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CDISC ADaM 2.1 Implementation: A Challenging Next Step in the Process Presented by Tineke Callant...
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Transcript of CDISC ADaM 2.1 Implementation: A Challenging Next Step in the Process Presented by Tineke Callant...
CDISC ADaM 2.1 Implementation:A Challenging Next Step in the Process
Presented by Tineke Callant
2014-03-14
2
Agenda
CDISC - Introduction
CDISC - Foundational standards
CDISC ADaM V2.1 - Analysis data flow
CDISC ADaM V2.1 - ADaM data structures
CDISC ADaM V2.1 - Traceability
CDISC ADaM V2.1 - ADaM metadata
CHKSTRUCT macro
Linear method - Challenges and solutions
Take home messages
3
Clinical Data Interchange Standards Consortium - Introduction
1997 - Inception
2000 - 32 global companies
CDISC is a global, open, multidisciplinary, non-profit organization that has established standards to support the acquisition, exchange, submission and archive of clinical research data and metadata.
2014 - ± 200 organizations biotechnology and pharmaceutical development companies device and diagnostic companies CROs and technology providers government institutions, academic research centers and other non-profit
organizations
5
Clinical Data Interchange Standards Consortium - Introduction
Mission statement
The CDISC mission is to develop and support global, platform-independent data standards that enable information system interoperability to improve medical research and related areas of healthcare.
Data standards to improve clinical research
6
Clinical Data Interchange Standards Consortium - Introduction
- 2001: Biomedical Research Integrated Domain Group (BRIDG) Model
7
Agenda
CDISC - Introduction
CDISC - Foundational standards
CDISC ADaM V2.1 - Analysis data flow
CDISC ADaM V2.1 - ADaM data structures
CDISC ADaM V2.1 - Traceability
CDISC ADaM V2.1 - ADaM metadata
CHKSTRUCT macro
Linear method - Challenges and solutions
Take home messages
11
CDISC - Foundational standards
Study Data Tabulation Model (SDTM)
The content standard for regulatory submission of case report form data tabulations from clinical research studies.
Datasets containing data collected during the study and organized by clinical domain.
Analysis Data Model (ADaM)
The content standard for regulatory submission of analysis datasets and associated files.
Datasets used for statistical analysis and reporting by the sponsor, submitted in addition to the SDTM domains.
12
Agenda
CDISC - Introduction
CDISC - Foundational standards
CDISC ADaM V2.1 - Analysis data flow
CDISC ADaM V2.1 - ADaM data structures
CDISC ADaM V2.1 - Traceability
CDISC ADaM V2.1 - ADaM metadata
CHKSTRUCT macro
Linear method - Challenges and solutions
Take home messages
14
Agenda
CDISC - Introduction
CDISC - Foundational standards
CDISC ADaM V2.1 - Analysis data flow
CDISC ADaM V2.1 - ADaM data structures
CDISC ADaM V2.1 - Traceability
CDISC ADaM V2.1 - ADaM metadata
CHKSTRUCT macro
Linear method - Challenges and solutions
Take home messages
15
CDISC ADaM V2.1 - ADaM data structures
The Subject-Level Analysis Dataset (ADSL) structure
The Basic Data Structure (BDS)
Other
16
CDISC ADaM V2.1 - ADaM data structuresThe Subject-Level Analysis Dataset (ADSL) structure
One record per subject
Variables (required + other) Study identifiers (e.g. DM.STUDYID) Subject demographics (e.g. DM.AGE) Population indicator(s) (e.g. RANDFL) Treatment variables (e.g. DM.ARM) Trial dates (e.g. RANDDT)
Required in a CDISC-based submission
17
CDISC ADaM V2.1 - ADaM data structures
The Subject-Level Analysis Dataset (ADSL) structure
The Basic Data Structure (BDS)
Other
18
CDISC ADaM V2.1 - ADaM data structuresThe Basic Data Structure (BDS)
One or more records per subject, per analysis parameter, per analysis time point (conditionally required)
Variables e.g. PARAM and related variables e.g. AVAL and AVALC and related variables e.g. the subject identification e.g. DTYPE e.g. treatment variables, covariates
