Article -> Article Details

Another task of the DM programmer is to transform the data from its raw format into a standard format. This standard format could be the CDISC Study Data Tabulation Model (SDTM) that is requested by regulatory agencies such as the FDA for submission of an incipient compound, or it could be a sponsor’s own standards. In the process of transforming the data, the DM programmer must make sure that the output conforms to the standard and is compliant as well as valid.

Thus, another aspect of the job is to write programs to check the data against the standard and run the programs whenever an incipient study is about to be analyzed. Determinately, when all the data has been transformed, the DM programmer must engender a convey file that will be sent to the regulatory agency that will review the submission data. The second type of clinical programmer is the statistical programmer (STAT) who takes the data that is cleaned and transformed by the DM programmer and engenders tables, listings, and graphs (TLG) for the clinical study report (CSR). Sometimes the data is taken from its raw state and transformed directly into TLGs, but most often the STAT programmer engenders analysis data sets from which they can facilely engender the compulsory output documents for the CSR. The STAT programmer is withal tasked with engendering ad hoc reports when needed, yearly safety updates, DSMB reports, and integrated safety and efficacy summaries.

There is a significant transition occurring for many clinical programmers in data management (DM). Many DM programmers are evolving from engendering programs in Base SAS to the utilization of incipient implements and solutions to engender the data that is needed in an incipient drug application submission. What did the programmer do in the past to cleanse the data and how has that process transmuted? Now that the data is requested to be in a standard format, what types of programs, macros, and formats were habituated to transform the data? What is done now to make the process more facile, more efficient, and repeatable across protocols, compounds, and therapeutic areas? From the old methodology to the incipient implements, we will show how the transformation process can be transmuted and amended.

Implementing SDTM with Base SAS

One possible approach is to implement the SDTM data standard with Base SAS as the primary implement. In the simplest form, this involves importing the source data into Base SAS, transforming that data with DATA steps, SQL and SAS PROCS, and then preserving SDTM domains as aeonian data sets. For this instance of engendering the DM file, sort the three source data sets by patient identifier, and then merge them together. The remaining activity is to define each of the SDTM DM variables in a DATA step and preserve that DM file to the target LIBREF. As is the case with all legacy SAS work, we have at our disposal a code editor window and SAS documentation perhaps in hard copy as well as online.

Base SAS Approach – Challenges and Benefits

There are several challenges with the reliance on Base SAS alone to perform SDTM domain data engendered. A primary issue is the management of metadata, as there is no metadata provided with Base SAS alone. One thing to note about this program is that you require to inscribe in all the LENGTH and LABEL verbalizations to define the SDTM metadata for the final domain data sets. This type of metadata is tedious, prone to error, and liable to result in inconsistencies across SDTM domain metadata for a tribulation. You additionally have no authentic regulation of the target metadata and no genuine-time validation that your resulting domain is valid SDTM data. When utilizing this Base SAS approach, you additionally run into logistical and strategic issues with code maintenance and reusability of the SAS code. The Base SAS code itself can become arduous to read, which makes maintenance arduous. This kind of coding inclines to be “one-off” in nature – resulting in constrained reusability.

The primary advantage of the Base SAS approach – albeit some might genuinely consider it a disadvantage – is that you have no restrictions as to what you can do with your SAS code. You have the full arsenal of Base SAS and can utilize any SAS procedure, macro code, or SQL procedure code to solve the quandary of SDTM data conversion. Some programmers have taken the Base SAS approach to SDTM engendered work and have augmented it with commonly available implements such as Microsoft Access or Excel as a place to store and apply metadata. This augmented approach is better than Base SAS solutions alone because you have your target SDTM metadata in a more manageable source, and you can consider the effort remotely data-driven and less prone to metadata consistency errors.