Evaluating the results of clinical studies can be daunting, but some simple tools can make it a fun experience. I consider drug literature evaluation to be a journey down a somewhat winding road that ultimately leads to a better understanding of a clinical study.
Each study or clinical trial of a drug tells a story, and it is up to us as pharmacists to use our skills just like a detective to critically evaluate and understand the behind-the-scenes statistics. Statistics are tools that evaluate data to provide important study results. Essentially, clinical trials are types of studies that are the basis of the drug approval process, which is a take-home point that I always emphasized when teaching pharmacy students.
Here are five things to know about statistics from clinical studies:
1. Read Beyond the Abstract
The study abstract is like a restaurant menu in that it gives you a taste of the study and includes descriptions of the most important points. However, the abstract does not go into detail about all the statistical methods used in the study. Reading the full study enables you to take an in-depth look at the results and statistical methods.
Pharmacy conferences can be a great way to get a glimpse at ongoing or completed research projects through poster presentations, which are basically abstracts or summaries of the study’s results. If the researchers who presented the poster or abstract decide to submit their manuscript to a journal for publication, then the information could change from what was presented. A study by Saldanha and colleagues in the journal Trials looked at discrepancies between conference abstracts and the later, full publications and found differences in the main outcome results that were reported. The take-home point is to never base clinical decisions on what is in an abstract or poster.
2. Determine Whether All Results Were Included
When evaluating clinical trials, it is always important to see how the data were analyzed.
Intention-to-treat is considered the gold standard analysis since it accounts for data from all patients who were randomized or initially assigned to treatment groups. Even if some of the patients failed to complete the entire study, their information is still analyzed and reported in the results. Intention-to-treat is designed to mimic what happens in clinical practice. Patients will not always be compliant with their medications or may experience side effects that cause them to discontinue treatment.
Per-protocol is another type of analysis, but it should be viewed cautiously since it excludes the results of patients who did not adhere to their protocol treatment. If a patient misses one or two doses, their valuable information may never be revealed in the results. This could make the treatment look better than it really is and lead to biased results.
Continue reading on page 2...