Training Course Syllabus:

CDISC Mapping and Strategies Implemented: 2-Day In-person Seminar

Course Description:

CDISC requirements to create SDTMs and ADaMs are not easy to understand or apply. There are many rules and standards that must be mastered and maintained across global studies. Pharmaceutical companies and CROs supporting global studies have a need to apply proven methods that reduce confusion and improve documentation. With new members joining the study team, there should be a system to help standardize and automate the FDA submission process.

This two day workshop teaches essential mapping and strategy concepts for creating and validating SDTM and ADaM variables in key CDISC datasets (DM, AE, ADSL, and ADAE). Examples of both SDTM and ADaM dataset structures will be reviewed and compared. In addition, a mapping plan from raw datasets to SDTM to ADaM datasets will also be outlined. To help assure higher quality clinical data, a qc checklist and some key edit check macros will be introduced. Students will get a copy of the new CDSIC e-guide and all SAS macros reviewed in class. All students will get a one month free trial premium membership to www.SASSavvy.com for making smarter SAS searches. Through case study analysis we will examine best practices to provide thoughts and ideas to develop or improve the CDISC mapping system.

Learning Objective:

Upon completing this course participants should:

Better understand ODM and SDM models
Better understand how SDTM and ADaM metadata play an important role to automate the process
Know how to maintain control terminology and value level metadata
Better understand differences and purpose of DEFINE.XML and DEFINE.PDF
Understand key differences between SDTM and ADaM Models and Process Flows
Understand key differences between the Seven CDISC Classes
How to create Dataset.XML from SAS
Better understand structure and syntax of ODM-XML files using examples
Understand the differences between the four different variable roles and three different variable types
Better understand the nine steps to SDTM mapping and seven steps to ADaM mapping
Better understand raw data, dataset joins and traceability concepts
Utilize metadata to automatically assign variable attributes in SDTMs and ADaMs
Create and process ISO8601 dates, hierarchy of adverse events variables, paired lab variables, as well as lab visit window techniques
Apply effective techniques for using PROC TRANSPOSE to create and merge SUPPXX datasets with SDTMs to create ADaMs
Be better prepared for the SAS Clinical Trials Certification exam
Utilize metadata to automatically assign variable attributes in ADaMs
Create and process ISO8601 dates, hierarchy of adverse events variables
Better understand the purpose of running OpenCDISC
Submit better FDA submissions by better understanding the technical and process review

Course Outline:
Day 1 (8:30 AM – 4:30 PM)

Understanding CDISC terms
ODM and SDM Map – The Big Picture
CDASH, Study Data Standardization Plan and Submission Data Standards
SDTMs and ADaMs Specifications
Metadata files and Control Terminology
CDISC Reference and Guides
DEFINE.XML and DEFINE.PDF – Differences and examples
MindMaps - SDTM and ADaM Domains, SDTM Variable Types and Roles
CDISC Quick References
Understanding Seven CDISC Classes
Study Reference Files
SDTM and ADaM Dataset Models and Process Flows
Creating and QCing Define.xml & Dataset-XML
Creating Dataset.XML from SAS
ODM-XML file structure and content
Global Element Order
Understanding Tagsets
Components – Metadata, Clinical Data, Administrative, Reference and Audit
Compare SDTM and ADaM – Key Differences
When are Key SDTM/ADaM Variables Created
Mapping Raw Data to SDTMs by SDTMs
Nine Step SDTM Mapping Plan
Confirm Date Variables
SDTM Mapping of Study Day, ex AESTDY
Three types of Raw Data collected
Three types of Dataset Joins
Match DM Variables: Three Types of Raw Variable Mapping to SDTMs
Seven Step ADaM Mapping Plan
ADaM Model Concepts
ADaM Six Levels of Flag Variables
ADaM BDS Variable Types
Three ADaM Models
Traceability
ADaM Mapping Plan – Analysis visit windows
ADLB – DTYPE=‘XXX’ New Records

Day 2 (8:30 AM – 4:30 PM)

80% General Variables
SDTM
Mapping to SDTM Variables: Four Types
Apply one of seven mapping methods
Eight Variable Types Based on Values
Control Terminology – Format Metadata from CODELISTS tab
SDTM Metadata Excel file
AE MedDRA Hierarchy Structure
Purpose of Trial Designs: Trial Elements, Trial Arms and Trial Visits
DM, AE, EX, SE, SV
ADaM
Analysis Variables
Imputation Methods
Baseline Identification
Visit Windows and Unscheduled Visits
ADSL, ADAE
20% Special Variables
SDTM
SUPPDM, SUPPAE, RELREC
Questionnaire Data – Online Reference
SDTM Oncology Domains (TU, TR, RS)
Findings About (FA) – Collection of different CRFs
ADaM - DTYPE, Other ex. ADVSLT
ADAM Metadata Excel file
ISO8601 Dates, Partial Dates, Durations and Periods
Study Validation Checklists
SDTM and ADaM QC Forms
OpenCDISC and SAS Clinical Standard Toolkit
Templates – SDTM and ADaM Specifications, Defaults, Master SDTM to ADaM Map
ISS/ISE – Master Control Terminology
Understanding the FDA Review process and preventing delays - FDA’s High Expectations
Understanding how to avoid FDA Review issues – Challenges
Sponsor’s Best Practices for better FDA Submissions - Lessons Learned
LB/ADLB
Paired lab variables
Lab visit window techniques
Raw/Standard Names/Units
Baseline Values
Change, Percent Change from Baseline
Imputation Methods

Seminar Summary:

This two day workshop teaches essential mapping and strategy concepts for creating and validating SDTM and ADaM variables in key CDISC datasets (DM, AE, ADSL, and ADAE). Examples of both SDTM and ADaM dataset structures will be reviewed and compared. (see full course description)

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