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.

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

SAS White Papers (Top)

1. CDISC Introduction Presentation

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]

5. SDTM What? ADaM Who? A Programmer’s Introduction to CDISC, Venita DePuy [Basic, Technical Screening, Inclusion/Exclusion]

6. An Introduction to SDTM ± 298 pages in 20 minutes?!, Jennie Guirk [Presentation]

7. Good Programming Practice [GPP] in SAS® & Clinical Trials, Srinivas Vanam, Manvitha Yennam, Phaneendhar Vanam [Programming Style]

8. Training Statistical Programmers on SAP Review Skills, Sascha Ahrweiler

9. A Programmer’s Guide to Statistical Procedures, Jim Edgington

10. Statistics for Clinical Trial SAS Programmers 1: paired t-test, Kevin Lee

11. Statistics: The Fourth Dimension of a “Statistical Programmer”, Gauri Khatu, Vibhavari Inamda

12. Oncology Trials 101 - The Basics and Then Some, Dave Polus

13. Clinical Trial Reporting Using SAS/GRAPH® SG Procedures, Susan Schwartz

14. Backpacking Your Way Through CDISC: A Budget-Minded Guide to Basic Concepts and Implementation, Rachel Brown, Jennifer Fulton [Definitions]

15. Tips for efficient CDISC eCRT production, Lanting Li, Yu Zhu, Huan Zhu [Unscheduled, Not Submitted, Checklist, Process, Define.xml]

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

General SAS Papers (Top)

1. Clinical Trials Terminology for SAS Programmers, Sy Truong

2. SAS® PROGRAMMER TO CLINICAL SAS PROGRAMMER, Gayatri Karkera, Neha Mohan [Phase I, II, III, IV, Endpoints]

3. Success As a Pharmaceutical Statistical Programmer, Sandra Minjoe, Mario Widel

4. THE ROLE OF SAS PROGRAMMERS IN CLINICAL TRIAL DATA ANALYSIS, Ming Wang

5. SAS® Programming for the Pharmaceutical Industry, Brian C. Shilling, Carol Matthews [QC]

6. The 5 Most Important Clinical SAS Programming Validation Steps, Brian Shilling

7. Pharmaceutical Programming: From CRFs to Tables, Listings and Graphs, a process
overview with real world examples Mark Penniston, Shia Thomas

8. Intro to Longitudinal Data: A Grad Student “How-To” Paper, Elisa Priest,Ashley Collinsworth

9. Longitudinal Data Techniques: Looking Across Observations, Ronald Cody

10. Pharma Company Questions and Answers, J.J. Hantsch

11. Careers in Biostatistics and Clinical SAS® Programming An Overview for the Uninitiated, Justina Flavin [Roles, Responsibilities]

12. Statistical Programming for Dummies [Presentation, Investigator’s Brochure (IB)]

13. Talking Past Each Other? How to Communicate with Medical Writers When Preparing Clinical Research Manuscripts for Journal Submission, Scott Thompson, Stephanie Thompson

14. Managing the Evolution of SAS® Programming, Carey Smoak

15. Empowering SAS® Programmers: The Role of the Manager, Carey Smoak

16. Skills for SAS® programmers in Epidemiology, Philip Holland [Presentation]

17. A Short Introduction to Longitudinal and Repeated Measures Data Analyses, Leanne Goldstein

18. The Baker's Dozen: What Every Biostatistician Needs to Know, AnnMaria De Mars [INCIDENCE, SENSITIVITY AND SPECIFICITY, RELATIVE RISK, RISK DIFFERENCE AND ODDS RATIO, FISHER’S EXACT TEST, MCNEMAR]

19. Expediting Access to Critical Pathology Data, Leanne Goldstein, Rebecca Ottesen, Julie Kilburn, Joyce Niland [Metastasis]

20. GCP101, Good Clinical Practices OR “Why we do What we do the Way we do it“, Elaine Dempsey

21. CLINICAL PROGRAMMING FOR NOVICE, Ramesh Ayyappath [Investigator’s Brochure (IB)]

22. Making of a Stat Programming Project Manager, Manjusha Gode, Ajay Sathe [Presentation] [Work-Life balance: Making it a reality]

23. Industry Standard Good Programming Practice for Clinical Trials (Using SAS), Mark Foxwell

24. Good Programming Practices at Every Level, Maria Dalton [Programming Style, TA]

25. The Anatomy of Clinical Trials Data: A Beginner’s Guide, Venky Chakravarthy [Glossary]

26. Stretching Data Training Methods: A Case Study in Expanding SDTM Skills, Richard Addy

27. The Super Genius Guide to Generating Dummy Data, Brian Varney

28. Producing a Format Library and Test Data for Case Report Forms using a Data Define Table

29. CRO, TLF, SOP? OMG!: A Beginner’s Guide to the Clinical Research Organization, Mandy Bowen, Otis Evans, Stephen Terry

30. THE ROLE OF SAS PROGRAMMERS IN CLINICAL TRIAL DATA ANALYSIS, Ming Wang