Quanticate Blog

CDASH Standards and Conformance in Clinical Data Management

Written by Clinical Data Management Team | Thu, May 16, 2024

Clinical research thrives on standardised processes, and one crucial aspect is the adherence to the Clinical Data Acquisition Standards Harmonization (CDASH). First developed in 2006, CDASH plays a vital role in establishing harmonized standards for the collection and submission of data from clinical studies. CDASH is a pivotal component of the Clinical Data Interchange Standards Consortium (CDISC), which was established in 1997 to ensure data in clinical research to be accessible, interoperable, and reusable by organizations analyzing safety and efficacy data for regulatory approvals.

 

What is CDASH?

The CDASH standards, developed within the framework of CDISC, are best practices for data collection, they help maximize data quality with the aim to streamline processes across the entire spectrum of medical research, from crafting clinical research protocols to reporting and regulatory submissions.

 

Why is CDASH important?

CDASH ensures a standard approach to capture data consistently across studies and reduces variability in data collection. These standards provide guidance on the needs of data capture and ensures the Case Report Form (CRF)/Electronic Case Report Form (eCRF) is designed with clear questions to produce consistent responses. These global CDASH standards on CRFs cover all therapeutic areas and phases of clinical trials.

 

Why are CDASH standards followed?

CDASH standards are highly recommended as they form a pre-requisite to the regulatory requirement of all clinical trial data to be submitted in CDISC’s Study Data Tabulation Model (SDTM) format. This 2006 regulatory requirement by the Food and Drug Administration (FDA) has grown in popularity amount other regulators who now require the same standards in place. This has resulted in over 500 organisations now being a part of CDISC and CDASH and SDTM being common practice.

Following CDASH standards enable Contract Research Organisations (CROs) and drug developers to standardise data collection formats and structures that provides clarity and traceability of data. The standardised CDASH data is submitted into SDTM which is a standard for organising and formatting data in the final CRF in a method that ensures it can be easily reviewed and reused. This provides more transparency to the regulators and data reviewers. The latest version of CDASH Model is v1.3 released in September 2023.

 

What are the objectives of CDASH?

  1. Integration into Clinical Workflow

CDASH supports the seamless integration of research into the clinical workflow, fostering effective partnering and information exchange between clinicians and researchers. This integration is essential for attracting more clinicians to engage in research activities, provided the process is streamlined within their existing workflow.

  1. Global CRF Standards

CDASH aims to develop content standards for a basic set of global, industry-wide Case Report Form (CRF) fields. These standards are designed to be applicable across various therapeutic areas and phases of clinical development, spanning Phases I to IV.

 

What is the difference between CDASH and SDTM?

CDASH and SDTM are both critical components of the CDISC framework, but they serve different purposes in the management and analysis of clinical trial data. CDASH is focused on the early stages of data collection where it provides guidelines and standards for designing case report forms (CRFs) in clinical trials with the goal of standardizing the data collection process. Whereas SDTM is used at a later stage and deals with the organizing and formatting of clinical trial data. After data has been collected using CDASH guidelines, SDTM provides a standardized structure for submitting data to regulatory bodies, so it is easier for reviewers to understand, analyse and make decision. In summary, CDASH ensure the data collected is standardised and efficient, SDTM structures and organizes this data in a universally understandable format, facilitating its review and analysis in later stages of the drug approval process.

 

What happened to standardisation of data pre-CDASH, and what’s the difference?

Prior to implementation of CDASH standards, question text and variable names in CRFs/eCRFs differed across protocols and sponsors. The same questions would be asked in various ways with different defined variable names and there was a lack of standardization. This resulted in challenges when updating data cleaning programs, and difficulties with the SDTM programs that were required for validating data and presenting data in suitable structures for review and submission requirement. This variability was greatly reduced with the introduction CDASH standards, thus greatly reducing the effort required for data cleaning and SDTM programming.

 

The benefits of CDASH

As mentioned, there are benefits to CDASH as standardizing study data at the point of data collection and CRF design results in a more efficiency data analysis process. CDASH standards describe common best practices to develop CRFs/eCRFs instead of following your own bespoke standards, this helps in collecting data consistently across studies. This further aids in producing data in SDTM format for submission purpose. This allows regulators to view submission data more accurately when it is all standardize and can review submission packages more efficiently as able to identify concerns or make approvals faster, this overall benefits the industry with a more efficient time in bringing drugs to market which benefits patients. In addition, you can remove the duplication of trials and post marketing evaluation which improves patient centricity.

