In this week’s interview, Dr. Aaron Carroll of Indiana University discusses what we should consider when evaluating prescription drugs. How can we tell if the benefits outweigh the risks to us?
You may want to listen to it on your local public radio station or catch the live stream at 7:00 a.m. EDT on your computer or smartphone (wunc.org). Here is a link to see which stations are airing our broadcast. If you can’t listen to the broadcast, you might want to listen to the podcast later. You can subscribe via your favorite podcast service provider, download the mp3 via the link at the bottom of the page or listen to the stream of this post from 18.12.2023.
How we evaluate prescription drugs:
Pharmaceutical companies spend years and millions of dollars evaluating the drugs they develop. Then they present the FDA with the results of at least two (rarely more) randomized controlled trials (RCTs) to prove that the drug they hope to get approved works and isn’t too risky. Structuring these RCTs is important, and we discuss some of the most useful tools. But first, we ask Dr. Carroll how people can use their personal experience to weigh the pros and cons of drugs.
In a guest essay for the New York Times opinion section, Dr. Carroll shares his own involvement in two issues that many people don’t understand, depression and obesity. He called it What Obesity Medicines and Antidepressants Have in Common. They do not have a mechanism of action, chemistry or other scientifically determined properties in common. Rather, both may have a stigma. Americans often believe that they should be able to eat less and exercise more if obesity is a problem. The attitude to depression is often Cheer up! or Pull yourself up by your bootstraps. (Never mind that this is physically impossible; it’s a popular metaphor.)
Another thing that antidepressants and new weight-loss drugs have in common: we don’t really know how they work. Yes, we have a name for an entire category of antidepressants that describes the purported mechanism, selective serotonin reuptake inhibitors. But studies have not confirmed that these drugs actually fight depression by causing the neurotransmitter serotonin to build up in the brain. (To learn more, listen to Show 1318: Challenging Dogma About Alzheimer’s and Depression.)
What does it matter if we know how the drug works? Perhaps the effect is primarily psychological. Someone who doesn’t understand how a drug affects that health condition may be reluctant to try it.
Personal experience helps when we evaluate prescription drugs:
Ultimately, the patient’s experience with the drug is important. If a doctor prescribes a drug, but the patient finds that he suffers from overwhelming or unacceptable side effects while using it, the drug is not helpful. On the other hand, even if a person doesn’t expect much from a prescription, they are likely to continue taking it if it helps. Dr. Carroll describes his reluctance to try an antidepressant and his dismay that he gained weight despite an excellent and careful diet. Using medication to treat these problems has improved his life.
Is it cheating?
Some people feel that taking a prescription for depression or weight loss is a scam. Strangely, they don’t seem to feel the same way about blood pressure medication, thyroid hormone, or antibiotics. The important thing we need to consider is not whether the drug is a scam, but rather whether it is beneficial. Do the benefits outweigh the risks? The answer may vary from person to person, but RCTs provide some guidance.
Statistical tools for evaluating prescription drugs:
Each study report contains some information about how well the drug worked. Usually this is a comparison between people taking the drug and people taking a placebo. The problem is how often they ended up with a particularly bad result.
Absolute vs. Relative Risk Reduction:
Ideally, the report will give us real numbers. How many people were in the study and how many received treatment? Calculating the results of different groups and dividing them by the number of people in the group produces an absolute risk. The difference between groups indicates absolute risk reduction.
This number is important, but it’s not usually the number you’ll find in a news story about a study. Suppliers often emphasize relative risk reduction. Usually this is a much higher number, but without knowing the absolute risk of the condition, it is mostly meaningless.
NNT and NNH:
Once you know the absolute risk reduction, you can calculate how many patients would have to take the drug for one person to benefit. This is called the number needed to treat, or NNT. The lower the NNT, the more likely a particular patient will benefit. On the contrary, the number needed for harm or NNH indicates the risk of a side effect associated with the use of the drug. Knowing what these numbers mean is very important when we evaluate prescription drugs.
Ultimately, we want evidence-based medicine. Both trials and experience provide valuable evidence to determine how beneficial a drug may be.
This week’s guest:
Aaron E. Carroll, MD, MS, is a professor emeritus of pediatrics at the Indiana University School of Medicine. He is the Bicentennial Professor, Associate Dean for Research Mentoring, and Director of Health at Indiana University. He blogs about health research and policy at The Incidental Economist and is a regular contributor to Opinion and Upshot at The New York Times. Dr. Carrolls latest book is The Bad Food Bible: How and Why to Eat Sinfully.
Photo of Dr. Carroll copyright Marina Waters.
Listen to the podcast:
A podcast of this show will be available on Monday, December 18, 2023, following the broadcast on December 16. You can stream the show from this site and download the podcast for free.
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