SDTM modelling: from study protocol to SDTM-compliant datasets

SDTM MODELLING: FROM STUDY
PROTOCOL TO SDTM-COMPLIANT
DATASETS
- Biometristi Italiani Associati – Seminario BIAS
CDISC SDTM and ADaM: Moving from theory to practice
SAS Institute – Milano - 14/03/2014
Angelo Tinazzi
Cytel Inc., Wilmington Del. USA
Succursale de Meyrin – Geneva – Switzerland
angelo.tinazzi@cytel.com

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..

SDTM MODELLING: FROM STUDY PROTOCOL TO COMPLIANTS DATASETS
Let’s migrate
 Phase III study
 First Relapsed or Refractory Acute Myeloid
Leukemia
 Two arms - Blinded study
Case Study
Let’s migrate
Migration Approach
Gap Analysis
Understanding datasets
Modelling the migration
Migration
Finalize, Val, Document
Conclusions

Let’s migrate
Prior and “follow-up” cancer treatment
Tumor Response (efficacy) including
response to prior therapies
Combination Therapies
Follow-up
Other 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 Migration
Migration
Finalize, 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

Data domains first ‘pruning’
AE
AEAER CMCMR
CMPR
PRAML
BPP
CG
NLMU
LVEF
MARA
VS
PMBSAIFVPR
IFCRE
NCNC
NPTN
SCT
EG
PE
SS
RESP
LB
Let’s migrate
Migration Approach
Gap Analysis
Migration
Conclusions
Events Findings Interventions Special Domains
ET
CD
RA
PRA
MLTX
RD
CD
RA
PRA
MLTX
RD

Data domains first ‘pruning’ – Multiple sources
SDTM 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
Migration
Conclusions
Source CDISC/NCI CT
INFUSION PARENTERAL
Administration by injection, infusion, or implantation
MOUTH/THROAT ORAL
Administration 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 trial
Created prior to CRF annotation and data migration
Experience 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
Migration
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.RFSTDTC
Else –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
Migration
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
Migration
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

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

Migration Approach
Gap Analysis
Migration
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
Let’s migrate
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
Let’s migrate
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 SDTM
e.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 domains
e.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 here
Select 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)
Migration Approach
Gap Analysis
Migration
Conclusions

Migration
“Auto” mapping
using smart rules
“Auto” mapping
using smart rules
Migration Approach
Gap Analysis
Migration
Conclusions

Migration
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 A
AETERM
Length=14
H Y P E R K A L E M I A Length=12
“Warning” issued by Validation Check SD1081
Let’s migrate
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-lock
Unplanned Visits
 Numbered based on chronological order
Medical Coding to be completed
Unexpected 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 Data
e.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 Guide
Additional Key Instructions
Let’s migrate
Migration Approach
Gap Analysis
Migration
Conclusions

Document - Reviewer Guide
Document 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

SDTM MODELLING: FROM STUDY PROTOCOL TO COMPLIANTS
DATASETS
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 Project
Weeks
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 documentsShare required
information
Share required
information
W2
W3
W4
W5

An example Project
Weeks CytelClient
Share documents
Annotate CRF
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
W0
W1
W2
W3
W4
W5

An example Project
Weeks CytelClient
Share documents
Annotate CRF
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
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 on
datasets
Receive Confirmation on
datasets
Create Define document
and submit all
deliverables
Create Define document
and submit all
deliverables
W0
W1
W2
W3
W4
W5

SDTM modelling: from study protocol to SDTM-compliant datasets

More Related Content

What's hot

Viewers also liked

Similar to SDTM modelling: from study protocol to SDTM-compliant datasets

More from Angelo Tinazzi

Recently uploaded

SDTM modelling: from study protocol to SDTM-compliant datasets

Editor's Notes