Supports the majority of statistical analyses
19
CDISC ADaM V2.1 - ADaM data structures
The Subject-Level Analysis Dataset (ADSL) structure
The Basic Data Structure (BDS)
Other
20
CDISC ADaM V2.1 - ADaM data structuresOther
CDISC ADaM Basic Data Structure for Time-to-Event Analysis Version 1.0 - May 8, 2012
CDISC ADaM Data Structure for Adverse Event Analysis Version 1.0 - May 10, 2012
21
Agenda
CDISC - Introduction
CDISC - Foundational standards
CDISC ADaM V2.1 - Analysis data flow
CDISC ADaM V2.1 - ADaM data structures
CDISC ADaM V2.1 - Traceability
CDISC ADaM V2.1 - ADaM metadata
CHKSTRUCT macro
Linear method - Challenges and solutions
Take home messages
23
Understanding the relationship of element vs. predecessor
Enabling transparancy
Analysis results → Analysis datasets → SDTM
CDISC ADaM V2.1 - Traceability
24
CDISC ADaM V2.1 - TraceabilityStrategies for implementing SDTM and ADaM standardsSusan Kenny – Michael Litzsinger
Parallel method
SDTM Domains DBMS Extract
Analysis Datasets
Retrospective method
DBMS Extract → Analysis Datasets → SDTM Domains
Linear method
DBMS Extract → SDTM Domains → Analysis Datasets
Hybrid method
DBMS Extract → SDTM Draft Domains → Analysis Datasets → SDTM Final Domains
26
CDISC ADaM V2.1 - Traceability
CDISC ADaM V2.1 Fundamental principles
– Provide traceability between the analysis data and its source data
Practical considerations– Maintain the values and attributes of SDTM variables
CDISC ADaM implementation guide (IG) V1.0 General variable naming conventions
27
CDISC ADaM V2.1 - TraceabilityGeneral variable naming conventions
Any ADaM variable whose name is the
same as an SDTM variable must be a
copy of the SDTM variable, and its label,
meaning, and values must not be
modified
28
Parallel method
SDTM Domains DBMS Extract
Analysis Datasets
Retrospective method
DBMS Extract → Analysis Datasets → SDTM Domains
Linear method
DBMS Extract → SDTM Domains → Analysis Datasets
Hybrid method
DBMS Extract → SDTM Draft Domains → Analysis Datasets → SDTM Final Domains
CDISC ADaM V2.1 - TraceabilityStrategies for implementing SDTM and ADaM standardsSusan Kenny – Michael Litzsinger
29
Linear method
DBMS Extract → SDTM Domains → Analysis Datasets
Traceability CDISC SDTM/ADaM Pilot Project Recommended
CDISC ADaM V2.1 - TraceabilityStrategies for implementing SDTM and ADaM standardsSusan Kenny – Michael Litzsinger
30
Hybrid method
DBMS Extract → SDTM Draft Domains → Analysis Datasets → SDTM Final Domains
Traceability Amendment 1 SDTM V1.2 and SDTM IG V3.1.2 Future?!?
CDISC ADaM V2.1 - TraceabilityStrategies for implementing SDTM and ADaM standardsSusan Kenny – Michael Litzsinger
31
Traceability → Recommended: Linear method
Flexible
Delivery of consistent analysis datasets
Easy to use (Excel file)
Easy to maintain (Excel file)
CDISC ADaM V2.1 - Traceability
32
Agenda
CDISC - Introduction
CDISC - Foundational standards
CDISC ADaM V2.1 - Analysis data flow
CDISC ADaM V2.1 - ADaM data structures
CDISC ADaM V2.1 - Traceability
CDISC ADaM V2.1 - ADaM metadata
CHKSTRUCT macro
Linear method - Challenges and solutions
Take home messages
34
CDISC ADaM V2.1 - ADaM metadata
Microsoft Office Excel spreadsheet as framework
analysis dataset
%CHKSTRUCT(ds_ = ) Automatization Compliance
define.xml
35
CDISC ADaM V2.1 - ADaM metadata
Analysis dataset metadata
Analysis variable metadata
Analysis parameter value-level metadata
Analysis results metadata
36
CDISC ADaM V2.1 - ADaM metadataAnalysis dataset metadata
Illustration from CDISC ADaM V2.1
Practical consideration: ADxxxxxx
! ≠ SDTM !The key variables should define uniqueness
37
Analysis dataset naming convention
ADxxxxxx
The subject-level analysis dataset is named ADSL
max. 8 characters
CDISC ADaM V2.1 - ADaM metadataAnalysis dataset metadata
38
CDISC ADaM V2.1 - ADaM metadata
Analysis dataset metadata
Analysis variable metadata
Analysis parameter value-level metadata
Analysis results metadata
40
CDISC ADaM V2.1 - ADaM metadata
Analysis dataset metadata
Analysis variable metadata
