Fundamentals of SDTM: Master Observations and Variables Today!

🌟Hey, friends! 🌟

Welcome to this week’s episode of Dr. Clinidata! I hope your week was epic! 🚀

This week let's dive into the basics of the Study Data Tabulation Model Implementation Guide (SDTMIG) and focus on a key area: observations and variables.

Observations in SDTM:

• An observation is a collection of data related to a subject who participated in a clinical trial.

• Each observation is made up of a series of variables.

Variables in SDTM:

• Variables are classified by their roles.

• A role determines what type of information needs to be conveyed by a variable about each distinct observation and how it can be used.

Understanding Variable Roles:

1) Identifier Variables:

• These helps identify the study, subject, domain, and sequence number of the record.

• e.g., STUDYID, USUBJID, DOMAIN, SEQ

2) Topic Variables:

• They specify the main focus of the observation, like the name of a lab test.

• e.g., --TERM, --DECOD

3) Timing Variables:

• These describe when the observation occurred, such as start and end dates.

• e.g., --STDTC, --ENDTC, --STDY, --ENDY, --DTC

4) Rule Variables:

• These outline conditions for starting, ending, or looping within the trial design.

• e.g., --STDTC, --ENDTC, --STDY, --ENDY, --DTC

5) Qualifier Variables:

• They provide extra details about the observation, such as units of measurement or descriptive terms.

• There are 5 different types of qualifiers:

5.1) Grouping Qualifiers:

• Used to group related observations within the same domain.

• e.g., --CAT and --SCAT

5.2) Result Qualifiers:

• Describe the outcome related to the topic variable.

• e.g., --ORRES or --STRESC.

5.3) Synonym Qualifiers:

• Provide alternative names for variables.

• e.g., ‑‑MODIFY and --DECOD, which are equivalent terms for a --TRT or --TERM topic variable

5.4) Record Qualifiers:

• Add attributes to the entire observation record.

• e.g., AGE, SEX, and RACE in the DM domain; and --BLFL, --

  POS, --LOC, --SPEC and --NAM in a Findings domain

5.5) Variable Qualifiers:

• Further modify specific variables within an observation.

• e.g., --ORRESU, --ORNRHI, and ‑‑ORNRLO, all of which are Variable Qualifiers of --ORRES; and --DOSU, which is a Variable Qualifier

  of ‑‑DOSE.

An example to illustrate:

Subject 505 had a systolic blood pressure of 120 mmHg and a diastolic blood pressure of 80 mmHg, measured in a seated position on study day 7.

In simple terms, think of each observation as a story about the subject, where each variable plays a role in telling that story clearly and precisely.

Stay tuned for more insights as we continue to unravel the intricacies of SDTM in upcoming newsletters!

CDISC SDTMIG 3.4

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