Study Data Tabulation Model Implementation Guide - W3

1 CDISC SDTM Implementation Guide (SDS Version ) CDISC, 2004. All rights reserved Page 1 Final July 14, 2004 Study Data Tabulation Model Implementation Guide : Human Clinical Trials Prepared by the CDISC Submission Data Standards Team Notes to Readers This is the approved Implementation Guide for Version 1 of the CDISC Study Data Tabulation Model This Implementation Guide comprises version of the Submission Data Standards. Revision History Date Version Summary of Changes 2004-06-25 Document Version Released version reflecting all changes identified during comment periods. 2004-07-14 Document Version Corrects minor typos and errors in sections , , , , , , CDISC SDTM Implementation Guide (SDS Version ) Page 2 CDISC, 2004. All rights reserved July 14, 2004 Final CONTENTS 1 ORGANIZATION OF THIS RELATIONSHIP TO PRIOR CDISC HOW TO READ THIS Implementation SUBMITTING 2 FUNDAMENTALS OF THE SDTM.

2 9 OBSERVATIONS AND DATA S E T S AND SPECIAL-PURPOSE 11 THE GENERAL DOMAIN 11 THE CDISC STANDARD DOMAIN CREATING A NEW How to Include Variables in New Domains (Steps 4 through 6)..15 3 SUBMITTING DATA IN STANDARD FORMAT ..16 STANDARD METADATA FOR DATASET CONTENTS AND USING THE CDISC DOMAIN MODELS IN REGULATORY CDISC Submission Dataset Definition Metadata ..17 CDISC Submission Value-Level Metadata ..19 4 ASSUMPTIONS FOR DOMAIN MODELS ..21 GENERAL ASSUMPTIONS FOR ALL General Dataset Assumptions ..21 General Variable Assumptions ..22 Coding and Controlled Terminology Assumptions ..23 Actual and Relative Time Assumptions ..25 Other Assumptions ..30 5 MODELS FOR SPECIAL PURPOSE DOMAINS.

3 35 Demographics Domain Model DM ..35 Assumptions for Demographics (DM) domain Model ..37 Comments Domain Model Assumptions for Comments (CM) domain Model ..39 6 DOMAIN MODELS BASED ON THE GENERAL CLASSES ..40 Concomitant Medications CM ..40 Assumptions for Concomitant Medications (CM) domain Model ..43 Exposure EX ..45 Assumptions for Exposure (EX) domain Model ..47 Substance Use - Assumptions for Substance Use (SU) domain Model ..51 Adverse Events AE ..53 Assumptions for Adverse Events (AE) domain Model ..57 Disposition DS ..59 Assumptions for Disposition (DS) domain Model ..60 CDISC SDTM Implementation Guide (SDS Version ) CDISC, 2004. All rights reserved Page 3 Final July 14, Medical History MH ..62 Assumptions for Medical History (MH) domain Model .

4 64 ECG Test Results EG ..66 Assumptions for ECG (EG) domain Model ..69 Inclusion/Exclusion Exceptions IE ..70 Assumptions for Inclusion/Exclusion Exceptions (IE) domain Model ..71 Laboratory Test Results Physical Examinations Assumptions for Physical Examinations (PE) domain Questionnaires Subject Characteristics SC ..82 Assumptions for Subject Characteristics (SC) domain Model ..83 Vital Signs VS ..84 7 TRIAL DESIGN PLANNED ELEMENTS, ARMS, AND Trial Elements ..88 Trial Arms ..89 Trial Visits ..90 SUBJECT ELEMENTS AND Subject Subject TRIAL Identifying Trial Developing the Trial Arms Table ..95 Distinguishing between Branches and Trial Epoch Concept.

5 101 Rules concept ..106 Recap of Trial Arms Variables ..106 Truncated Arms ..107 TRIAL Identifying Trial Elements ..109 Developing the Trial Elements Table .. 110 Recap of Trial Elements Variables .. 112 Distinguishing Elements from Epochs .. 112 TRIAL 113 Identifying Trial Visits .. 113 Developing the Trial Visits Table .. 113 Recap of Trial Visits Variables .. 114 SUBJECT Identifying Subject Elements .. 115 Unplanned Elements .. 115 Deriving SE End Date/Times .. 115 Recap of Subject Elements 116 Using Subject Elements Data to Place Subject Data within an Element or Epoch .. 116 SUBJECT 116 Identifying Subject Visits .. 116 Recap of Subject Visits 117 TRIAL INCLUSION/EXCLUSION 117 HOW TO Model THE DESIGN OF A CLINICAL 118 CDISC SDTM Implementation Guide (SDS Version ) Page 4 CDISC, 2004.

