In this week’s interview, Dr. Aaron Carroll of Indiana University discusses what we should look for when we evaluate prescription drugs. How can we tell if the benefits will outweigh the risks for us?
You may want to listen to it via your local public radio station or get the live stream at 7 a.m. EDT on your computer or smart phone (wunc.org). Here is a link so you can know which stations air our broadcast. If you can’t hear the broadcast, you may want to listen to the podcast afterward. You can subscribe through your favorite podcast provider, download the MP3 using the links at the bottom of the page, or listen to the stream on this post starting December 18, 2023.
How we evaluate prescription drugs:
Pharmaceutical companies spend years and millions of dollars evaluating the drugs they develop. They then present the FDA with the results of at least two (rarely more) randomized controlled trials (RCTs) to provide evidence that the drug they want to approve works and is not too risky. Is. It’s important to parse those RCTs, and we’ll discuss some of the most useful tools. But first, we ask Dr. Carroll how people can use their personal experience to evaluate the benefits and harms of a drug.
In a guest essay for the Opinion section of The New York Times, Dr. Carroll shares his involvement with two issues that many people don’t understand: depression and obesity. They titled it What obesity drugs and anti-depressants have in common. What they have in common is not mechanism of action, chemistry or other scientifically determined properties. Rather, both may be stigmatized. Americans often believe that if obesity is a problem one should eat less and exercise more. For depression, the attitude is often cheer up! Or pull yourself up by your bootstraps. (Never mind that this is physically impossible; it’s a popular metaphor.)
Another similarity between antidepressants and new weight loss drugs: We don’t really know how they work. Yes, we have a name for a whole class of antidepressants that describe a purported mechanism, selective serotonin re-uptake inhibitors. But research has not confirmed that these drugs actually fight depression by causing a buildup of the neurotransmitter serotonin in the brain. (For more on this, you may want to listen to the show 1318: Challenging Dogma About Alzheimer’s Disease and Depression.)
What difference does it make whether we know how the medicine works or not? Perhaps its effect is primarily psychological. Someone who does not understand how a medication affects a related health condition may be reluctant to try it.
Personal experience helps when we evaluate prescription drugs:
Ultimately, it is the patient’s experience with the medicine that matters. If a doctor prescribes a drug, but the patient finds that he or she is having excessive or unacceptable side effects while taking it, the decision will be that the drug is not useful. On the other hand, even if a person does not expect much from a prescription, if it helps he or she is likely to keep taking it. Dr. Carroll describes her reluctance to take antidepressants, as well as her frustration at her weight gain despite an excellent, careful diet. The use of medicines to treat these problems has improved their lives.
Is this cheating?
Some people feel that taking prescriptions to treat depression or lose weight is cheating. Strangely, they don’t feel the same way about taking blood pressure pills, thyroid hormones or antibiotics. The important thing we need to consider is not whether a medicine is cheating, but whether it is helpful. Do the benefits outweigh the risks? The answer may vary from person to person, but RCTs provide some guidelines.
Statistical tools to evaluate prescription drugs:
Each research report will include some indication of how well the drug performed. Usually this is a comparison between people taking the drug and people taking a placebo. The issue is how many times they suffered a particular bad outcome.
Absolute versus relative risk reduction:
Ideally, the report would give us actual numbers. How many people were in the trial and how many received treatment? Total risk is generated by tallying the results in different groups and dividing by the number of people in the group. The difference between the groups represents an absolute risk reduction.
That number is important, but it’s not usually the number you’ll find in news accounts of studies. Reporters often emphasize relative risk reduction. Typically, this is a very high number, but without knowing the full risk of the situation, it is mostly meaningless.
NNT and NNH:
Once you know the absolute risk reduction, you can calculate how many patients a person would have to take the drug to get the benefit. This is called the number needed to treat or NNT. The lower the NNT, the greater the chance that a patient will benefit. In contrast, the number Needed to Harm or NNH expresses the risk of side effects associated with the use of the drug. When we evaluate prescription drugs it’s important to know what these numbers mean.
Ultimately, we want evidence-based medicine. Both experimentation and experience provide valuable evidence for determining how useful a drug may be.
This week’s guest:
Aaron E. Carroll, MD, MS, is a distinguished professor of pediatrics at Indiana University School of Medicine. He is the Bicentennial Professor, Associate Dean for Research Mentoring, and Chief Health Officer of Indiana University. He blogs on health research and policy at The Incidental Economist and is a regular contributor to Opinion and Upshot for The New York Times. Dr. Carroll’s most recent book is The Bad Food Bible: How and Why to Eat Sinfully.
Dr. Carroll’s photo is copyright to Marina Waters.
Listen to the podcast:
A podcast of this event will be available on Monday, December 18, 2023, following the broadcast on December 16. You can stream shows and download podcasts for free from this site.
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