Understanding Medical Studies

by National Institute on Aging

Every day in the newspaper or on television we see stories about new medical findings. Perhaps we hear that a certain drug causes a 300% or three-fold increase in strokes. That's a large increase - it sounds scary. But, if you know that in every 10,000 people not taking the drug, there are two strokes, then a three-fold increase really only means six more strokes. Maybe that's not quite so frightening. It's also confusing that sometimes stories seem to report opposite results - a new vaccine prevents a devastating infection, or it doesn't. How are we to make sense of such stories? How do we know what to believe?

This fact sheet provides some background to help you understand these news reports. It might also help you judge which results are really important and which are simply interesting but not a reason to change how you take care of yourself.

How does a research study begin?

First, you should know that there are different types of research studies. Often a scientist starts with a question and sets up a controlled experiment to get the answer. Maybe a new drug needs to be tested to see if it cures a bacterial infection. In this kind of experiment the scientist grows the bacteria in the laboratory and then adds the new drug to see what happens. Usually, there is also a control - that is, the same bacteria is grown but not exposed to the new drug. The scientist then looks to see how the new drug affected the treated bacteria compared with the untreated bacteria. Perhaps the treated bacteria are dying while the control ones are still growing. That could mean the drug is effective. If so, the scientist might move on to testing the drug in animals and then in people.

Which studies involve people?

When studying people, scientists often use observational studies. In these, researchers keep track of a group of people for several years without trying to change their lives or provide special treatment. This can help scientists find out who develops a disease, what those people have in common, and how they differ from the group that did not get sick. What they learn can suggest a path for more research. However, observational studies have certain weaknesses. Sometimes differences between groups are caused by something the investigators are not aware of. For any observational study, only further research can prove for sure whether their finding is the actual cause of illness or not.

What comes next?

The results of laboratory experiments and observational studies often interrelate. For example, perhaps a new drug for lowering cholesterol has already been tested for safety in a controlled experiment. Scientists know from observational studies that eating a lot of high-fat foods can raise cholesterol levels and they know that people with high cholesterol are more likely to have heart attacks. This might lead scientists to suspect that they can prevent heart attacks by lowering cholesterol levels with the new drug.

But how to prove that this suspicion is correct? Another kind of research study, called a randomized controlled clinical trial (RCT), is thought to be the best way to learn whether a certain treatment works or not. A clinical trial often involves thousands of human volunteers. They are assigned to two or more study groups by chance (randomized). One of the groups, the control group, receives a placebo. A placebo looks just like the treatment or drug being tested, but actually does nothing.

To start the clinical trial the scientists sign up volunteers. The volunteers are randomly divided into two groups. One receives the test drug, and the other, the control group, gets a placebo. The study is also masked. This means that neither the doctors nor the volunteers know who is getting the test treatment or the placebo. For the next several years the investigators keep track of cholesterol levels and heart attacks in each group. They also watch for side effects of the drug. At the end of the study period, everyone learns which group was getting the test drug and which was on placebo, and the results are analyzed. Fewer heart attacks in the group receiving the test drug would show that the drug prevents heart disease.

How are the results explained?

But, how well does this fictional drug prevent heart attacks? We have to look at how it affects someone's risk of heart attack. By studying large numbers of people, scientists can learn how big these effects are. Benefits and risks can be explained in several ways. These include relative risk and absolute risk.

When the difference between two groups is described as "relative," it is usually shown as a ratio or a percent. An "absolute" difference is nothing more than a number found by subtraction. How these numbers are presented to you can sway how you "feel" about the finding and affect whether you change your behavior.

Relative risk

Let's look again at our earlier research example. In describing the results, the scientist might talk about relative risk. This compares the likelihood that a person who takes the new medicine will have a heart attack to the likelihood that a person in the placebo group will have one. It tells us how much larger or smaller the chance of heart attack is while using the test drug. Maybe the researchers found the relative risk of heart attack in the placebo group was "1.5." Since a finding of "1.0" means there is an equal chance in each group, the finding of 1.5 means the chance of heart attacks in the group receiving the placebo is 50% greater than the chance of heart attacks in people taking the test medicine. It does not mean half of all those who did not receive the test drug had heart attacks.

About the Author

www.nia.nih.gov
NIA, one of the 27 Institutes and Centers of NIH, leads a broad scientific effort to understand the nature of aging and to extend the healthy, active years of life. In 1974, Congress granted authority to form NIA to provide leadership in aging research, training, health information dissemination, and other programs relevant to aging and older people.