6 All rights reserved July 14, 2004 Final 8 REPRESENTING RELATIONSHIPS AMONG DATASETS OR RECORDS .. 119 RELATING GROUPS OF RECORDS WITHIN A --GRPID RELATING PEER RECORDS IN SEPARATE RELREC DATA S E RELREC Dataset RELATING DEPENDENT RECORDS IN DIFFERENT RELREC Split Datasets Example ..123 RELATING NON-STANDARD VARIABLE VALUES TO A PARENT SUPPQUAL Dataset ..124 SUPPQUAL Examples ..125 Examples of how to use the SUPPQUAL dataset are listed in the table below: ..125 Examples of data that should not be in the SUPPQUAL dataset include: ..126 RELATING COMMENTS TO A PARENT COMMENTS Example ..127 HOW TO DETERMINE WHERE DATA BELONG IN THE 9 Implementation EXAMPLES ..129 DEMOGRAPHICS EXAMPLE ..129 INTERVENTIONS EXAMPLES.

7 130 CM Example: Intermittent use of concomitant medications ..130 EX Examples: ..131 SU Examples:..134 EVENTS EXAMPLES ..140 AE Example: Mapping an AE CRF to CDISC AE ..140 DS MH Example: - Mapping a MH CRF to CDISC MH with multiple event records per subject ..144 FINDINGS EG Examples ..146 IE LB PE Examples ..151 QS SC Examples ..156 VS TRIAL DESIGN EXAMPLES ..159 10 APPENDICES ..165 CDISC SDS GLOSSARY OF STANDARDIZED AND RESERVED Reserved Domain Codes ..167 Electrocardiogram Test Codes (for measured or calculated parameters) ..169 Vital Signs Test Codes.

8 169 Supplemental Qualifiers Name Codes ..170 CDISC VARIABLE NAMING LESSONS LEARNED FROM THE CDISC SDTM Implementation Guide (SDS Version ) CDISC, 2004. All rights reserved Page 5 Final June 25, 2004 1 Introduction PURPOSE This document describes the CDISC Version ( ) Submission Data Standards (SDS), which have been prepared by the Submissions Data Standards team of the Clinical Data Interchange Standards Consortium (CDISC). Like its predecessors, is intended to Guide the organization, structure, and format of standard clinical trial Tabulation datasets submitted to a regulatory authority such as the US Food and Drug Administration (FDA). supersedes the Version Submission Data Domain Models document, which was approved by Health Level Seven (HL7) as an informative document in June 2003. This document should be used in close concert with the CDISC Study Data Tabulation Model (SDTM) available at and describes how to implement the SDTM for use with data tabulations submitted for human clinical trials.

9 The SDTM, which should be read before this Implementation Guide , describes a general conceptual Model for representing clinical Study data that is submitted to regulatory authorities. SDS provides specific domain models, assumptions, business rules, and examples for preparing standard datasets that are based on the SDTM. Tabulation datasets, which describe the essential data collected in a clinical trial, are one of four types of data currently submitted to the FDA along with patient profiles, listings, and analysis files. By submitting tabulations that conform to the standard structure, sponsors may benefit by no longer having to submit separate patient profiles or listings with a product marketing application. is not currently intended to meet the needs supported by analysis datasets, which will continue to be submitted separately in addition to the tabulations. The availability of standard submission data will provide many benefits to regulatory reviewers.

10 Reviewers can be trained in the principles of standardized datasets and the use of standard software tools, and thus be able to work with the data more effectively with less preparation time. Another benefit of the standardized datasets is to support the FDA s efforts to develop a repository for all submitted trial data and a suite of standard review tools to access, manipulate, and view the tabulations. Use of these data standards is also expected to benefit industry by streamlining the flow of data from collection through submissions, and facilitating data interchange between partners and providers. Note that the SDS represents an interchange standard, rather than a presentation format -- it is assumed that Tabulation data will be transformed by software tools to better support viewing and analysis. This document is intended for companies and individuals involved in the collection, preparation and, analysis of clinical data that will be submitted to regulatory authorities.