What is SDTM in clinical trials?
The Study Data Tabulation Model (SDTM) is one of the most important CDISC data standards. This standard is used for organizing data collected in human clinical trials.
Organizations must use the SDTM standard when submitting clinical data to the US Food and Drug Administration (FDA), the UK Medicines and Healthcare products Regulatory Agency (MHRA), and the Pharmaceuticals and Medical Devices Agency (PMDA) in Japan.
The SDTM standard explains exactly how to organize and present the data. It gives regulatory reviewers a clear description of the structure, attributes, and contents of each dataset, and the variables submitted as part of your clinical trial, which means it’s easier for them to analyze the content. There are benefits for organizations too: studies are more consistent, because they’re all in the same standard format. This enables easier data sharing and reuse.
What is the latest version of SDTM?
CDISC build the SDTM standards from two important models:
- Latest version – SDTM v2.0
- Provides a standardized set of variables, assembled into ‘classes’, which are refined and built into variable collections for specific uses cases. Examples include Vital Signs observations, Adverse Events, and Medical History reporting. The SDTM core model also supports the non-human trial standard SEND.
- Latest version – SDTM implementation guide v3.4
CDISC is always developing new domains. It’s important to regularly check the CDISC website for the latest updates.
Formalizing the structure of domains has also led to the development of conformance rules, by both the CDISC SDTM team and regulatory bodies. These rules are programmed into software validation tools to automate the checking of SDTM clinical datasets against the conformance rules.
What is the SDTM implementation guide?
The SDTM Implementation Guide (SDTMIG) is really important, so let’s look at it in more detail.
According to CDISC: “Where the SDTM provides a standard model for organizing and formatting data for human and animal studies, the SDTMIG is intended to guide the organization, structure, and format of standard clinical trial tabulation datasets.”
The SDTMIG is an essential resource to help you map or convert data to SDTM. We highly recommend familiarizing yourself with this document before doing SDTM mappings or conversions.
What are SDTM datasets?
SDTM datasets are the data tables that are created in alignment with the SDTM standard, for submission to regulatory authorities. The datasets include details about clinical study participants, including visits, treatments, and observations.
Here’s an example of an SDTM+ dataset for DM (Demographics) domain.
What are SDTM domains?
According to CDISC, SDTM domains are ‘A collection of logically related observations with a common, specific topic that are normally collected for all subjects in a clinical investigation. NOTE: The logic of the relationship may pertain to the scientific subject matter of the data or to its role in the trial.’
SDTM domains are divided into the following classes:
- Special purpose domains
- General observation classes
- Findings about
- Trial designs
- Relationship datasets
How do you create SDTM datasets?
- Determine which SDTM domains to create.
- Compare the SDTM data to the SDTM metadata and map directly where possible.
- Map the rest of the source datasets to SDTM domains.
- Map variables in the source datasets to the variables in the SDTM domains.
- Decide whether custom domains and SUPPQUAL domains need to be created.
- Perform the data conversion – there are various mapping tools you can use to do this.
- Validate the SDTM datasets.
Ready to implement SDTM?
There’s a lot to get your head around with SDTM. But don’t worry – we can help!
Pinnacle 21 Clinical Data Management and Automation Suite can help you go from protocol to SDTM to submission in half the time. With spec design, mapping, and conversion tools embedded in our clinical MDR, you’ll have SDTM datasets in just two to four weeks. That’s because CRFs are designed in line with SDTM from the outset – so mappings can be done at study design.