book

Implementing CDISC Using SAS

by Chris Holland, Jack Shostak

December 2012

Intermediate to advanced

286 pages

6h 49m

English

SAS Institute

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About This Book
About The Authors
Acknowledgments
Chapter 1: Implementation Strategies
Why “CDISC It”?Which Models to Use and WhereStarting with the Clinical Data Acquisition Standards Harmonization (CDASH) StandardImplementation Plans and the Need for GovernanceSDTM ConsiderationsADaM ConsiderationsChapter Summary
Chapter 2: SDTM Metadata and Define.xml for Base SAS Implementation
SDTM MetadataTable of Contents MetadataVariable-Level MetadataCodelist MetadataValue-Level MetadataComputational Method MetadataBuilding define.xmlDefine File Header MetadataDefine File Creation SAS ProgramChapter Summary
Chapter 3: Implementing the CDISC SDTM with Base SAS
Base SAS Macros and Tools for SDTM ConversionsCreating an SDTM Codelist SAS Format CatalogCreating an Empty SDTM Domain DatasetCreating an SDTM --DTC Date VariableCreating an SDTM Study Day VariableSorting the Final SDTM Domain DatasetBuilding SDTM DatasetsBuilding the Special-Purpose DM and SUPPDM DomainsBuilding the LB Findings DomainBuilding a Custom XP Findings DomainBuilding the AE Events DomainBuilding the EX Exposure Interventions DomainBuilding Trial Design Model (TDM) DomainsChapter Summary
Chapter 4: Implementing CDISC SDTM with the SAS Clinical Standards Toolkit and Base SAS
SAS Clinical Standards Toolkit BackgroundClinical Standards Setup for Study XYZ123Building SDTM DatasetsBase SAS Macros and Tools for SDTM ConversionsBuilding the Special-Purpose DM and SUPPDM DomainsBuilding define.xmlChapter Summary
Chapter 5: Implementing the CDISC SDTM with SAS Clnical Data Integration
SAS Clinical Data Integration IntroductionSAS Clinical Data Integration MetadataClassifications of SAS Clinical Data Integration MetadataSetup of SAS Clinical Data Integration MetadataSAS Clinical Data Integration Study SetupDefine the Clinical Study and SubfoldersRegister Source Datasets and Define Target SDTM DatasetsSetting SAS Clinical Data Integration DefaultsCreating SDTM DomainsCreating the Special-Purpose DM and SUPPDM DomainCreating the AE (Adverse Events) Events DomainCreating the XP Pain Scale Customized Findings DomainCreating the EX Exposure Interventions DomainCreating the LB Laboratory Findings DomainCreating the Trial Design Model DomainsUsing Customized Code in SDTM ProductionTemplating Your SDTM Conversion Jobs for ReuseUsing SAS Clinical Data Integration to Create define.xmlChapter Summary
Chapter 6: ADaM Metadata and ADaM Define.xml
Metadata SpreadsheetsVariable Metadata in ADaMAnalysis Parameter Value-Level MetadataAnalysis Results MetadataBuilding define.xmlDefine.xml Navigation and RenderingChapter Summary
Chapter 7: Implementing ADaM
ADaM ToolsISO 8601 Date and DateTime ConversionsMerging In Supplemental QualifiersADSL – The Subject-Level DatasetThe ADaM Basic Data Structure (BDS)ADAE – Adverse Event Analysis DatasetsADTTE – The Time-to-Event Analysis DatasetChapter Summary

Chapter 8: SDTM Validation
SAS Clinical Standards ToolkitSAS Clinical Standards Toolkit SetupSAS Clinical Standards Toolkit Validation ProgramSAS Clinical Data IntegrationOpenCDISC ValidatorInstalling OpenCDISC ValidatorRunning OpenCDISC Validator (Graphical User Interface)Evaluating the Report File and Report ResultsModifying the Configuration FilesRunning OpenCDISC Validator in Command Line ModeChapter Summary
Chapter 9: Validating ADaM Data
ADaM’s Published Validation ChecksOpenCDISC ValidatorRunning the OpenCDISC Validator as a MacroTraceability ChecksChapter Summary
Chapter 10: CDISC Data Review and Analysis
Safety Evaluations with JMP ClinicalGetting Started with JMP ClinicalSafety AnalysesPatient ProfilesCustomizing JMP ClinicalOne PROC Away with ADaM DatasetsChapter Summary
Chapter 11: Integrated Data and Regulatory Submissions
Regulatory GuidanceData Integration ChallengesData Integration StrategiesRepresenting Subjects Who Appear in Multiple Studies in Subject-Level DatasetsDeciding on Which Data to IntegrateCoding Dictionary IssuesSummary of Data Integration StrategiesData Integration and Submission ToolsSetting Variable Lengths Based on the Longest Observed ValueConverting from Native SAS to Version 5.0 Transport FilesConverting from Version 5.0 Transport Files to Native SASGetting Submission ReadyChapter Summary
Chapter 12: Other Topics
Standard for Exchange of Non-Clinical DataHL7 MessagingBRIDG ModelProtocol Representation ModelFDA Janus Clinical Trials RepositoryCDISC Model VersioningFuture CDISC DirectionsChapter Summary
Appendix A: Source Data Programs
adverse Datasetdemographics Datasetdosing Datasetlaboratory Datasetpain scores Dataset
Appendix B: SDTM Metadata
Appendix B.1 - Table of Contents MetadataAppendix B.2 - Variable-Level MetadataAppendix B.3 - Codelist MetadataAppendix B.4 - Value-Level MetadataAppendix B.5 - Computational Method MetadataAppendix B.6 - Define Header Metadata
Appendix C: ADaM Metadata
Appendix C.1 - Define Header MetadataAppendix C.2 - Table of Contents MetadataAppendix C.3 - Variable-Level MetadataAppendix C.4 - Parameter-Level MetadataAppendix C.5 - Computational Method MetadataAppendix C.6 - Codelist MetadataAppendix C.7 - Analysis Results MetadataAppendix C.8 - External Links Metadata
Appendix D: %make_define SAS Macro
%make_define SAS MacroAdditional SAS Code Comments
Index

Content preview from Implementing CDISC Using SAS

Appendix A: Source Data Programs

This appendix presents Base SAS programs that you can run to generate the source data for the SDTM datasets. The trial design dataset source data are available as a Microsoft Excel file called trialdesign.xlsx that can be downloaded from the author page for this book. See support.sas.com/publishing/authors/index.html.

adverse Dataset

demographics Dataset

proc format; value trt 1 = "Active" 0 = "Placebo"; value gender 1 = "Male" 2 = "Female"; value race 1 = "White" 2 = "Black" 3 = "Other"; ...

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Implementing CDISC Using SAS

by Chris Holland, Jack Shostak