TTHealthWatch is a weekly podcast from Texas Tech. In it, Elizabeth Tracey, director of electronic media for Johns Hopkins Medicine in Baltimore, and Rick Lange, MD, president of the Texas Tech University Health Sciences Center in El Paso, look at the top medical stories of the week.
This week’s topics include treating COVID-19 pneumonia and a new model for clinical trials, a chronic pain prediction score, polygenic risk score for coronary artery disease, and a new agent for smoking cessation.
Program notes:
0:41 Treating COVID-related pneumonia
1:45 Concurrent placebo group
2:41 May reduce time needed for trials
2:54 New agent for smoking cessation
3:54 Adults who wanted to quit
4:54 Had already tried quitting average six times
5:51 Polygenic risk score for coronary artery disease
6:56 Many ethnicities worldwide
7:56 Need to start young
8:47 Prognostic risk score for chronic pain
9:46 Risk of pain spreading
10:46 Experience a death or divorce?
11:50 End
Transcript:
Elizabeth: Can we predict development and spread of chronic pain?
Rick: Ages of modified immune system in people with COVID-19 pneumonia.
Elizabeth: A new agent for helping people quit smoking.
Rick: And quantifying the relationship between many of the common genetic abnormalities and the risk of coronary artery disease.
Elizabeth: That’s what we’re talking about this week on TT HealthWatch, your weekly look at the medical headlines from Texas Tech University Health Sciences Center in El Paso. I’m Elizabeth Tracey, a Baltimore-based medical journalist.
Rick: And I’m Rick Lange, president of Texas Tech University Health Sciences Center in El Paso, where I’m also dean of the Paul L. Foster School of Medicine.
Elizabeth: Rick, gosh, we haven’t talked about COVID for a while. Why don’t we turn right to JAMA, this issue of is there anything that helps when people have COVID-related pneumonia?
Rick: As recently as April of this year, there were still a thousand COVID-related deaths weekly.
This particular study is interesting for two things. One is the results, but also how they did the study. They specifically looked at the most severely-diseased individuals. These were adults who were in the hospital and had evidence of COVID-19 pneumonia.
We know from previous studies that things like dexamethasone and some immune-modulating agents can actually improve outcome. They tested three different agents, all that had different pathways, but they all affected the immune system. One is called abatacept, one is called cenicriviroc, and the other is infliximab. Two of these are given as a single infusion, one is an oral agent, and then they assessed time to recovery by day 28. The second was, what was the mortality?
Here is the way the study was done. Oftentimes, you test each of these three agents with three different randomized controlled trials, but they didn’t do that. First of all, they randomized the individuals to one of these three agents, and then they were randomized to either receive that agent or a placebo. So we had a concurrent placebo group that could be spread among all of these three different drugs. It required less patients and it could be done more quickly.
In the end, they unfortunately discovered that these three agents were no better than placebo to recovery by day 28. Interestingly enough, though, two of those three looked like they actually reduced mortality by about 40%.
Fortunately, we have other agents that we know are beneficial. We know these other agents reduce mortality, they improve outcome, and you recover faster. We don’t need to try any of these three agents that we studied this particular time. However, in the case where those agents aren’t available — and that happened before — then one could try one of these two agents that reduce mortality.
Elizabeth: Do you think that this is a model that has legs going forward in terms of facilitating outcomes in clinical trials?
Rick: I do, especially for conditions that are considered to be pandemics. I mean, they affect a large number of individuals, they oftentimes very rapidly develop, and the time it can take to do a randomized controlled trial can be months or up to a year. This particular way that they conducted this trial, I think, can be applied to future trials as well.
Elizabeth: Remaining in JAMA, let’s take a look at this new agent for smoking cessation. It’s called cytisinicline. It is a close cousin of varenicline, something we’re already familiar with and that’s licensed in this country for aiding in smoking cessation. I had no idea that almost half a million people die a year, still, in this country, relative to complications from cigarette smoking.
Rick: That’s the number of people who are dying of COVID, and we really jumped on that pretty quickly. But these ongoing deaths related to tobacco use kind of sit in the background, so I’m interested in this particular study.
Elizabeth: Right. That, of course, is something that the editorialist points out and also points out that more than 50% of U.S. adults who smoke have attempted to quit at least once each year, and about 7% of those who smoke achieving abstinence each year for 6 months. So it’s pretty bad when people actually try to take care of this themselves.
