New to CDISC      

After learning clinical data, the next logical step is to learn CDISC, Clinical Data Interchange Standards Consortium.  Both pharma and medical device SAS programmers can benefit from this page.  See also New to Clinical Data, CDISC Programming, CDISC 101 Mapping Training videos, Statistical Analysis and New to SAS® Programming.  See Introduction to CDISC on SAS Savvy webinar and Pinnacle 21 Demo webinar.  Common Data Models for clinical data.

• Welcome to CDISC
• CDISC Glossary
• Annotated Case Report Forms
• Introduction to CDISC
• Compare SDTMs
• Compare SDTMs and ADaMs
• Clinical Programmer Duties
• SAS White Papers 
• General SAS Papers

Welcome to CDISC

  

CDISC Primer (Introduction Videos on SEND, CDASH, SDTMIG, ADaMs)

CDISC Glossary (CDISC Blog) (Top)

Annotated Case Report Form (CRF) (Top)

Introduction to CDISC (Blog) (Top) 

• MindMap: Clinical Process Flow, CDISC, Control Terminology  
• Specifications: SDTMs, ADaMs
• Timeline: Start study, End study, SDTMs/ADaMs, Database lock and TLGs  
• SAP: Statistical Analysis Plan, Template
• CRF: Case Report Forms, Randomized Controlled Trial 

• TLGs Table Shells: Tables, Lists and Graphs, QC Checklist

  
  

Compare SDTMs

   

Compare SDTMs and ADaMs

  

   

Clinical Programmer Duties (Top)

Responsible for building programs to create SAS datasets from the clinical database, external data sources, and other sources while following the clinical study's protocol or statistical plans.

1. Primary responsibilities
2. Build SAS datasets from clinical database.
3. Develop SAS macros, templates and utilities for data cleaning and reporting.
4. Utilize SDTM guidelines to build datasets.
5. Communicate with an internal team to create deliverables for pharmaceutical and biotechnology clients.
6. Implement analyses specified in the protocol or the Statistical Analysis Plan (SAP) while working with the project statistician.
7. Ensure CRF meets the guidelines of the protocol and check for consistency and adequacy.
8. Write SAS programs to generate tables, listings, and figures and analysis datasets.
9. Review CRF annotations and data specifications.
10. Work in tandem with Biostatistics and Data Management member on various clinical projects.
11. Identify and edit checks per the data validation plan or data management plan.
12. Study management reports using SAS.
13. Validate the programmed analysis datasets, tables, listing and figures.
14. Perform analyses defined in the statistical analysis.
15. Prepare clinical and statistical summary reports.
16. Communicate with programming and statistics leads.
17. Utilize SAS programming skills within protocol team and perform all programming required for clinical trial analysis and reporting.
18. Perform quality control on final reports.
19. Develop SAS coding and table templates for preparing, processing and analyzing clinical data.
20. Establish monitoring of data transfers for ongoing trials to identify study conduct or data quality issues.

CDISC White Papers (Top)

1. Practical Methods for Creating CDISC SDTM Domain Data Sets from Existing Data, Robert Graebner [Tutorial, Comments]

2. Introduction - Introduction to the CDISC Standards, Sandra Minjoe

3. CDISC: Why SAS® Programmers Need to Know, Victor Sun

4. A Relational Understanding of SDTM Tables, John R. Gerlach, Glenn O’Brien [HOW]