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The Ultimate Guide to Mastering Your SAS Course


Clinical Data Interchange Standards Consortium (CDISC), a multidisciplinary non-profit organization, has developed standards to support acquisition, exchange, submission, and archival of clinical research data and metadata. Metadata is the data of the data entered. This includes data about the individual who made the entry or a change in the clinical data, the date and time of entry/change and details of the changes that have been made. Among the standards, two important ones are the Study Data Tabulation Model Implementation Guide for Human Clinical Trials (SDTMIG) and the Clinical Data Acquisition Standards Harmonization (CDASH) standards, available free of cost from the CDISC website (www.cdisc.org). The SDTMIG standard[4] describes the details of model and standard terminologies for the data and serves as a guide to the organization. CDASH v 1.1[5] defines the basic standards for the collection of data in a clinical trial and enlists the basic data information needed from a clinical, regulatory, and scientific perspective.

The Role of SAS Programmers in Clinical Trials

Statistical programmers write and review statistical analysis plans (SAPs), write and execute statistical programs, and analyze data sets according to the endpoints of the clinical trial protocol, the requirements of regulators, and the needs of sponsors. Based on an SAP, statistical programmers create analysis files and reporting programs to produce the tables, figures, and listings required to produce a clinical study report. They can also provide all programming needs, from the beginning to the end of a study, and continued monitoring, working seamlessly with a client’s staff and departments.

What Are the Advantages of SAS Programming over Other Languages?

In a clinical trial, thousands of case reports with many data points each can be handled using platforms like SAS. Additionally, SAS is a quite sophisticated and strong programming language, enabling programmers to execute extremely precise data manipulation and analysis as well as effectively present the data. The SAS platform has been specifically designed to manage the volume of data and level of analysis needed to conduct large clinical studies. Such an analysis is necessary for both a complete comprehension of a study’s findings and for effectively conveying those findings to pharmaceutical regulators. SAS is used to process a large portion of the data that is annually reported to the FDA

SAS Statistical Programming and CDISC

Before statistical programmers start generating lines of code in a clinical trial —particularly if the study data is to be submitted to the FDA—, SDTM (Study Data Tabulation Model) and ADaM (Analysis Data Model) specifications should be in place. SDTM and ADaM are standards belonging to CDISC (Clinical Data Interchange Standards Consortium), which is an international organization that actively develops data standards for clinical research. SDTM defines a standard structure for clinical trial data and for non-clinical study data tabulations, which are to be submitted as part of a product application to a regulatory authority such as the FDA. On the other hand, ADaM defines dataset and metadata standards that support the efficient generation, replication, and review of clinical trial statistical analyses, and traceability among analysis results, analysis data, and data represented in SDTM. Statistical programmers —as members of a clinical trial team— must be knowledgeable and follow CDISC standards in their work.


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