Implementing CDISC Using SAS

Implementing CDISC Using SAS

by Chris Holland, Jack Shostak
Released December 2012
Publisher(s): SAS Institute
ISBN: 9781629592459

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Book description

For decades researchers and programmers have used SAS to analyze, summarize, and report clinical trial data. Now Chris Holland and Jack Shostak have written the first comprehensive book on applying clinical research data and metadata to the Clinical Data Interchange Standards Consortium (CDISC) standards. Implementing CDISC Using SAS: An End-to-End Guide is an all-inclusive guide on how to implement and analyze Study Data Tabulation Model (SDTM) and Analysis Data Model (ADaM) data and prepare clinical trial data for regulatory submissions. Topics covered include creating and using metadata, developing conversion specifications, implementing and validating SDTM and ADaM data, determining solutions for legacy data conversions, and preparing data for regulatory submission. The book covers products such as Base SAS, SAS Clinical Data Integration, and the SAS Clinical Standards Toolkit, as well as JMP Clinical. Anyone dealing with CDISC standards--including SAS or JMP programmers, statisticians, and data managers in the pharmaceutical, biotechnology, or medical device industries--will find the philosophical best practices and implementation examples in this book invaluable. This book is part of the SAS Press program.

Table of contents

  1. About This Book
  2. About The Authors
  3. Acknowledgments
  4. Chapter 1: Implementation Strategies
    1. Why “CDISC It”?
    2. Which Models to Use and Where
    3. Starting with the Clinical Data Acquisition Standards Harmonization (CDASH) Standard
    4. Implementation Plans and the Need for Governance
    5. SDTM Considerations
    6. ADaM Considerations
    7. Chapter Summary
  5. Chapter 2: SDTM Metadata and Define.xml for Base SAS Implementation
    1. SDTM Metadata
      1. Table of Contents Metadata
      2. Variable-Level Metadata
      3. Codelist Metadata
      4. Value-Level Metadata
      5. Computational Method Metadata
    2. Building define.xml
      1. Define File Header Metadata
      2. Define File Creation SAS Program
    3. Chapter Summary
  6. Chapter 3: Implementing the CDISC SDTM with Base SAS
    1. Base SAS Macros and Tools for SDTM Conversions
      1. Creating an SDTM Codelist SAS Format Catalog
      2. Creating an Empty SDTM Domain Dataset
      3. Creating an SDTM --DTC Date Variable
      4. Creating an SDTM Study Day Variable
      5. Sorting the Final SDTM Domain Dataset
    2. Building SDTM Datasets
      1. Building the Special-Purpose DM and SUPPDM Domains
      2. Building the LB Findings Domain
      3. Building a Custom XP Findings Domain
      4. Building the AE Events Domain
      5. Building the EX Exposure Interventions Domain
      6. Building Trial Design Model (TDM) Domains
    3. Chapter Summary
  7. Chapter 4: Implementing CDISC SDTM with the SAS Clinical Standards Toolkit and Base SAS
    1. SAS Clinical Standards Toolkit Background
    2. Clinical Standards Setup for Study XYZ123
    3. Building SDTM Datasets
    4. Base SAS Macros and Tools for SDTM Conversions
    5. Building the Special-Purpose DM and SUPPDM Domains
    6. Building define.xml
    7. Chapter Summary
  8. Chapter 5: Implementing the CDISC SDTM with SAS Clnical Data Integration
    1. SAS Clinical Data Integration Introduction
    2. SAS Clinical Data Integration Metadata
      1. Classifications of SAS Clinical Data Integration Metadata
      2. Setup of SAS Clinical Data Integration Metadata
    3. SAS Clinical Data Integration Study Setup
      1. Define the Clinical Study and Subfolders
      2. Register Source Datasets and Define Target SDTM Datasets
      3. Setting SAS Clinical Data Integration Defaults
    4. Creating SDTM Domains
      1. Creating the Special-Purpose DM and SUPPDM Domain
      2. Creating the AE (Adverse Events) Events Domain
      3. Creating the XP Pain Scale Customized Findings Domain
      4. Creating the EX Exposure Interventions Domain
