By Justin Sjogren, MS, Clinical BioStatistician/Programer
[Note: In August 2011, one of my former Statistics professors at GVSU asked me if MMS would be interested in having a booth at GVSU Statistics Career Day, and if I would be willing to give a talk. My presentation focused around my job as a statistician/programmer in the pharmaceutical industry and was geared towards undergraduate and graduate students who were interested in learning more about what a career in statistics is like from the perspective of a former student. The presentation is summarized below.]
Statisticians play an important role in many phases of the clinical trial process, beginning at the design stage and progressing through the final analysis. Statisticians keep the big picture in mind and key strengths include their ability to ask good questions, or ask why a particular decision was made and how best to ensure that each question is worthwhile and useful. They provide input early on in trial development about things such as the type of trial design, randomization considerations, and sample size calculations, which identify the number of subjects needed for a successful trial. All these items help to save the sponsor in time and cost.
Another key responsibility of the statistician is to write the Statistical Analysis Plan (SAP). This regulatory document tells specifically how the analyses will be performed and what will be reported in the final tables. This is where the statistician can think more deeply about how to answer the research question through the appropriate analyses.
During the clinical trial and as subject data starts being made available, clinical programmers will begin producing draft summary tables and statisticians will begin looking into the draft output to ensure everything is in order. In a blinded clinical trial, the treatment group assignments remain unknown until trial completion, so in the datasets, programmers assign subjects to ‘dummy’ treatment groups, which allows them to produce tables that will look just like the final output, only the treatments that the subjects are assigned to are not real. This allows for the study team to have a look at the tables and provide comments prior to the final analysis.
Some clinical trials will have interim analyses, which is a special type of analysis done after only a percentage of the subjects have been enrolled. Often times, early in drug development, the sponsor may be curious about which dose levels are most effective and most well-tolerated, so they will assess this at some point (maybe after 50% of the subjects have been enrolled) during the trial rather than waiting until all subjects have been enrolled. This allows the sponsor to drop doses or re-allocate to certain dose groups if any safety or tolerability issues are seen. This can be tricky however, because the trial is still ongoing and the core study team needs to remain blinded, so an independent group is often utilized to help aid in these decisions. For example, an independent (separate from the sponsor company) statistician will typically be identified to ‘unblind’ the study and perform the required unblinded analyses. Often times the statistician will submit the results to a panel of experts (called a data monitoring committee) to review and decide if or what study modifications may be needed. These may be due in some way to a particular safety concern that may even lead to trial termination or suspension. These decisions are communicated to the sponsor’s upper management.
In a more traditional clinical trial, when all subjects have completed, the database is locked, the study is unblinded, and statisticians and programmers are charged with creating the final tables, listings and graphs. If the analysis calls for any inferential statistics (such as models or statistical tests), the statisticians will typically create these tables. These tables are sent to the medical writers for incorporation into the clinical study report. Then, statisticians are available to the medical writers for any technical questions regarding the tables
Statisticians can have a wide variety of duties and responsibilities, but below are some common traits a good statistician will possess:
- Clear and concise writer – there are no style points when writing SAPs, but clear writing is still very important in providing a how-to for another statistician or in providing statistical rationale for statisticians and non-statisticians alike
- Understanding of statistical tools such as SAS® – having this skill is extremely helpful for investigating issues, completing analysis and validation, etc.
- Interpretation of statistical concepts to non-statistical audiences
- Learn from experiences – build off of what has and has not worked in the past
- Strong attention to detail
- Thoroughness