How to Extend Metadata

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If data are in scope for a domain defined in this guide, but not all data can be collected using the domain's collection fields, then fields may be added from the CDASH Model or created using guidance below. Prior to adding fields from the CDASH Model or considering a new field, confirm that none of the fields in the domain will fit the need. Fields may be added from the CDASH Model or created only when data are different in nature and are not in scope for existing domain fields. 

Once confirmed, determine whether adding a field from the CDASH Model will fit the need. If adding a field from the CDASH Model meets the need, then a new field will not be created. New fields will only be created for when data are not in scope for a field defined in the CDASH Model. 

The overall process for extending metadata is as follows:

Adding Fields from the CDASH Model

1. Using the root variables and other CDASH metadata in the CDASH Model, add any additional variables that are needed to meet the requirements of data collection. Follow CDISC Variable Naming Fragment (see Appendix B, Glossary and Abbreviations) conventions, and CDASH root variable-naming conventions where they exist (e.g., --DAT for dates, --TIM for times, --YN for prompts, as described in the CDASH Model). 
   Example: Replace "--" with the 2-character domain code that matches the other variables in the same domain. For example, to add the --LOC variable to a Medical History CRF, the domain code is MH, so the variable would become MHLOC in that domain.

   
   

2. The Question Text and Prompt columns in the CDASH Model metadata provide different variations in the recommended text for asking the question on a CRF. For each question, the sponsor may elect to either use the Question Text or the Prompt on the CRF. Some text is presented using brackets [ ], parentheses ( ), and/or incorporating forward slashes. These different formats are used to indicate how the Question Text or Prompt may be modified by the sponsor.

   1. The text inside the brackets provides an option on the verb tense of the question, or text that can be replaced with protocol-specific verbiage.

   2. The text inside the parentheses provides options (e.g., singular/plural), or text that may be eliminated.

   3. Text separated with a forward slash provides optional words that the sponsor may choose.

      Example: The CDASH variable --PERF, from the CDASH Model, has the following Question Text and Prompt.

      Question Text:  [Were any/Was the] [--TEST/ topic] [measurement(s)/test(s)/examination(s)/specimen(s)/sample(s)] [performed/collected]?

       Prompt:  [--TEST/Topic] [Measurement(s)/Test(s)/Examination(s)/Specimen(s)/Sample(s)] [Performed/Collected]?

      The sponsor wants to add a question to a CRF that asks whether a lab specimen was collected, using a Yes/No response.

      The sponsor selects the CDASH variable --PERF and adds the appropriate domain code. LBPERF  

      Use either the Prompt or the Question Text on the CRF.

      Question Text: Was the laboratory specimen collected?

      • In the first set of brackets, the text option "Was the" is selected, as the study required only 1 lab test to be performed. [Were any/Was the] 
      • In the second set of brackets, the text used is "laboratory," which is the topic of interest. [--TEST/Topic (laboratory)]
      • In the third set of brackets, the text option "specimen," without the optional "s," is selected. [measurement(s)/test(s)/examination(s)/specimen(s)/sample(s)]
      • In the fourth set of brackets, the text option "collected" is selected. [performed/collected]

      Prompt: Laboratory Specimen Collected

      •  In the first set of brackets, the text used is the topic of interest (i.e., laboratory). [--TEST/Topic (Laboratory)] 
      • In the second set of brackets, the text option "specimen," without the optional "s," is selected. [Measurement(s)/Test(s)/Examination(s)/Specimen(s)/Sample(s)]
      • In the third set of brackets, the text option "collected" is selected. [Performed/Collected]

      
      

3. Create custom domains based on 1 of the General Observation Classes in the CDASH Model. See Section 3.4, How to Create New Data Collection Fields When No CDASHIG Field Has Been Defined, for more information.

Creating New Fields

When creating a new data collection field, determine whether the data will be used for an operational use case, such as data cleaning, or are actual data to be represented in a tabulation dataset. In general, new data collection fields (not already defined in the CDASH Model) will fall in one of following categories:

• A field used for operational, Data Cleaning purposes only.
• A field used to collect data that have Direct Mapping to a target variable in the tabulation dataset.
• A field used to collect data that have No Direct Mapping to a target variable in the tabulation dataset.

The table below provides implementation guidance aligned with both the category of the field and target variable.