Overview
The CDISC SDTM data structure combines all comments into a separate dataset.  It is common for clinical data to have comments stored along with the data in which it is collected.  It is therefore a common task to transform all the data contains comments into a separate SDTM data structure.  This tool automates this process by helping the user identify and move comment fields into the specified CO dataset.

Comment Options
The comment screen allows you to select all the options to instruct CDISC builder to transform the selected data to the designated CO dataset.  The data flow is shown here.

Source Data with Comments

CDISC Builder Comment

CDISC Comment (CO) Data

The options available for selecting data and options for CDISC comment transformation:

• Source Data - This is the location of the dataset that is going to have the CDISC guidelines verification check.
• Data Sets - The selected dataset that is going to be verified.
• Preview - A print out of the first 100 observation of the data
• Related Domain - The CDISC related domain which the comment is associated with.
• Study Identifier - The name of the study or the protocol number
• Comment Variable - The variable(s) that contain the comments
• Date Variable - A date variable associated with the comment
• Identification Variable - A unique identifier such as a sequence number or date that uniquely identifies the comment if there are multiple.
• Unique Subject ID Variable - The subject ID variable
• Output - The output dataset that which is usually CO
• Base Code - An optional SAS base code that can be generated used to create the comment transformation.
• Save Code - The code saved in this location will contain a macro call capturing all the options that has been selected.  This can therefore be executed independent from this interface as a SAS program.
• Find Comment - This option searches through all existing datasets in the specified library for possible comment fields. 

Only one dataset can be selected at a time to have comment applied.  This is due to the fact that the identifying variable usually is different among each dataset and therefore has to be selected individually.