Observation date is after the latest Disposition date•SD0002 - NULL value in AEDECOD variable marked as Required

Let’s migrate

Migration Approach

Gap Analysis



Migration


Conclusions




QC of Migration of Clinical Datae.g. double programming and blinded if possible

Compliance to SDTM standards (OpenCDISC) Re-program of key statistical outputs

e.g. compare outputs created with original raw data and compare with outputs created from SDTM converted datasets

Validate Let’s migrate

Migration Approach

Gap Analysis



Migration


Conclusions




«Justify» errors / warnings Provide additional instructions / details

Help the reviewer understanding the data structure Useful ‘hints’ for stats/programming team

!!!! «Original» information may not in the location where you would expect to be !!!!!

Document - Reviewer Guide Let’s migrate

Migration Approach

Gap Analysis



Migration


Conclusions




Document - Reviewer Guide Let’s migrate

Migration Approach

Gap Analysis



Migration


Conclusions




Document - Reviewer GuideAdditional Key Instructions

Let’s migrate

Migration Approach

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Conclusions




Document - Reviewer GuideDocument Deviations

Let’s migrate

Migration Approach

Gap Analysis



Migration


Conclusions

Unexpected variable for a domain belonging to an observation class where the variable is allowed E.g. Severity of Medical History



Conclusions

ADaM is the right place for «derivation», but actually migrating to SDTM implies the «shake» of original source data

Migrating to SDTM is not just a matter of renaming variables

It could be challenging for biostats sometime to find / locate the required information

Let’s migrate

Migration Approach

Gap Analysis



Migration


Conclusions



Questions



Q&A

Q: Does SDTM requires british or american english?

A: Standard NCI terminology should be used, while for free text original entries should be kept e.g. investigator specifications



Q&A

Q: Should study in a submission up-coded to the same Medical Dictionary version? E.g. MedDRA for AEs

A: Yes if an ISS (Integrated Safety Summary) is submitted, then a single version of MedDRA should be used





TA

Identifying Elements and Trials Arms - PLANNED

TE




TV

Identifying Elements and Trials Arms - PLANNED

+TI +TS




SV

Identifying Elements and Trials Arms - ACTUAL

SE



An example ProjectWeeks

W0

CytelClient

W1

Share documents

Annotate CRF

Understanding Study Datasets

Gap Analysis

Submit datasets

Migration

Validation

Provide information

Develop Mapping

specifications

Create Define.XML

Review

Review

Communicate the results /issues

Confirmation on specs

Submit

Confirmation on datasets

Final submission

• Study protocol CY21-002, CRF, SAP etc.

• Datasets• Other informative

documents

• Study protocol CY21-002, CRF, SAP etc.

• Datasets• Other informative

documents

• Compare source dataset as against CRF

• Inform in case of missing documents

• Compare source dataset as against CRF

• Inform in case of missing documents Share required

informationShare requiredinformation

W2

W3

W4

W5



An example ProjectWeeks CytelClient

Share documents

Annotate CRF


Gap Analysis

Submit datasets

Migration

Validation

Provide information

Develop Mapping

specifications

Create Define.xml

Review

Review



Submit


Final submission

W0

W1

W2

W3

W4

W5



An example ProjectWeeks CytelClient

Share documents

Annotate CRF


Gap Analysis

Submit datasets

Migration

Validation

Provide information

Develop Mapping

specifications

Create Define.xml

Review

Review



Submit


Final submission

Receive specs approvalReceive specs approval

• Develop and validate datasets as listed in the scope document

• Submit - Datasets - SAS programs - Support documents

• Develop and validate datasets as listed in the scope document

• Submit - Datasets - SAS programs - Support documents

Receive Confirmation ondatasetsReceive Confirmation ondatasets

Create Define document and submit alldeliverables

Create Define document and submit alldeliverables

W0

W1

W2

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sdtm modelling: from study protocol to sdtm-compliant datasets

Health & Medicine

migration migration

migration team

migration experience

tinazzi sdtm modelling

study protocol

compliants datasets

source datasets data

source datasets raw