Analysis parameter value-level metadata
Analysis results metadata
41
Illustration from CDISC ADaM V2.1
CDISC ADaM V2.1 - ADaM metadataAnalysis parameter value-level metadata
42
CDISC ADaM V2.1 - ADaM metadata
Analysis dataset metadata
Analysis variable metadata
Analysis parameter value-level metadata
Analysis results metadata (not required)
43
CDISC ADaM V2.1 - ADaM metadataAnalysis variable metadata in practice
Analysis dataset metadata
Analysis variable metadata
Dataset name Display formatVariable name Codelist / Controlled termsVariable label Source / DerivationVariable type
Parameter identifier (Basic Data Structure (BDS))
Analysis results metadata (not required)
45
CDISC ADaM V2.1 - ADaM metadataAnalysis variable metadata in practice
SAS variable attributes
To work in a SAS environment– NAME
– TYPE
– LENGTH
– FORMAT
– INFORMAT
– LABEL
– POSITION IN OBSERVATION
– INDEX TYPE
Analysis variable metadata fields
– DATASET NAME
– VARIABLE NAME
– VARIABLE LABEL
– VARIABLE TYPE
– DISPLAY FORMAT
– CODELIST /
CONTROLLED TERMS
– SOURCE / DERIVATION
– BASIC DATA STRUCTURE:PARAMETER IDENTIFIER
47
CDISC ADaM V2.1 - ADaM metadataAnalysis variable metadata in practice - Subposition in observation
Example ADSL – SITEGR* (Char) and SITEGR*N (Num)
* = a single digit [1-9]
SITEID
SITEID grouped together by city in the variable SITEGR1 (SITEGR1N)
SITEID grouped together by province in the variable SITEGR2 (SITEGR2N)
48
CDISC ADaM V2.1 - ADaM metadataAnalysis variable metadata in practice - Subposition in observation
%CHKSTRUCT(ds_ = ADSL)
1 21 2ORDER
49
CDISC ADaM V2.1 - ADaM metadataAnalysis variable metadata in practice - Subposition in observation
ORDER 1 2 1 2
50
CDISC ADaM V2.1 - ADaM metadataAnalysis variable metadata in practice - Subposition in observation
Example ADSL – SITEGR* (Char) and SITEGR*N (Num)
* = a single digit [1-9]
POSITION IN OBSERVATION
SUBPOSITION IN OBSERVATION
VARIABLE NAME
1 STUDYID
2 USUBJID
3 SITEID
4 1 SITEGR*
4 2 SITEGR*N
52
CDISC SDTM CDISC ADaM
Req - Required
The variable must be included in the dataset and cannot be null for any record.
Req - Required
The variable must be included in the dataset.
Exp - Expected
... and may contain some null values.
Cond - Conditionally required
... in certain circumstances.
Perm - Permissible
The variable should be used in a domain as appropriate when collected or derived.
Perm - Permissible
The variable may be included in the dataset, but is not required.
CDISC ADaM V2.1 - ADaM metadataAnalysis variable metadata in practice - Core
53
Agenda
CDISC - Introduction
CDISC - Foundational standards
CDISC ADaM V2.1 - Analysis data flow
CDISC ADaM V2.1 - ADaM data structures
CDISC ADaM V2.1 - Traceability
CDISC ADaM V2.1 - ADaM metadata
CHKSTRUCT macro
Linear method - Challenges and solutions
Take home messages
54
CHKSTRUCT macro
Microsoft Office Excel spreadsheet as framework
analysis dataset
%CHKSTRUCT(ds_ = ) Automatization Compliance
define.xml
55
CHKSTRUCT macro - Automatization
%CHKSTRUCT(ds_ = ADSL)
Before
After
4 6 5 7 1 2 3
1 2 3 4 5 6 7
ORDER THE ANALYSIS VARIABLES
56
CHKSTRUCT macro - Automatization
%CHKSTRUCT(ds_ = ADSL)
Before
After
LABEL THE ANALYSIS VARIABLES
57
CHKSTRUCT macro - Automatization
%CHKSTRUCT(ds_ = ADSL)
Key variables
7
2 1 3 4
5
6 9 810
5
1 2 3 4
6
7 8 910
Key variables
Before
After
SORT THE ANALYSIS DATASET
62
Agenda
CDISC - Introduction
CDISC - Foundational standards
CDISC ADaM V2.1 - Analysis data flow
CDISC ADaM V2.1 - ADaM data structures
CDISC ADaM V2.1 - Traceability
CDISC ADaM V2.1 - ADaM metadata
CHKSTRUCT macro
Linear method - Challenges and solutions
Take home messages
65
Linear method - Challenges and solutionsStep 1 - CDISC SDTM Implementation Guide
Any ADaM variable whose name is the
same as an SDTM variable must be a
copy of the SDTM variable, and its label,
meaning, and values must not be
modified
66
Linear method - Challenges and solutionsStep 1 - CDISC SDTM Implementation GuideChallenge: Flexible variable length
...
