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Clinical studies on subjects are typically conducted to evaluate the impact of tobacco products on individual health. Clinical reports are written on these studies and may be included in Product Applications to health authorities. These clinical reports typically follow Good Clinical Practice guidelines and the clinical reports follow ICH: Guideline for Industry Structure and Content of Clinical Study Reports. 

CDISC Tobacco Product Standards have been developed in this guide and described in Section X.  These CDISC Tobacco Product Standards  are used in this section. 

This section provides recommendations for reporting data commonly collected in studies which evaluate the impact of tobacco on an individual's health. .  

These  CDISC Tobacco Product Standards are based on the SDTM Model. The SDTM model has been designed to represent the broadest range of human and animal study data in a standardized manner.  This SDTM Model document  ( REF ) describes the basic concepts and general structure of the model. Individual implementation guides (IGs) have also been created to provide detail specification and recommendations for representing  data commonly collected. The Study Data Tabulation Model Implementation Guide for Human Clinical Trials (SDTMIG) https://www.cdisc.org/standards/foundational/sdtmig provides useful guidelines for creating data tabulations for Human Clinical Trials. Since, data tabulations and clinical study reports on tobacco products are operationally similar to data tabulations and clinical study reports prepared for Human Clinical Trials, this SDTMIG was also employed in developing this section.  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 study 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 a the study should be represented according to one 1 of the 3 SDTM general observation classes. Within these classes, observations about study subjects are represented in a series of domains. A domain is defined as a collection of logically related observations with a common topic. 

This section describe basic assumptions,, and provides numerous examples for reporting the individual subject data using CDISC Tobacco Standards; a format that facilitates data review.  

, 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.  

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Warning
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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