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This transcript has been edited for clarity.
If you’ve been paying attention only to the headlines, when you think of “Ozempic” you’ll think of a few things: a blockbuster weight loss drug or the tip of the spear of a completely new industry — why not? A drug so popular that the people it was invented for (those with diabetes) can’t even get it.
Ozempic and other GLP-1 receptor agonists are undeniable game changers. Insofar as obesity is the number-one public health risk in the United States, antiobesity drugs hold immense promise even if all they do is reduce obesity.
In 2023, an article in Scientific Reports presented data suggesting that people on Ozempic might be reducing their alcohol intake, not just their total calories.
A 2024 article in Molecular Psychiatry found that the drug might positively impact cannabis use disorder. An article from Brain Sciences suggests that the drug reduces compulsive shopping.
A picture is starting to form, a picture that suggests these drugs curb hunger both literally and figuratively. That GLP-1 receptor agonists like Ozempic and Mounjaro are fundamentally anticonsumption drugs. In a society that — some would argue — is plagued by overconsumption, these drugs might be just what the doctor ordered.
If only they could stop people from smoking.
Oh, wait — they can.
At least it seems they can, based on a new study appearing in Annals of Internal Medicine.
Before we get too excited, this is not a randomized trial. There actually was a small randomized trial of exenatide (Byetta), which is in the same class as Ozempic but probably a bit less potent, with promising results for smoking cessation. 
But Byetta is the weaker drug in this class; the market leader is Ozempic. So how can you figure out whether Ozempic can reduce smoking without doing a huge and expensive randomized trial? You can do what Nora Volkow and colleagues from the National Institute on Drug Abuse did: a target trial emulation study.
A target trial emulation study is more or less what it sounds like. First, you decide what your dream randomized controlled trial would be and you plan it all out in great detail. You define the population you would recruit, with all the relevant inclusion and exclusion criteria. You define the intervention and the control, and you define the outcome.
But you don’t actually do the trial. You could if someone would lend you $10-$50 million, but assuming you don’t have that lying around, you do the next best thing, which is to dig into a medical record database to find all the people who would be eligible for your imaginary trial. And you analyze them.
The authors wanted to study the effect of Ozempic on smoking among people with diabetes; that’s why all the comparator agents are antidiabetes drugs. They figured out whether these folks were smoking on the basis of a medical record diagnosis of tobacco use disorder before they started one of the drugs of interest. This code is fairly specific: If a patient has it, you can be pretty sure they are smoking. But it’s not very sensitive; not every smoker has this diagnostic code. This is an age-old limitation of using EHR data instead of asking patients, but it’s part of the tradeoff for not having to spend $50 million.
After applying all those inclusion and exclusion criteria, they have a defined population who could be in their dream trial. And, as luck would have it, some of those people really were treated with Ozempic and some really were treated with those other agents. Although decisions about what to prescribe were not randomized, the authors account for this confounding-by-indication using propensity-score matching. You can find a little explainer on propensity-score matching in an earlier column here. 
It’s easy enough, using the EHR, to figure out who has diabetes and who got which drug. But how do you know who quit smoking? Remember, everyone had a diagnosis code for tobacco use disorder prior to starting Ozempic or a comparator drug. The authors decided that if the patient had a medical visit where someone again coded tobacco-use disorder, they were still smoking. If someone prescribed smoking cessation meds like a nicotine patch or varenicline, they were obviously still smoking. If someone billed for tobacco-cessation counseling, the patient is still smoking. We’ll get back to the implications of this outcome definition in a minute.
Let’s talk about the results, which are pretty intriguing. 
When Ozempic is compared with insulin among smokers with diabetes, those on Ozempic were about 30% more likely to quit smoking. They were about 18% more likely to quit smoking than those who took metformin. They were even slightly more likely to quit smoking than those on other GLP-1 receptor antagonists, though I should note that Mounjaro, which is probably the more potent GLP-1 drug in terms of weight loss, was not among the comparators.
This is pretty impressive for a drug that was not designed to be a smoking cessation drug. It speaks to this emerging idea that these drugs do more than curb appetite by slowing down gastric emptying or something. They work in the brain, modulating some of the reward circuitry that keeps us locked into our bad habits.
There are, of course, some caveats. As I pointed out, this study captured the idea of “still smoking” through the use of administrative codes in the EHR and prescription of smoking cessation aids. You could see similar results if taking Ozempic makes people less likely to address their smoking at all; maybe they shut down the doctor before they even talk about it, or there is too much to discuss during these visits to even get to the subject of smoking. You could also see results like this if people taking Ozempic had fewer visits overall, but the authors showed that that, at least, was not the case.
I’m inclined to believe that this effect is real, simply because we keep seeing signals from multiple sources. If that turns out to be the case, these new “weight loss” drugs may prove to be much more than that; they may turn out to be the drugs that can finally save us from ourselves.
Dr. Wilson is associate professor of medicine and public health and director of the Clinical and Translational Research Accelerator at Yale University, New Haven, Connecticut. He has disclosed no relevant financial relationships.
A version of this article first appeared on Medscape.com.
