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CDISC-SDTM

  • ➔ Introduction
  • ➔ Fundamentals of SDTM
  • ➔ Submitting Data in Standard Format
  • ➔ Assumption for Domain Models

STUDY DATA TABULATION MODEL (SDTM):

  • ✔ INTRODUCTION TO SDTM
  • ✔ CRF ANNOTATION
  • ✔ MAPPING SPECIFICATIONS
  • ✔ SDTM PROGRAMMING

SUBMITTING DATA IN STANDARD FORMAT:

  • ✔ Standard Metadata for Dataset Contents and Attributes
  • ✔ Using the CDISC Domain Models in Regulatory Submissions - Dataset METADATA
    • Primary Keys
    • CDISC Submission Value-Level Metadata
    • conformance

MODELS FOR SPECIAL-PURPOSE DOMAINS:

  • ✔ Demographics
  • ✔ Comments
  • ✔ Subject Elements
  • ✔ Subject Visits

DOMAIN MODELS BASED ON THE GENERAL OBSERVATION CLASSES:

  • ✔ Interventions
  • ✔ Events
  • ✔ Findings
  • ✔ Findings about

TRIAL DESIGN DATA SETS:

  • ✔ Introduction
  • ✔ Trial Arms
  • ✔ Trial Elements
  • ✔ Trial Visits
  • ✔ Trial Inclusion/Exclusion Criteria
  • ✔ Trial Summary Information
  • ✔ How to Model the Design of a Clinical Trial

REPRESENTING RELATIONSHIPS AND DATA:

  • ✔ Relating Group of Records Within a Domain Using the Grpid Variable
  • ✔ Relating Peer Records
  • ✔ Relating Datasets
  • ✔ Relating Non-Standard Variables Values to a Parent Domain
  • ✔ Relating Comments to A Parent Domain
  • ✔ How to Determine where Data Belong in the SDTM
  • ✔ Trial Design Datasets
  • ✔ Representing Relationships And Data
  • ✔ Models for Special Purpose Domains
  • ✔ Domain Models Based on General Observation Classes

FUNDAMENTALS OF THE SDTM:

  • ✔ Observations and Variables
  • ✔ Datasets and Domains
  • ✔ Special-Purpose Datasets
  • ✔ The General Observation Classes
  • ✔ The SDTM Standard Domain Models
  • ✔ Creating a New Domain

ASSUMPTIONS FOR DOMAIN MODELS:

GENERAL ASSUMPTIONS FOR ALL DOMAINS:

  • ✔ General Domain Assumptions
  • ✔ Review Study Data Tabulation and Implementation Guide
  • ✔ Relationship to Analysis Datasets
  • ✔ Additional Timing Variables
  • ✔ Order of the Variables
  • ✔ CDISC Core Variables
  • ✔ Additional Guidance on Dataset Naming
  • ✔ Splitting Domains
  • ✔ Origin Metadata
  • ✔ Assigning Natural Keys in the Metadata

GENERAL VARIABLE ASSUMPTIONS:

  • ✔ Variable-Naming Conventions
  • ✔ Two-Character Domain Identifier
  • ✔ Use of "Subject" and USUBJID
  • ✔ Case Use of Text in Submitted Data
  • ✔ Grouping Variables and Categorization
  • ✔ Submitting Free Text from the CRF
  • ✔ Multiple Values for a Variable

CODING AND CONTROLLED TERMINOLOGY ASSUMPTIONS:

  • ✔ Types of Controlled Terminology
  • ✔ Controlled Terminology Text Case
  • ✔ Controlled Terminology Values
  • ✔ Use of Controlled Terminology and Arbitrary Number Codes
  • ✔ Storing Controlled Terminology for Synonym Qualifier Variables
  • ✔ Storing Topic Variables for General Domain Models
  • ✔ Use of "Yes" and "No" Values

ACTUAL AND RELATIVE TIME ASSUMPTIONS:

  • ✔ Formats for Date/Time Variables
  • ✔ Formats for Date/Time Variables
  • ✔ Intervals of Time and Use of Duration for -DUR Variables
  • ✔ Use of the "Study Day" Variables
  • ✔ Clinical Encounters and Visits
  • ✔ Representing Additional Study Days
  • ✔ Use of Relative Timing Variables
  • ✔ Date and Time Reported in a Domain Based on Findings
  • ✔ Use of Dates as Result Variables
  • ✔ Representing Time Points

OTHER ASSUMPTIONS:

  • ✔ Original and Standardized Results of Findings and Tests Not Done
  • ✔ Linking of Multiple Observations
  • ✔ Text Strings That Exceed the Maximum Length for General-Observation-Class Domain Variables
  • ✔ Evaluators in the Interventions and Events Observation Classes
  • ✔ Clinical Significance for Findings Observation Class Data
  • ✔ Supplemental Reason Variables
  • ✔ Presence or Absence of Pre-Specified Interventions and Events

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