Role | Specifies Specifies the role of the variable in the resulting dataset including information conveyed by the variable in the context of a data record and how it the variable can be used. Values in this column are: - Identifier for variables which identify the study, subject, domain, pool identifier, and sequence number of the record.
- Topic for variables which specify the focus of the data record.
- Qualifier variables include additional illustrative text or numeric values that for variables which describe the results or additional traits of the observation (e.g., units, descriptive adjectives).
- Rule variables express an algorithm or executable method to define start, end, and branching or looping conditions in the Trial Design Model datasets.
- Timing for variables which describe the timing of the observation (e.g., start date and end date).
The set of qualifier variables can be further categorized into 5 subclasses: - Grouping qualifiers are used to group together a collection of observations within the same domain. Examples include --CAT and --SCAT.
- Result qualifiers describe the specific results associated with the topic variable in a Findings dataset. They answer the question raised by the topic variable. Result qualifiers include --ORRES, --STRESC, and --STRESN.
- Synonym qualifiers specify an alternative name for a particular variable in an observation. Examples include --MODIFY and --DECOD, which are equivalent terms for a --TRT or --TERM topic variable, and --TEST, which is an equivalent term for a --TESTCD.
- Record qualifiers define additional attributes of the observation record as a whole (rather than describing a particular variable within a record). Examples include AGE, SEX, SPECIES, and STRAIN in the Demographics (DM) domain and --REASND, --BLFL, --LOC, --SPEC, and --NAM in a Findings domain.
- Variable qualifiers are used to further modify or describe a specific variable within an observation and are only meaningful in the context of the variable they qualify. Examples include --ORRESU, --ORNRHI, and --ORNRLO, all of which are variable qualifiers of --ORRES, and --DOSU, which is a variable qualifier of --DOSE.
SDTM The SDTMIG for Human Clinical Trials is based on the SDTM’s general framework for organizing clinical trial information that is to be submitted to regulatory authorities. The SDTM is built around the concept of observations collected about subjects who participated in a clinical study. Each observation can be described by a series of variables, corresponding to a row in a dataset. Each variable can be classified according to its role. A role determines the type of information conveyed by the variable about each distinct observation and how it can be used. Variables can be classified into 5 major roles: - Identifier variables, such as those that identify the study, subject, domain, and sequence number of the record
- Topic variables, which specify the focus of the observation (e.g., the name of a lab test)
- Timing variables, which describe the timing of the observation (e.g., start date and end date)
- Qualifier variables, which include additional illustrative text or numeric values that describe the results or additional traits of the observation (e.g., units, descriptive adjectives)
- Rule variables, which describe the condition to start, end, branch, or loop in the Trial Design Model
The set of Qualifier variables can be further categorized into 5 subclasses: - Grouping Qualifiers are used to group together a collection of observations within the same domain. Examples include --CAT and --SCAT.
- Result Qualifiers describe the specific results associated with the topic variable in a Findings dataset. They answer the question raised by the topic variable. Result Qualifiers are --ORRES, --STRESC, and --STRESN.
- Synonym Qualifiers specify an alternative name for a particular variable in an observation. Examples include ‑‑MODIFY and --DECOD, which are equivalent terms for a --TRT or --TERM topic variable, and --TEST and ‑‑LOINC, which are equivalent terms for a --TESTCD.
- Record Qualifiers define additional attributes of the observation record as a whole (rather than describing a particular variable within a record). Examples include --REASND, AESLIFE, and all other serious adverse event (SAE) flag variables in the AE domain; AGE, SEX, and RACE in the DM domain; and --BLFL, --POS, --LOC, --SPEC and --NAM in a Findings domain
- Variable Qualifiers are used to further modify or describe a specific variable within an observation and are only meaningful in the context of the variable they qualify. Examples include --ORRESU, --ORNRHI, and ‑‑ORNRLO, all of which are Variable Qualifiers of --ORRES; and --DOSU, which is a Variable Qualifier of ‑‑DOSE.
For example, in the observation, "Subject 101 had mild nausea starting on study day 6," the Topic variable value is the term for the adverse event, "NAUSEA". The Identifier variable is the subject identifier, "101". The Timing variable is the study day of the start of the event, which captures the information, "starting on study day 6," whereas an example of a Record Qualifier is the severity, the value for which is "MILD". Additional Timing and Qualifier variables could be included to provide the necessary detail to adequately describe an observation.
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