CDASH standards provide guidance for development of data collection tools which are clear, understandable, and precise without any ambiguity. Following CDASH standards ensures traceability of trial data from the time the data is collected from site till the data is ready for final analysis and regulatory submission. This ensures the integrity of source data is maintained to support a trial’s outcome/findings from data.

CROs can further save on time required for setting up of new studies following the CDASH standards as most of the data collection and associated programming can be standardised across studies.

 

CDASH Guidelines and resources

CDISC have several guidance documents and resources to help with ensuring CDASH compliance. These include:

  • CDISC is consistent in releasing implementation guidelines for all its standards and this is also true of CDASH with the Clinical Data Acquisition Standards Harmonization Implementation Guide (CDASHIG). These official guidelines define the standardizes methods required for collecting the data consistently and have examples on how to implement the CDASH standards on your CRFs.
  • Therapeutic Area User Guides (TAUGs) defines data that is relevant to specific disease indications to help ensure there are standardised disease-specific metadata across all TAs and has some great examples and advice on applying these TA specific CDISC standards.
  • Controlled Terminology offers code lists and valid values for data items within CDISC-defined datasets, enhancing the efficiency and flexibility of the data collection process.

 

CDASH Conformance Rules

Understanding the importance of CDASH conformance is key for professionals involved in clinical trials, including Clinical Investigators, Medical Monitors, Clinical Research Associates, Clinical Data Managers, Biostatisticians, and others tasked with managing and analysing clinical trial data.

The defined CDASH conformance rules in place describe how to conform to the CDASH standard in such a way that the harmonization with SDTM is maintained.

  1. Tier I Level

At the individual CRF level, conformance is evaluated by ensuring the presence of highly recommended and relevant Recommended/Conditional fields for the CDASH domain required by the study. CDASH provides flexibility, allowing studies to include only the domains needed, with special considerations for protocol-specific prompts, languages, and cultural variations.

  1. Tier II Level

Operational implementation of CDASH standards takes center stage at this level. Meeting Tier I conformance rules is a prerequisite, and additional requirements focus on CDASH naming conventions. The goal is to achieve end-to-end traceability of variable names from the data capture system to the SDTM datasets, enhancing efficiency in data mapping, warehouse building, and data sharing between partners.

 

CDASH Naming Conventions

CDASH naming conventions are the guidelines for naming the data collection field on the CRF. The guidelines typically involve the use of clear, descriptive names, adherence to specific prefixes and suffixes, and the application of uniform formats for dates, times, and other data types. Understanding of SDTM and referencing CDASH standards and SDTMIG v3.1.3  Appendices is crucial for effective variable naming.

 

Challenges in Electronic Patient Reported Outcomes (ePRO)

With digital technologies becoming more popular due to a rise in virtual trials, this presents challenges due to lack of standardisation in studies with ePRO (Electronic Patient Reported Outcomes) datasets. Currently ePRO design is not abided by standards to be followed and therefore data models vary by eCOA (Electronic Clinical Outcome Assessment) provider and by the sponsor.

With the number of studies using ePRO and eCOA for study data collection, the requirement to set up and follow the CDASH/CDISC standards in recommended.

 

Standardisation with eSource

With growing clinical trial costs and a rise in reducing on-site monitoring with various techniques such as risk based monitoring, eSource has grown in popularity to transmit data directly from electronic health records (EHRs). This results in the potential for more data variations going into your EDC system. Researchers such as Rocca and the University of California have been attempted to incorporated structured data in this process CDASH mappings to support with standardizing data from eSource and EHR systems. This research helped to contribute to a SCDM’s guide on implementing eSource.

 

Conclusion

To summarize, CDASH standards have build the foundation required for presentation of data in CDISC compliant structure and SDTM. The standards have revolutionized the way clinical data is managed, presented, and submitted thus enhancing the quality and efficiency required in clinical research and drug development cycle including; clinical trials conduct, data validation & analysis, and regulatory review process. CDASH conformance is a critical aspect of clinical studies, ensuring standardized data collection and submission processes. Professionals involved in clinical trials must grasp the nuances of CDASH conformance levels to enhance the efficiency and integrity of clinical trial data.