...
...
67
Linear method - Challenges and solutionsStep 1 - CDISC SDTM Implementation GuideChallenge: Flexible variable length
CDISC SDTM IG Variables of the same name in split datasets should have the same
SAS Length attribute Version 5 SAS transport file format: max. 200 characters -- TESTCD and QNAM: max. 8 characters -- TEST and QLABEL: max. 40 characters
Example: DM.RACE: $41, $50, and $200
Amendment 1 to SDTM V1.2 and SDTM IG V3.1.2 Version 5 SAS transport file format: max. 200 characters
! only if necessary !
68
Traceability
Flexible
Delivery of consistent analysis datasets
Easy to use
Easy to maintain
Linear method - Challenges and solutionsStep 1 - CDISC SDTM Implementation GuideChallenge: Flexible variable length
69
Linear method - Challenges and solutionsStep 1 - CDISC SDTM Implementation GuideSolution: [sdtm] ↔ %CHKSTRUCT(ds_ = )
70
Example: LB.LBSCAT
Linear method - Challenges and solutionsStep 1 - CDISC SDTM Implementation GuideChallenge: Permissible variables
Solution: [sdtm] ↔ %CHKSTRUCT(ds_ = )
72
Linear method - Challenges and solutionsStep 2 - SUPP--
QNAM → variable name
QLABEL → variable label
QVAL → variable type
→ variable length
e.g. SUPPDM SDTM dataset e.g. ADSL ADaM dataset
73
Linear method - Challenges and solutionsStep 2 - SUPP--Challenge: Flexible code list
QLABEL is different for the same QNAM– Example
ELIGCONF Subject Still Eligible
ELIGCONF Still Fulfill Eligibility Criteria
QLABEL format– Example
RANDNO RANDOMIZATION NUMBER
RANDNO Randomization Number
QLABEL changes during the course of a study– Example
ELIGIBLE Suject Eligible For Dosing
ELIGIBLE Subject Eligible For Dosing
77
Linear method - Challenges and solutions - Step 3Challenge: 12 SDTM → 12 ADaM?!?
1
3
2
4
5
6
8
7
910
SDTM
12
11
ADaM
?
?
??
??
??
??
??
78
Linear method - Challenges and solutions - Step 3Solution: 1 central model + sponsor specific add-ons
sponsorspecificadd-on
centralADaMmodel
domlist.sas7bdat
varlist.sas7bdat
codelist.sas7bdat
domlist.sas7bdat
varlist.sas7bdat
codelist.sas7bdat
domlist.sas7bdat
varlist.sas7bdat
codelist.sas7bdat
1
1 Convert Excel file to SAS datasets (by ADaM administrator)
2
2 Combine central model and sponsor specific add-on (by study programmer)
1
79
Traceability
Flexible
Delivery of consistent analysis datasets
Easy to use
Easy to maintain
Linear method - Challenges and solutions - Step 3Solution: 1 central model + sponsor specific add-ons
81
Linear method - Challenges and solutions - Step 4Challenge: SDTM model no. 1, 2, 3 ... ?
1
3
2
4
5
6
8
7
910
SDTM
12
11
ADaM
?
?
??
??
??
??
??
82
Linear method - Challenges and solutions - Step 4 Solution: Central metadata repository
CDISC metadata SDTM version SDTM metadata ...
Study characteristics Therapeutic area Clinical phase Trial design characteristics ...
Project metadata Study timelines Key Performance Indicators ...
86
Agenda
CDISC - Introduction
CDISC - Foundational standards
CDISC ADaM V2.1 - Analysis data flow
CDISC ADaM V2.1 - ADaM data structures
CDISC ADaM V2.1 - Traceability
CDISC ADaM V2.1 - ADaM metadata
CHKSTRUCT macro
Linear method - Challenges and solutions
Take home messages
87
Take home messagesMessage no. 1
ADaM SDTM
SDTM and ADaM go hand in hand
Thus, without a CDISC compliant SDTM database to start from, ADaM cannot exist
But do realize a strong analysis data model needs more than a CDISC compliant SDTM database alone
88
Linear method: Recommended Challenging
Solution: SDTM: Central metadata repository ADaM: Automatization, e.g. [sdtm], [supp] …
Study medata differences are handled efficiently
Take home messagesMessage no. 2