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You've probably heard that randomized clinical trials and observational studies are like oil and water—you can't mix them together. After all, randomized clinical trials (RCTs) are the gold standard of medical research, while observational studies are the ugly stepchild of medical research. You would never confuse one with the other, right? Wrong! As it turns out, RCTs and observational studies actually have a lot in common—a lot more than you might think! This blog post will outline how randomized clinical trials and observational studies share many similar attributes, which has interesting implications for the world of biomedical research.

What are randomized clinical trials?

A randomized clinical trial (RCT) is a type of research study that compares two or more interventions, such as medication or treatment. A single RCT can test just one variable in order to see how it affects health outcomes like mortality, morbidity, quality of life, etc. An RCT is highly controlled in order to ensure that only one intervention is tested on subjects at a time. For example, if testing a new cancer drug for its ability to kill tumor cells was being performed in an RCT, participants would be randomly assigned either to receive the drug or no treatment; all other variables would remain constant so that any differences observed between groups could be attributed solely to differences in their treatment.

What are observational studies?

These are studies that follow groups of people to determine how different factors affect their health. This type of study is useful for understanding patterns in health and disease, but cannot prove cause-and-effect. Any differences between two groups (for example, smokers and non-smokers) could be due to a number of factors aside from tobacco use; if you have a medical condition that leads you to both smoke more than normal AND have worse health than normal (perhaps), then it might not be fair to say smoking caused your poor health—the other factor may have been at play too. Also, observational studies rely on participants' memory or records regarding what they did in their past.

Who can participate in RCTs?

RCTs often require that a participant be a certain age, suffer from a specific condition, and meet other criteria before they can participate. Because of these restrictions, RCTs are susceptible to biased sampling—they may attract individuals who are particularly responsive to treatment. If you want to know how effective your product or service is for typical patients in typical clinical settings, look to observational studies for answers. When it comes to observational research, there are no gold standard selection methods—just make sure that you only include data from those representative of your target patient population. The more diversely an observational study samples patients, ages, and conditions, the greater its generalizability—the more likely it is that its results apply to your target patient population.

Is the design of an RCT random?

There are two basic ways to structure an RCT. One can randomly assign individuals to treatment arms, or one can treat everybody in a similar fashion but make sure that assignment is random (for example, by computer) at some point after subjects have started their first intervention. Although these approaches appear quite different on paper, they often wind up looking very similar when implemented in practice because sample sizes are so small that treating everybody identically winds up essentially randomizing people anyway. If you imagine sampling without replacement—that is, if each new person has a nonzero probability of being assigned to any intervention arm—the two designs really look identical.

What is randomization in science, anyway?

Don’t be fooled by how similar randomized clinical trials (RCTs) and observational studies can seem on first glance. Both designs have a place in biomedical research, but neither one is superior to the other—they’re just different. The main differences between RCTs and observational studies are who participates in each study, what is being studied, how participants are selected, whether any treatments or interventions are given during participation in either design, and how results are measured. In general, RCTs better answer specific questions about cause-and-effect relationships while observational studies can be useful for making associations between variables that may not be able to be tested in an experimental setting.

How do we know if it was random enough?

Before scientists can rely on a clinical trial, they have to make sure it was conducted correctly. One of their main concerns is whether or not participants were randomly assigned to groups. This is necessary because each group should have as many (or as few) characteristics in common with one another as possible. If a sample isn't randomized—meaning that people aren't randomly assigned to either treatment or control groups—the results are potentially biased (another word for erroneous). Scientists try to minimize potential bias by using randomization techniques and computer-generated random numbers. But even with these measures, experts can't completely eliminate bias from all clinical trials or observational studies—it would take an impossibly large number of test subjects, researchers and testing time periods for that to happen!

How do RCT results apply to me/my family/my loved ones/myself when I have cancer/I have lupus?

The results of a randomized clinical trial may not directly apply to you or someone you love. That’s because they don’t consider all of an individual’s personal characteristics (i.e., not everyone has cancer, lupus, Alzheimer’s, etc.). Further, RCTs typically exclude people who have certain health conditions from participating in trials because it can be unethical to deny them treatment based on chance alone. What does that mean for your use of RCT evidence? The best way to think about it is that RCT data represent one statistical population and therefore do not necessarily apply to every person individually.

So...which should I trust more - randomized clinical trials or observational studies?

It depends. If a randomized clinical trial is comparing two treatments with strong evidence behind them, then yes, you should trust that trial more than an observational study - particularly if it has a prospective randomized design. For example, if you have patients in a randomized clinical trial comparing chemotherapy to surgery for esophageal cancer, we know that these are both valid treatments for that disease based on prior research - so our minds are at ease. But what about studies that try to compare one treatment with another (such as plant-based diets vs animal-based diets for reducing cardiovascular risk) or where we don't yet have strong evidence behind one of them?

Conclusion

Of course, there are major differences between randomized clinical trials and observational studies. However, it’s important to note that randomized clinical trials only try to determine cause-and-effect relationships when they can remove all other factors in determining a patient’s condition. Meanwhile, as scientists have seen more of these similar aspects over time, we’ve come to find that our interpretations about which types of data should be used for which type of study might have been too rigid—and may not hold up as well over time. Ultimately, many researchers feel that looking at both RCT data and observational data together is what will help us make better conclusions about many health problems. While some research has shown that combining randomized clinical trial and observational data from electronic medical records could lead to a greater understanding of how certain drugs affect patients, we still need more research on how to best combine these two types of data.