This transcript has been edited for clarity.
If you’ve been paying attention only to the headlines, when you think of “Ozempic” you’ll think of a few things: a blockbuster weight loss drug or the tip of the spear of a completely new industry — why not? A drug so popular that the people it was invented for (those with diabetes) can’t even get it.
Ozempic and other GLP-1 receptor agonists are undeniable game changers. Insofar as obesity is the number-one public health risk in the United States, antiobesity drugs hold immense promise even if all they do is reduce obesity.
In 2023, an article in Scientific Reports presented data suggesting that people on Ozempic might be reducing their alcohol intake, not just their total calories.
A 2024 article in Molecular Psychiatry found that the drug might positively impact cannabis use disorder. An article from Brain Sciences suggests that the drug reduces compulsive shopping.
A picture is starting to form, a picture that suggests these drugs curb hunger both literally and figuratively. That GLP-1 receptor agonists like Ozempic and Mounjaro are fundamentally anticonsumption drugs. In a society that — some would argue — is plagued by overconsumption, these drugs might be just what the doctor ordered.
If only they could stop people from smoking.
Oh, wait — they can.
At least it seems they can, based on a new study appearing in Annals of Internal Medicine.
Before we get too excited, this is not a randomized trial. There actually was a small randomized trial of exenatide (Byetta), which is in the same class as Ozempic but probably a bit less potent, with promising results for smoking cessation.
But Byetta is the weaker drug in this class; the market leader is Ozempic. So how can you figure out whether Ozempic can reduce smoking without doing a huge and expensive randomized trial? You can do what Nora Volkow and colleagues from the National Institute on Drug Abuse did: a target trial emulation study.
A target trial emulation study is more or less what it sounds like. First, you decide what your dream randomized controlled trial would be and you plan it all out in great detail. You define the population you would recruit, with all the relevant inclusion and exclusion criteria. You define the intervention and the control, and you define the outcome.
But you don’t actually do the trial. You could if someone would lend you $10-$50 million, but assuming you don’t have that lying around, you do the next best thing, which is to dig into a medical record database to find all the people who would be eligible for your imaginary trial. And you analyze them.
The authors wanted to study the effect of Ozempic on smoking among people with diabetes; that’s why all the comparator agents are antidiabetes drugs. They figured out whether these folks were smoking on the basis of a medical record diagnosis of tobacco use disorder before they started one of the drugs of interest. This code is fairly specific: If a patient has it, you can be pretty sure they are smoking. But it’s not very sensitive; not every smoker has this diagnostic code. This is an age-old limitation of using EHR data instead of asking patients, but it’s part of the tradeoff for not having to spend $50 million.
After applying all those inclusion and exclusion criteria, they have a defined population who could be in their dream trial. And, as luck would have it, some of those people really were treated with Ozempic and some really were treated with those other agents. Although decisions about what to prescribe were not randomized, the authors account for this confounding-by-indication using propensity-score matching. You can find a little explainer on propensity-score matching in an earlier column here.
It’s easy enough, using the EHR, to figure out who has diabetes and who got which drug. But how do you know who quit smoking? Remember, everyone had a diagnosis code for tobacco use disorder prior to starting Ozempic or a comparator drug. The authors decided that if the patient had a medical visit where someone again coded tobacco-use disorder, they were still smoking. If someone prescribed smoking cessation meds like a nicotine patch or varenicline, they were obviously still smoking. If someone billed for tobacco-cessation counseling, the patient is still smoking. We’ll get back to the implications of this outcome definition in a minute.
Let’s talk about the results, which are pretty intriguing.
When Ozempic is compared with insulin among smokers with diabetes, those on Ozempic were about 30% more likely to quit smoking. They were about 18% more likely to quit smoking than those who took metformin. They were even slightly more likely to quit smoking than those on other GLP-1 receptor antagonists, though I should note that Mounjaro, which is probably the more potent GLP-1 drug in terms of weight loss, was not among the comparators.
This is pretty impressive for a drug that was not designed to be a smoking cessation drug. It speaks to this emerging idea that these drugs do more than curb appetite by slowing down gastric emptying or something. They work in the brain, modulating some of the reward circuitry that keeps us locked into our bad habits.
There are, of course, some caveats. As I pointed out, this study captured the idea of “still smoking” through the use of administrative codes in the EHR and prescription of smoking cessation aids. You could see similar results if taking Ozempic makes people less likely to address their smoking at all; maybe they shut down the doctor before they even talk about it, or there is too much to discuss during these visits to even get to the subject of smoking. You could also see results like this if people taking Ozempic had fewer visits overall, but the authors showed that that, at least, was not the case.
I’m inclined to believe that this effect is real, simply because we keep seeing signals from multiple sources. If that turns out to be the case, these new “weight loss” drugs may prove to be much more than that; they may turn out to be the drugs that can finally save us from ourselves.
Dr. Wilson is associate professor of medicine and public health and director of the Clinical and Translational Research Accelerator at Yale University, New Haven, Connecticut. He has disclosed no relevant financial relationships.
A version of this article first appeared on Medscape.com.
