SDTM - The General Domain Classes

The General Domain Classes

Most observations collected during the study (other than those represented in special purpose domains) should be divided among three general observation classes: Interventions, Events, or Findings:

• The Interventions class captures investigational treatments, therapeutic treatments, and surgical procedures that are intentionally administered to the subject (with some actual or expected physiological effect) either as specified by the study protocol (e.g., “exposure”), coincident with the study assessment period (e.g., “concomitant medications”), or other substances self-administered by the subject (such as alcohol, tobacco, or caffeine)
• The Events class captures occurrences or incidents independent of planned study evaluations occurring during the trial (e.g., 'adverse events' or 'disposition') or prior to the trial (e.g., 'medical history').
• The Findings class captures the observations resulting from planned evaluations to address specific questions such as observations made during a physical examination, laboratory tests, ECG testing, and sets of individual questions listed on questionnaires.

In most cases, the identification of the general class appropriate to a specific collection of data by topicality is straightforward. Often the Findings general class is the best choice for general observational data collected as measurements or responses to questions. In cases when the topicality may not be as clear, the choice of class may be based more on the scientific intent of the protocol or analysis plan or the data structure.

All datasets based on any of the general observation classes share a set of common Identifier variables and Timing variables. Three general rules apply when determining which variables to include in a domain:

• The same set of Identifier variables applies to all domains based on the general observation classes. An optional identifier can be used wherever appropriate.
• Any valid Timing variable is permissible for use in any submission dataset (such as to describe studies with more precise time points such as a Pharmacokinetics trial), but it should be used consistently where applicable for all domains.
• Any additional Qualifier variables from the same general class may be added to a domain model.