How to Make Sense of Medical Headlines and Studies
How should you respond when you hear or read medical headlines that are either sensational or confusing?
Rob Lamberts, MD
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How to Make Sense of Medical Headlines and Studies
I am sure you have heard all of the headlines regarding the new recommendations about screening for breast cancer. They caused quite a bit of controversy and some outright anger.
I got a twitter from Lynette…or is that a tweet? Whatever. She wondered what my take was on these breast cancer screening recommendations. When these recommendations were issued by the US Preventive Task Force, I had to spend a lot of my time in the office telling how I interpreted these big changes.
How to Make Sense of Medical Headlines
In truth, this happens frequently, with medical headlines hitting the newspapers, morning TV shows, and blogs on the Internet. People don’t know how to deal with this kind of thing, as a lot of times it is either sensational (like a cure for cancer or key to fixing obesity) or it directly contradicts things people have heard earlier. The recent breast cancer recommendations, for example, seem to contradict what people took for granted: women should perform self breast exams and get mammograms. Now they say not to do them? What can you believe?
So in the next two articles I am going to teach you how to listen to what you hear on the news without getting totally confused. Today’s article will focus on some common mistakes we make and the next one will cover how to do it right.
How to Make Sense of Medical Studies
OK, back to those confusing headlines. I have to first say that it isn’t always easy for me to handle studies and headlines, so I don’t expect to remove confusion, but I do think I can reduce it some.
The first step in this process is to understand common mistakes people make when dealing with science and how it relates to their health care.
Error 1: Correlation Does Not Equal Cause
To understand the first error, imagine a farmer who notices that a rooster crows before every sunrise. It happens every morning. This fine scientist decides that the rooster’s crowing must cause the sun to rise, coming up with the sun-rooster hypothesis. But this is no slouch scientist, and so he goes out to test this hypothesis by asking his farmer friends, and all of them say the rooster always crows before the sunrise.
So there you have it: proof that roosters have cosmologic powers, right? Not so fast! What our scientist has done is to simply note a correlation between two observations, which is fine, but the conclusion that one causes the other is in error. Is our scientist foolish for thinking this? No, he just needs more information to make his conclusion.
This kind of thing happens often in medical science. Did you know that heavy coffee drinkers have higher rates of lung cancer than those who don’t drink any coffee? But before you sell all your stock in Starbucks, let me tell you one more fact: heavy coffee drinkers are much more likely to be smokers than those who don’t drink coffee.
Experiments Must Confirm Hypotheses
To prove that one thing causes another takes a lot more work than just noting that they happen together. Experiments need to be performed to test the hypothesis. Tape the mouth of the rooster shut and see if the sun still rises. Go to a place without roosters and see if the sun rises. Compare smokers who drink lots of coffee with those who do not. Have heavy coffee drinkers switch to decaf and see if the cancer rate goes down. All hypotheses must be thoroughly tested before they can be relied on.
Error 2. Science Does Not Equal Fact
The second error people make is to equate science with fact. A scientist makes a finite number of observations and draws conclusions from them. But often the best sounding theories–the ones that seem obvious–are knocked flat when put to the test.
Often the best sounding theories–the ones that seem obvious–are knocked flat when put to the test.
A good example of this is the theory that post-menopausal women should have hormone replacement therapy. When I first started in practice, it was believed that women should get estrogens after menopause. That belief came from the observation that prior to menopause, women have a low rate of heart attacks and a low rate of bone loss that could lead to osteoporosis, but after menopause heart attacks and osteoporosis rates went way up. The belief that post-menopausal women should take hormones was bolstered by a study that looked at a huge number of women retrospectively and found that those who had taken hormones had lower rates of heart disease.
Science Changes
But retrospective studies (ones that look back at populations looking for trends) are unreliable, and so scientists did a prospective study to prove the benefits of hormones. They took a large number of women and put half of them on hormones and gave the other half a sugar pill, or placebo, and watched to see what happened. To the dismay of the hormone manufacturers, the women who got hormones had an increase in heart attacks, not a decrease. That made us all do a 180 and take all the women to whom we have been pushing hormones off of them.
Were we wrong to push hormones? No, the best information we had at the time said that it helped; but when the better information came along we had to change what we were saying. This is the nature of science: it changes. Scientific theories should always be questioned; the more questions they stand up to, the more solid the theory.
Error 3: Groups Don’t Equal Individuals
The third big mistake people make is to assume that science on a group must apply to them individually. There are several ways this can go wrong.
The first way this can go wrong is that the person may not belong to the group of people in the study. For example, there are studies that show that a certain blood pressure drug can prevent kidney damage. But it is wrong to think conclude everyone with high blood pressure should be put on that medication. This is an actual class of drugs, and the studies on them were done on diabetics, who are especially prone to kidney problems. You should always read the fine print in the studies before applying them to yourself, and there is always lots of fine print.
The second way people can put too much trust studies is by seeing things in black and white. Even the most convincing data doesn’t apply to 100% of people. People are really complex, and there are always a lot of factors we don’t know about. If a certain drug benefits 99 out of 100 people, who’s to say that you are not that 1 in 100? Someone has to be. Medical practice must always take into account that we are dealing with individuals, not groups. The best we can do is to improve people’s odds; there are no sure things.
How to Avoid Mistakes When Hearing Scientific Studies
So now that I have totally undermined your trust in medical science, let me give you my Quick and Dirty Tips on how to avoid mistakes when hearing scientific studies.
Tip 1: Don’t believe everything you hear – Many people make mistakes when looking at scientific information, so you should always be skeptical.
Tip 2: Be willing to change what you believe – It’s simply the nature of science to change what it says. The biggest mistakes come when we don’t question things.
Tip 3: Find trusted sources – I don’t have time to research everything, so I rely on others to do that for me. You should do the same; but understand that all sources (even your fabulous doctor) should not be trusted 100%
That’s it for today. Next I will get to more specifics about how to listen better.
If you have questions you want answered, send them to housecalldoctor@quickanddirtytips.comcreate new email. You can find me on Twitter as @housecalldoc and on Facebook under “House Call Doctor.”
Let me remind you that this podcast is for informational purposes only. My goal is to add to your medical knowledge and translate some of the weird medical stuff you hear, so when you do go to your doctor, your visits will be more fruitful. I don’t intend to replace your doctor; he or she is the one you should always consult about your own medical condition.
Catch you next time! Stay Healthy!
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