SAS is a programming language used by many clinical programming groups to organize and manage data obtained from a clinical trial, that is, clean the data, manage the data, convert the data into a standard report and store the data, which can be submitted for further approvals. |
Clinical SAS programmers are often grouped into different departments based on the tasks they support. Programmers supporting the SAS edit checks and data cleaning tasks work closely with data management department. SAS programmers who help with creation of standardized analysis datasets from raw datasets may work as part of a SAS programming department. In this department there are also several divisions of programmers depending on the work they perform in the analysis of the data.
Clinical SAS programmers implement the analysis methods on the collected data and provide the study summary tables, data listings and graphs to the senior level statisticians, medical writers and clinicians, thus are helpful in writing the clinical study report. Clinical SAS programmers work closely with clinicians, biostatisticians, and data managers and provide important interface between clinical trial data and the intended analysis.
While data is being re-entered and cleaned, clinical statistical programmers may begin to write SAS programs to generate report tables, listings and graphs according to the study protocols statistical analysis plan and the tables shells designed by the study biostatistician. Drafts of tables, listings and graphs are reviewed by the senior level statisticians and more data clarification queries may also be generated in this process. The responsibility of the programmer is also to notify the data management team either directly or via the biostatistician of any issues in the data or data discrepancy noticed in due course of the programming activities. Programmers may also need to interact with the clinical data management at the same time for the data base lock.
Mostly the programming requirements and activities are based upon the methods and statistical analysis that has been provided by the clinical biostatistician, thus the role of a biostatistician is also critically important in the clinical data analysis.
SAS programmers perform interim analysis of data: An interim analysis is an intermediate assessment on the collected clinical data that is usually done during the patient enrolment or follow-up stages of a clinical trial for the purpose of assessing the intermediate performance of the trial, where the quality of the data collected or treatment effects are analysed. Interim analysis is also called as “data-dependent stopping” or “early stopping”. Interim analysis is most often used to find convincing evidence to say that there is a significance large difference between the stipulated study protocol and the actual treatment outcome and that difference is convincing enough to terminate the trial at a point earlier than planned at first. Interim analysis is also used to possibly reduce the expected number of patients and to shorten the follow-up time needed to make a sensible conclusion of the trial.
SAS Programmers in Interim data analysis do certain function like, drafting table shells, creating specifications for analysis datasets, creating specifications for tables, figures, and listings, identifying first look analyses, performing data checking, parallel programming analysis datasets, checking data results and parallel programming tables, figures, and listings.
Who can be successful programmer: A SAS programmer analyzing the clinical data will be successful purely on the basis of his/her SAS expertise in clinical domain. However, it is beneficial for a SAS programmer to have the basic understanding about Clinical trial processes as he will always have a competitive edge over a pure SAS programmer and he/she will be in a position to take decisions with respect to data analyses while programming. Also, he/she would be more independent and be able to contribute better in terms of understanding and development of more meaningful and high quality reports.
Conclusion: A Clinical SAS programmer with both SAS and clinical knowledge would not only be able to do more justice to the role by generating more reliable and meaningful outputs but also, this combination of knowledge would significantly ease the difficulties in communication channels across different functions in a clinical trial data analysis.
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