Published on 17/11/2025

Working With Standard and Custom Controlled Terminology in CDISC

The Clinical Data Interchange Standards Consortium (CDISC) has established critical frameworks for data management in clinical research. Controlled terminology plays a vital role in ensuring data integrity, consistency, and interoperability across diverse clinical trial environments. This tutorial provides a comprehensive guide for clinical operations, regulatory affairs, and medical affairs professionals on incorporating both standard and custom controlled terminology in the context of CDISC standards.

Understanding Controlled Terminology in CDISC

Controlled terminology refers to standardized vocabulary used to classify and define data elements consistently throughout clinical trials. In the context of CDISC, the two primary types of terminology are standard and custom. Understanding each is crucial for compliance with regulatory requirements and for facilitating effective data exchange.

Standard controlled terminology is predefined and maintained by CDISC. This terminology includes standard codes and definitions that must be used in studies adhering to CDISC frameworks like the Study Data Tabulation Model (SDTM) or the Analysis Data Model (ADaM). These terms help ensure that collected data are comparable and interpretable across different studies and data repositories.

Custom controlled terminology, on the other hand, allows for the addition of terms specific to a particular study or therapeutic area. This ability to customize enhances the flexibility required for innovative clinical trials—such as those exploring novel therapies, including clinical trials for dental implants—while maintaining a structure aligned with CDISC standards.

Choosing the Right Terminology: A Strategic Approach

When initiating a clinical trial, it is critical to identify which controlled terminology will be most appropriate for the study design. Employing a robust strategy for selecting controlled terminology involves several key steps:

Step 1: Identify the Clinical Objectives – Understand the primary goals of the clinical study. Are you measuring efficacy, safety, or both? The objectives will guide terminology choices.
Step 2: Consult CDISC Standards – Review the latest versions of the CDISC SDTM and ADaM specifications. Ensure you are using the relevant standard terminology that aligns with these guidelines.
Step 3: Engage Stakeholders – Involve biostatisticians, data managers, and clinical investigators early in the process. Their insights can help identify necessary custom terms.
Step 4: Conduct Terminology Mapping – Map clinical terms to the controlled vocabulary. Ensure that both standard and custom terms are correctly aligned with the data collection instruments.
Step 5: Validate Terminology – Before finalizing the protocol, validate the selected terms with cross-functional areas to confirm their appropriateness for regulatory submissions and data analysis.

Implementing Controlled Terminology in Clinical Trials

Once terminology has been identified and validated, the next phase of implementation can commence. This includes data collection, management, and preparation for submission to regulatory authorities. The following steps outline this integration:

Step 1: Develop Data Collection Instruments – Design Case Report Forms (CRFs), electronic data capture (EDC) systems, and other data collection tools that incorporate the selected controlled terminology. This ensures data are collected uniformly across all sites.
Step 2: Train Staff on Terminology – Conduct training sessions for data collectors and site investigators on the importance of using controlled terminology. Highlight the impact of consistent terminology on data integrity and regulatory compliance.
Step 3: Monitor Data Entry – Implement real-time data monitoring to check for conformance with controlled terms. Utilize data validation checks to prevent errors during data entry.
Step 4: Compile Datasets for Submission – When compiling datasets for regulatory submission, ensure that the datasets are fully aligned with the controlled terminology adopted during the study. This includes preparing submission-ready datasets that meet CDISC standards—essential for an EMA submission process.

Leveraging Custom Terminology: Best Practices

Custom controlled terminology is indispensable in studies that require unique language to clarify data elements not covered by standard terms. Its implementation, however, needs careful consideration. Here are best practices to follow:

Step 1: Define Clear Criteria for Customization – Establish criteria for when custom terminology will be used. This avoids unnecessary complexity in data management.
Step 2: Collaborate with CDISC Terminology Updates – Monitor updates to CDISC terminology regularly. Custom definitions that are superseded by standard terms should be retired or updated accordingly.
Step 3: Document All Custom Terms – Maintain thorough documentation of custom terms, including definition, context of use, and the reason for its inclusion. This documentation will serve as a guide for data analysts and regulatory bodies.
Step 4: Review Custom Terms with Regulatory Experts – Prior to study initiation, consult with regulatory affairs experts to ensure that the custom terms comply with relevant regulations.

Challenges and Solutions in Utilizing Controlled Terminology

Despite the clear advantages of using standard and custom controlled terminology, several challenges can arise during implementation. Some common issues and their solutions include:

Challenge 1: Inconsistent Usage of Terms – Mitigate this risk by enforcing stricter data entry protocols and regular training sessions for investigators.
Challenge 2: Lack of Familiarity with Custom Terms – Educate personnel on the importance and application of custom terms through comprehensive training workshops.
Challenge 3: Regulatory Scrutiny – Ensure preparation for regulatory focus on terminology by providing thorough documentation and validation for both standard and custom terminology during submissions.

Addressing these challenges proactively will support the smooth execution of clinical trials and maintain compliance with regulatory standards.

Navigating Regulatory Requirements: CDISC Compliance

To ensure compliance with both CDISC and regulatory requirements, professionals must be well-versed in the standards governing controlled terminology. Each regulatory authority has guidelines that govern the use of controlled vocabularies during clinical trials.

For instance, the FDA expects clinical data to adhere to CDISC standards to facilitate regulatory review. Similarly, the MHRA and EMA have established guidelines encouraging the harmonization of data formats, emphasizing the importance of controlled terminology adherence for data submissions.

Professionals involved in clinical operations must therefore maintain an ongoing relationship with regulatory bodies. Companies such as Axis Clinical Research provide resources and support, helping teams navigate the complexities of compliance.

Future Trends in Controlled Terminology and Data Management

The landscape of clinical research is evolving, with increasing reliance on real-time data and patient-centric approaches, including at-home clinical trials. With this evolution come new terminology challenges that must be addressed. Here are anticipated trends:

Trend 1: Increased Use of Artificial Intelligence – AI will increasingly play a role in clinical data management, including automating the assignment and validation of controlled terminology.
Trend 2: Expansion of Custom Terminology – As personalized medicine grows, the need for custom terms that address specific patient demographics and outcomes will become more prevalent.
Trend 3: Collaborative Data Standards Development – Global collaboration among organizations such as WHO and CDISC will result in more streamlined and widely accepted controlled terminology standards.

Conclusion: Maximizing Data Integrity Through Controlled Terminology

Incorporating standard and custom controlled terminology is pivotal in ensuring data integrity, regulatory compliance, and the efficacy of clinical trials. By following the outlined steps and best practices, clinical operations, regulatory affairs, and medical affairs professionals can navigate the complexities of controlled terminology effectively, enhancing the quality of clinical research.

Implementing effective strategies around controlled terminology not only streamlines data management processes but also fosters trust among stakeholders and regulatory agencies, paving a pathway toward successful clinical outcomes.