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STUDY DATA TABULATION MODEL

• SDTM (Study Data Tabulation Model) defines a standard structure for human clinical trial (study) data tabulations that are to be submitted as part of a product application to a regulatory authority such as the FDA

• The Submission Data Standards team of CLINICAL DATA INTER CHANGE STANDARDS CONSORTIUM(CDISC) defines SDTM

• 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 or table

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1. Identifier variables, which identify the study, subject of the observation, the domain, and the sequence number of the record

2. Topic variables, which specify the focus of the observation (such as the name of a lab test)

3. Timing variables, which describe the timing of the observation (such as start date and end date)

4. Qualifier variables, which include additional illustrative text, or numeric values that describe the results or additional traits of the observation (such as units or descriptive adjectives)

5. A fifth type of variable role, Rule, can express an algorithm or executable method to define start, end, or looping conditions in the Trial Design model

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QUALIFIER VARIABLES CAN BE FURTHER CATEGORIZED INTO FIVE SUB-CLASSES:

1. Grouping Qualifiers are used to group together a collection of observations within the same domain

2. Result Qualifiers describe the specific results associated with the topic variable for a finding. It is the answer to the question raised by the topic variable

3. Synonym Qualifiers specify an alternative name for a particular variable in an observation

4. Record Qualifiers define additional attributes of the observation record as a whole

5. Variable Qualifiers are used to further modify or describe a specific variable within an observation and is only meaningful in the context of the variable they qualify

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SUBMISSION METADATA MODEL USES SEVEN DISTINCT METADATA ATTRIBUTES

1. The Variable Name (limited to 8-characters for compatibility with the SAS system V5 Transport format)

2. A descriptive Variable Label, using up to 40 characters, which should be unique for each variable in the dataset

3. The data Type (e.g., whether the variable value is a character or numeric)

4. The set of controlled terminology for the value or the presentation format of the variable(Controlled Terms or Format)

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5. The Origin or source of each variable

6. The Role of the variable (Identifier, Topic, Timing, or the five types of Qualifiers)

7. Comments or other relevant information about the variable or its data

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GENERAL DOMAIN CLASSES:

• Most observations collected during the study should be divided among three general observation classes: Interventions, Events, or Findings

1.The Interventions class captures investigational treatments, therapeutic treatments, and surgical procedures that are intentionally administered to the subject

a.Concomitant Medications - CM

b.Exposure - EX

c. Substance Use - SU

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2.The Events class captures occurrences or incidents independent of planned study evaluations occurring during the trial or prior to the trial 

(e.g., 'adverse events' or 'disposition')

a. Adverse Events - AE

b.Disposition - DS

c. Medical History - MH

d.Protocol Deviations - DV

e.Clinical Events - CE

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3. 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.

a. ECG Tests - EG

b. Inclusion/Exclusion Exceptions - IE

c. Questionnaires - QS

d. Physical Examinations - PE

e. Pharmacokinetics Concentrations - PC

f. Subject Characteristics - SC

g. Vital Signs – VS etc.....

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REFERENCES

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1. CDISC Study Data Tabulation Model / Submission Data Domain Models, Version 3.1

2. CDISC Study Data Tabulation Model SDTM Implementation Guide V3.1.1

3. From Wikipedia, the free encyclopedia

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