Studies involving a tobacco product may include assessments of pattern of product use, extent of exposure to toxicants and biological effects, abuse potential, and consumer perception of the product, as well as other physiological and subjective effects. This may include nicotine pharmacokinetics, questionnaires, and daily diaries to assess tobacco and nicotine use status, biomarkers of exposure as well as medical history, physical examination, and other routine data. These studies types include abuse liability studies, in-laboratory studies (subject uses the product once or a few times, but only in a laboratory setting), short-term studies (<2 weeks of duration on a particular product), intermediate-term studies (> 2 weeks and ≤ 12 months), or long-term studies (>12 months).
Most subject-level observations collected during the study should be represented according to 1 of the 3 SDTM general observation classes, and the special-purpose domains which represent data that do not fit any of the general observation classes. Given this, referring to both the CDASH Model when applicable and the SDTM is highly recommended when using domains to support understanding of intended scope and to inform extensions and creation of custom domains when needed. See also Section 2.1, How To Determine Where Data Belong, Section 2.7, Standards for Collection, and Section 2.8, Standards for Collection.
The examples in this section illustrate how to represent various aspects of studies involving a tobacco product using the CDASH Model and the SDTM, including
guidance on the use of domains and variables;
sample aCRFs;
- examples of SDTM datasets, with text describing the context and example records of note.
The domain specification tables include rows for all required and expected variables for a domain and for a set of permissible variables are most likely relevant. The permissible variables do not include all the variables that are allowed for the domain; they are a set of variables that are considered likely to be included.
It is important to note that the inclusion of concepts in this implementation guide should not be construed as a requirement to collect data on these concepts in any particular study. The examples included are intended to show how data of particular kinds can be represented using CDISC standards. The examples given are for guidance only and should not be over-interpreted .
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