CDISC and their funding partner, the National Organization for Rare Disorders, have announced the public review of version 1.0 of the Rare Diseases Therapeutic Area User Guide (TAUG-Rare Diseases). This guide provides valuable insights and guidance for CDASH, SDTM, and ADaM, specifically tailored to rare disease studies.
🔍 Key Insights for SAS Programmers:
1️⃣ Mapping Rare Disease-specific Data to SDTM Domains: Discover best practices for mapping unique and specific data from rare diseases to SDTM domains. Learn about the challenges and considerations that arise in this process and how to overcome them effectively.
2️⃣ Harmonizing and Standardizing Variables: Gain strategies to harmonize and standardize rare disease-specific variables across different studies. This ensures consistency in analysis and interpretation, facilitating meaningful comparisons.
3️⃣ Controlled Terminology for Accurate Representation: Explore the use of controlled terminology to ensure accurate representation of rare disease data. Learn how it can improve data quality, facilitate data sharing, and promote interoperability across studies.
4️⃣ Annotated Case Report Forms (aCRFs): Access sample annotated case report forms tailored specifically for rare disease studies. These examples can serve as valuable references to guide your data collection and mapping processes.
5️⃣ Implementing ADaM: Learn about best practices for implementing ADaM (Analysis Data Model) in the context of rare disease studies. Discover how utilizing ADaM can streamline your data analysis processes and support regulatory submissions.
🌟 Join the Public Review and Contribute:
Participating in the public review of TAUG-Rare Diseases v1.0 provides you with an opportunity to contribute your expertise and help shape the future of rare disease research. By sharing your insights and suggestions, you can ensure that the guide meets the needs of SAS Programmers and the rare disease research community.
📆 Public Review Timeline: Until 26 June 2023
Let’s come together and make a difference in rare disease research by providing valuable feedback on this user guide. Your contributions will play a significant role in advancing data standards and promoting high-quality, standardized data collection and analysis in the field of rare diseases. 🌍