SDTM Variables Classification by Role

Why SDTM variables are Organized by different Roles?

In clinical trials, data is collected from various sources and in different formats. This data needs to be standardized to make it easier to analyse and compare across different studies and organizations. The Study Data Tabulation Model (SDTM) is a standardized format for clinical trial data that provides a common structure and terminology for organizing data. Standardizing the data into a common format makes it easier to analyse, compare, and share the data across different studies and organizations.

Types of SDTM variables based on roles

There are basically five types of SDTM variables based on the roles and these are:

Identifier Variables: Identifier variables are used to uniquely identify each subject and each observation within a study.

These include:

•  Study ID: The identifier for the study.
• Site ID: The identifier for the site where the subject was enrolled.
• Subject ID: The identifier for the subject.
• Visit Number: The identifier for the specific visit or assessment that the data pertains to.
• Arm or Treatment Group: The identifier for the group that the subject was assigned to.

Timing Variables: These variables capture the date and time of observations and provide information on the timing of study events.

These include:

• Start Date: The start date of a study or a specific period of time within a study.
• End Date: The end date of a study or a specific period of time within a study.
• Date of Enrollment: The date when a subject was enrolled in the study.
• Date of Randomization: The date when a subject was randomized to a treatment group.
• Date of the First Dose: The date when the subject received the first dose of treatment.

Qualifier Variables: Qualifier variables provide additional information about the observation or measurement being captured.

These include:

• Test Code: The code for the laboratory test or procedure that was performed to obtain the result being reported.
• Units of Measure: The units of measure that were used to report the result.
• Reference Range: The reference range for the result being reported.
• Result Qualifier: A code that indicates the quality or validity of the result being reported.
• Assay ID: The identifier for the assay used to perform the laboratory test or procedure.

Rule Variables: Rule variables define the processing rules and derivations for other variables in the dataset.

These include:

• Derivation Rule: A rule that describes how a variable was derived from other variables in the dataset.
• Imputation Method: A code that describes the method used to impute missing data.
• Method Code: A code that describes the method used to collect or process the data.

Topic Variables: Topic variables provide additional information about the data being captured.

These include:

• Project Name: The name of the project that the study is part of.
• Comment: A free-text field for comments or notes about the data.
• Domain: The name of the domain to which the variable belongs.
• Dataset Name: The name of the dataset that the variable belongs to.
• Variable Name: The name of the variable.

Order of variables in SDTM domains

The order of variables in SDTM generally follows this order:

1. Identifier Variables
2. Topic Variables
3. Timing Variables
4. Qualifier Variables
5. Result Variables

The Trick to Learn Order if SDTM variable

To remember this acronym, you can use the following phrase:

"I Tend To Qualify Results"

Each letter in the phrase corresponds to the first letter of each variable role in the order they appear in the acronym.

E.g., Identifier Variables come first, followed by Timing Variables, Qualifier Variables, Rule Variables, and Topic Variables.