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WORK IN PROGRESS

What to Expect from a TA Standard

A TA standard typically provides advice, examples, and explanations related to the use of the Clinical Data Acquisition Standards Harmonization (CDASH) model, the Study Data Tabulation Model (SDTM), and/or the Analysis Data Model (ADaM), and the implementation guides for each in the context of human clinical trials.

Advice might include:

  • Guidance on which domains and datasets to use in collecting and storing data

  • Guidance on which variables to use to represent data items
  • Guidance on the definition of non-standard (supplemental) variables, when the currently defined standard variables are insufficient for the task
  • Guidance on relating data across domains and datasets

Examples might include:

  • Annotated sample case report forms (CRFs) compliant with CDASH

  • CDASH metadata associated with the sample CRFs

  • Examples of SDTM datasets, with text describing the situational context and pointing out records of note

  • Sample analysis datasets compliant with ADaM, with dataset- and variable-level metadata

  • Table shells, mock reports, and diagrams illustrating the kinds of statistical analysis that can be performed based on the ADaM datasets

Explanations might include:

  • Discussion of why and how the standards were applied as shown in the examples, including clinical background relevant to modeling decisions
  • Diagrams (concept maps) that illustrate clinical processes, concepts, and/or relationships among data items
  • Where applicable, links to proposed additions to foundational standards (e.g., proposed new domains or variables)

Additional content might include:

  • Links to Biomedical Concepts for some core TA data (these are maintained in SHARE, which is the authoritative source)
  • Links to patient-oriented resources about the TA, so that readers may familiarize themselves with the TA
  • A brief clinical discussion of some of the more central¹ concepts to the TA, to aid those handling the data (e.g., data managers, statisticians, programmers) recognize the concepts and apply CDISC standards appropriately. Such a discussion might include the way in which the concept is relevant to the TA, the clinical situations from which data for the concept might arise, and the guise(s) in which the data might appear.

A TA standard does not include:

  •  Advice on what data to collect or how to analyze it
  •  Information and advice already included in the foundational standards
  •  Definitive controlled terminology
  •  Implementation advice and terminology for questionnaires, ratings, or scales
  •  Regulatory guidance or advice
  •  Clinical advice

Remember...

CDISC standards specify how to structure the data to support efficient data sharing for regulated clinical trials.

CDISC standards do not specify what data should be collected or how to conduct clinical trial protocols, assessments, or endpoints.

What is CDISC?

The Clinical Data Interchange Standards Consortium (CDISC) is a global, open, multidisciplinary, non-profit organization that has established standards to support the acquisition, exchange, submission, and archive of clinical research data and metadata. CDISC standards aim to enhance the harmonization of clinical data and streamline research processes. All CDISC standards are vendor-neutral, platform-independent, and freely available via the CDISC website.

The CDISC mission is to develop and support global, platform-independent data standards that enable information system interoperability to improve medical research and related areas of healthcare. The CDISC vision is to inform patient care and safety through higher quality medical research.

What is CFAST?

The Coalition for Accelerating Standards and Therapies (CFAST) is a collaborative initiative formed to accelerate clinical research and medical product development by facilitating the establishment and maintenance of data standards, tools and methods for conducting research in therapeutic areas that are important to public health. The goal of the CFAST initiative is to identify a core set of clinical therapeutic area concepts and endpoints for targeted therapeutic areas and translate them into CDISC standards to improve semantic understanding, support data sharing and facilitate global regulatory submission. Additional information, including a list of contributing organizations, can be found at: http://www.cdisc.org/cfast.

What is NCI EVS?

The U.S. National Cancer Institute (NCI) Enterprise Vocabulary Services (EVS) is CDISC's partner in developing controlled terminology for use alongside CDISC standards.

Since 1997, EVS has provided terminology content, tools, and services to accurately code, analyze and share cancer and biomedical research, clinical and public health information. EVS works with many partners to develop, license and publish terminology, jointly develop software tools, and support harmonization and shared standards. The NCI Thesaurus (NCIt) is EVS's core reference terminology and biomedical ontology.

CDISC controlled terminology is available at: http://www.cancer.gov/cancertopics/cancerlibrary/terminologyresources/cdisc.

What is a TAUG?

"TAUG" is the prefix for the short name (and file name) for a TA standard. Working backwards: "G" stands for "guide", because the document's purpose is to function as a how-to; "U" stands for "user", which indicates the target audience; and "TA" stands for "therapeutic area", because the document focuses not on a specific foundational standard, but on a specific therapeutic area. In short: “TAUG” stands for “therapeutic area user guide”, an informative data standard that focuses on a specific therapeutic area.

What are foundational standards?

 

What are Biomedical Concepts?

A Biomedical Concept (BC) is a unit of knowledge, created by a unique combination of the characteristics that define observations of real world phenomena in clinical research and/or healthcare, which represents biomedical knowledge that borrows from medical knowledge, statistical knowledge, BRIDG, and the CDISC standards. Metadata for biomedical concepts include the properties of the data items that are parts of the concepts, controlled terminology for those data items, and the ways in which the concepts relate to each other.

What are Concept Maps?

Concept maps are graphical tools for organizing and representing knowledge. They include concepts, usually enclosed in circles or boxes of some type, and relationships between concepts indicated by a connecting line linking two concepts. Words on the line, referred to as linking words or linking phrases, specify the relationship between the two concepts. We define concept as a perceived regularity or pattern in events or objects, or records of events or objects, designated by a label.

– From the introduction to What is a Concept Map?, by Alberto J. Cañas & Joseph D. Novak. Read the rest here.

The concept maps in CDISC standards use the following coding for the classification of concepts:

This classification is based on classes in the Biomedical Research Integrated Domain Group (BRIDG) model (available at http://bridgmodel.nci.nih.gov/). These color-symbol pairs have been used to highlight kinds of things that occur commonly in clinical data and therefore give rise to common patterns of data. Concepts whose class does not have an assigned code have a thinner, black outline, and no accompanying symbol. These may include the subject of an observation, as well as characteristics, or attributes, of the coded concepts.

 


¹ To the best of the team's knowledge. As CDISC is not comprised of clinical experts, the selection of concepts to cover, and any clinical discussion related to them, relies heavily on team clinicians, clinical and regulatory guidelines, academic works, and input from contributing organizations. Clinical guidelines, articles, and other works consulted by the team during the development of a standard are cited where appropriate, and a full list of works cited and consulted is usually included in the appendices, under "References".

STUFF TO FIND A PLACE FOR

CDISC data standards are living documents. Due differing update cycles, some of the modeling approaches and controlled terminology presented in the examples in a document may become outdated before the next version of the document is released.

When a particular type of data has existing CDISC standards that can be used without additional development or customization, it is not covered in special detail in subsequent standards.

Although the examples in CDISC data standards try to appear plausible, including using controlled terminology where available, they should not be regarded as a definitive source for controlled terminology. Some codelists and/or values applicable to biomedical concepts and data elements in a document may still be in development at the time of publication. Some examples may use values that appear to be controlled terminology, but which are actually generic or "best guess" placeholders. Readers should consult the current CDISC Controlled Terminology (available at: http://www.cancer.gov/cancertopics/cancerlibrary/terminologyresources/cdisc) as the ultimate authority for correct controlled terminology codelists and values.

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