      5. Creating the LB Laboratory Findings Domain
      6. Creating the Trial Design Model Domains
      7. Using Customized Code in SDTM Production
      8. Templating Your SDTM Conversion Jobs for Reuse
    5. Using SAS Clinical Data Integration to Create define.xml
    6. Chapter Summary
  9. Chapter 6: ADaM Metadata and ADaM Define.xml
    1. Metadata Spreadsheets
      1. Variable Metadata in ADaM
      2. Analysis Parameter Value-Level Metadata
      3. Analysis Results Metadata
      4. Building define.xml
    2. Define.xml Navigation and Rendering
    3. Chapter Summary
  10. Chapter 7: Implementing ADaM
    1. ADaM Tools
      1. ISO 8601 Date and DateTime Conversions
      2. Merging In Supplemental Qualifiers
    2. ADSL – The Subject-Level Dataset
    3. The ADaM Basic Data Structure (BDS)
    4. ADAE – Adverse Event Analysis Datasets
    5. ADTTE – The Time-to-Event Analysis Dataset
    6. Chapter Summary
  11. Chapter 8: SDTM Validation
    1. SAS Clinical Standards Toolkit
      1. SAS Clinical Standards Toolkit Setup
      2. SAS Clinical Standards Toolkit Validation Program
    2. SAS Clinical Data Integration
    3. OpenCDISC Validator
      1. Installing OpenCDISC Validator
      2. Running OpenCDISC Validator (Graphical User Interface)
      3. Evaluating the Report File and Report Results
      4. Modifying the Configuration Files
      5. Running OpenCDISC Validator in Command Line Mode
    4. Chapter Summary
  12. Chapter 9: Validating ADaM Data
    1. ADaM’s Published Validation Checks
    2. OpenCDISC Validator
    3. Running the OpenCDISC Validator as a Macro
    4. Traceability Checks
    5. Chapter Summary
  13. Chapter 10: CDISC Data Review and Analysis
    1. Safety Evaluations with JMP Clinical
      1. Getting Started with JMP Clinical
      2. Safety Analyses
      3. Patient Profiles
      4. Customizing JMP Clinical
    2. One PROC Away with ADaM Datasets
    3. Chapter Summary
  14. Chapter 11: Integrated Data and Regulatory Submissions
    1. Regulatory Guidance
    2. Data Integration Challenges
    3. Data Integration Strategies
      1. Representing Subjects Who Appear in Multiple Studies in Subject-Level Datasets
      2. Deciding on Which Data to Integrate
      3. Coding Dictionary Issues
      4. Summary of Data Integration Strategies
    4. Data Integration and Submission Tools
      1. Setting Variable Lengths Based on the Longest Observed Value
      2. Converting from Native SAS to Version 5.0 Transport Files
      3. Converting from Version 5.0 Transport Files to Native SAS
    5. Getting Submission Ready
    6. Chapter Summary
  15. Chapter 12: Other Topics
    1. Standard for Exchange of Non-Clinical Data
    2. HL7 Messaging
    3. BRIDG Model
    4. Protocol Representation Model
    5. FDA Janus Clinical Trials Repository
    6. CDISC Model Versioning
    7. Future CDISC Directions
    8. Chapter Summary
  16. Appendix A: Source Data Programs
    1. adverse Dataset
    2. demographics Dataset
    3. dosing Dataset
    4. laboratory Dataset
    5. pain scores Dataset
  17. Appendix B: SDTM Metadata
    1. Appendix B.1 - Table of Contents Metadata
    2. Appendix B.2 - Variable-Level Metadata
    3. Appendix B.3 - Codelist Metadata
    4. Appendix B.4 - Value-Level Metadata
    5. Appendix B.5 - Computational Method Metadata
    6. Appendix B.6 - Define Header Metadata
  18. Appendix C: ADaM Metadata
    1. Appendix C.1 - Define Header Metadata
    2. Appendix C.2 - Table of Contents Metadata
    3. Appendix C.3 - Variable-Level Metadata
    4. Appendix C.4 - Parameter-Level Metadata
    5. Appendix C.5 - Computational Method Metadata
    6. Appendix C.6 - Codelist Metadata
    7. Appendix C.7 - Analysis Results Metadata
    8. Appendix C.8 - External Links Metadata
  19. Appendix D: %make_define SAS Macro
    1. %make_define SAS Macro
    2. Additional SAS Code Comments
  20. Index

Product information

  • Title: Implementing CDISC Using SAS
  • Author(s): Chris Holland, Jack Shostak
  • Release date: December 2012
  • Publisher(s): SAS Institute
  • ISBN: 9781629592459