This transcript has been edited for clarity.
If you’ve been paying attention only to the headlines, when you think of “Ozempic” you’ll think of a few things: a blockbuster weight loss drug or the tip of the spear of a completely new industry — why not? A drug so popular that the people it was invented for (those with diabetes) can’t even get it.
Ozempic and other GLP-1 receptor agonists are undeniable game changers. Insofar as obesity is the number-one public health risk in the United States, antiobesity drugs hold immense promise even if all they do is reduce obesity.
In 2023, an article in Scientific Reports presented data suggesting that people on Ozempic might be reducing their alcohol intake, not just their total calories.
A 2024 article in Molecular Psychiatry found that the drug might positively impact cannabis use disorder. An article from Brain Sciences suggests that the drug reduces compulsive shopping.
A picture is starting to form, a picture that suggests these drugs curb hunger both literally and figuratively. That GLP-1 receptor agonists like Ozempic and Mounjaro are fundamentally anticonsumption drugs. In a society that — some would argue — is plagued by overconsumption, these drugs might be just what the doctor ordered.
If only they could stop people from smoking.
Oh, wait — they can.
At least it seems they can, based on a new study appearing in Annals of Internal Medicine.
Before we get too excited, this is not a randomized trial. There actually was a small randomized trial of exenatide (Byetta), which is in the same class as Ozempic but probably a bit less potent, with promising results for smoking cessation.
But Byetta is the weaker drug in this class; the market leader is Ozempic. So how can you figure out whether Ozempic can reduce smoking without doing a huge and expensive randomized trial? You can do what Nora Volkow and colleagues from the National Institute on Drug Abuse did: a target trial emulation study.
A target trial emulation study is more or less what it sounds like. First, you decide what your dream randomized controlled trial would be and you plan it all out in great detail. You define the population you would recruit, with all the relevant inclusion and exclusion criteria. You define the intervention and the control, and you define the outcome.
But you don’t actually do the trial. You could if someone would lend you $10-$50 million, but assuming you don’t have that lying around, you do the next best thing, which is to dig into a medical record database to find all the people who would be eligible for your imaginary trial. And you analyze them.
The authors wanted to study the effect of Ozempic on smoking among people with diabetes; that’s why all the comparator agents are antidiabetes drugs. They figured out whether these folks were smoking on the basis of a medical record diagnosis of tobacco use disorder before they started one of the drugs of interest. This code is fairly specific: If a patient has it, you can be pretty sure they are smoking. But it’s not very sensitive; not every smoker has this diagnostic code. This is an age-old limitation of using EHR data instead of asking patients, but it’s part of the tradeoff for not having to spend $50 million.
After applying all those inclusion and exclusion criteria, they have a defined population who could be in their dream trial. And, as luck would have it, some of those people really were treated with Ozempic and some really were treated with those other agents. Although decisions about what to prescribe were not randomized, the authors account for this confounding-by-indication using propensity-score matching. You can find a little explainer on propensity-score matching in an earlier column here.
It’s easy enough, using the EHR, to figure out who has diabetes and who got which drug. But how do you know who quit smoking? Remember, everyone had a diagnosis code for tobacco use disorder prior to starting Ozempic or a comparator drug. The authors decided that if the patient had a medical visit where someone again coded tobacco-use disorder, they were still smoking. If someone prescribed smoking cessation meds like a nicotine patch or varenicline, they were obviously still smoking. If someone billed for tobacco-cessation counseling, the patient is still smoking. We’ll get back to the implications of this outcome definition in a minute.
Let’s talk about the results, which are pretty intriguing.
When Ozempic is compared with insulin among smokers with diabetes, those on Ozempic were about 30% more likely to quit smoking. They were about 18% more likely to quit smoking than those who took metformin. They were even slightly more likely to quit smoking than those on other GLP-1 receptor antagonists, though I should note that Mounjaro, which is probably the more potent GLP-1 drug in terms of weight loss, was not among the comparators.
This is pretty impressive for a drug that was not designed to be a smoking cessation drug. It speaks to this emerging idea that these drugs do more than curb appetite by slowing down gastric emptying or something. They work in the brain, modulating some of the reward circuitry that keeps us locked into our bad habits.
There are, of course, some caveats. As I pointed out, this study captured the idea of “still smoking” through the use of administrative codes in the EHR and prescription of smoking cessation aids. You could see similar results if taking Ozempic makes people less likely to address their smoking at all; maybe they shut down the doctor before they even talk about it, or there is too much to discuss during these visits to even get to the subject of smoking. You could also see results like this if people taking Ozempic had fewer visits overall, but the authors showed that that, at least, was not the case.
I’m inclined to believe that this effect is real, simply because we keep seeing signals from multiple sources. If that turns out to be the case, these new “weight loss” drugs may prove to be much more than that; they may turn out to be the drugs that can finally save us from ourselves.
Dr. Wilson is associate professor of medicine and public health and director of the Clinical and Translational Research Accelerator at Yale University, New Haven, Connecticut. He has disclosed no relevant financial relationships.
A version of this article first appeared on Medscape.com.