In this study, they had 810 adults who smoked cigarettes daily and wanted to quit. It was conducted at 17 U.S. sites over about a year plus. These participants were randomly assigned to a 3-mg, three-times-a-day dose for 12 weeks of the medication, three times daily for 6 weeks, then placebo three times daily for 6 weeks, and then placebo three times daily for 12 weeks.
This is important because this medicine has been around in Europe for a while. One of the things that’s been kind of a sticking point relative to bringing it here has been this issue of the dosing schedule, which was pretty onerous. The good news about all of this is that cytisinicline resulted in abstinence rates of almost 33%, versus 7% for weeks 9 to 12 in this cohort, and 21% versus 5% during weeks 9 to 24. So it does seem to have a significant impact on people’s ability to remain abstinent.
Rick: These were individuals who wanted to quit. The trial participants had already tried quitting an average of six different times. They have other ways of doing that. We have nicotine replacement — as you said, varenicline — also bupropion. This particular agent, as you said, has been around in Europe for about 50 years and it’s smaller doses. You need to take it 6 times a day and that’s not very practical. Having a drug that you can take 3 times a day, knowing that one in five individuals, even 12 weeks after it’s been stopped, is still not smoking cigarettes — that’s actually a pretty good result.
Now, what we don’t have are head-to-head comparisons with other types of treatment. Is this better than varenicline? We don’t really know. We do know that the side effects are somewhat similar: insomnia, abnormal dreams, which occur in about 8% to 10% of individuals. But it’s clearly better than placebo and is another option for those individuals that are interested in stopping smoking.
Elizabeth: That’s what we need, as many options as possible, as many modalities as possible. I would just add prevention, of course, to that mix.
Rick: Right. Talking about smoking, we know that is a risk factor for coronary artery disease. Let’s talk about the next article in Nature Medicine. This is titled “A multi-ancestry polygenic risk score improves risk prediction for coronary artery disease.” Wow, that’s a mouthful.
To put it in perspective, we talked about personalized medicine in the past. We have to be able to analyze each individual and put it into perspective of the large population. When we look at different genetic variations, we know that when you look across the entire gene spectrum, there are many genes that somehow can affect the presence of coronary artery disease, or peripheral vascular disease, or even risk of stroke. But studying these requires large populations.
The value of this particular study is they had over 269,000 cases and over 1.178 million controls, and coronary artery disease risk factors and genome-wide associations that quantify the relationship between each of the common DNA variants and the risk of disease into a single quantitative and predictive measure.
What they determined was that the use of this polygenic risk score actually improved the things that we usually use, the pooled cohort equation. We know that if you have diabetes, hypertension, and high cholesterol, and you have a family history of coronary disease, all those things are risk factors. But the addition of this gene score actually helps as well. It took about 3% of individuals that were thought to be at a low risk and put them up into a higher risk, so much so that we would actually treat them with statin therapy.
Let’s talk about the applicability. This is a great study because it looked not only at Europeans, but also South Asians, East Asians, and Africans as well. It tells us that this polygenic risk score is beneficial in all of these different groups. We don’t really know whether, once you’ve identified these individuals, whether putting them on a statin or aspirin will actually benefit them or not.
Finally, the incremental value — we haven’t assessed what the cost is. Determining when someone has high blood pressure or diabetes or high cholesterol, those are relatively easy things to do with family history, a genome-wide analysis on absolutely everybody. By the way, you need to start young when the traditional risk factors haven’t actually appeared. It’s interesting, but is it widely applicable? Not quite yet.
Elizabeth: I’m wondering, though, because we see so many manifestations of genetic analysis in clinical decision-making now and my prediction is that that’s only going to continue to be even more widely implemented in all sorts of arenas. It could be that it’s ultimately going to end up being one of those things that when you’re born they take a couple of those cells and they say, “Okay, we’re going to analyze all your genes right now so that we can tell you this is going to be your best strategy for living as healthy as possible.”
Rick: I do think that as the analysis testing becomes better and it becomes less expensive, we’re going to be incorporating more of these. I don’t want to ignore the fact that it interacts with the environment and choices that we make as well.
Elizabeth: We shall see. Remaining in Nature Medicine then, let’s take a look at this study that purports to have developed a prognostic risk score for development and spread of chronic pain. This is from our latest darling, the U.K. Biobank analysis. Their N in that is 490,000 plus.
They use this data. They identified a risk score to classify various chronic pain conditions and pain-related medical conditions. In a longitudinal analysis, it was able to predict the development of widespread chronic pain across multiple body sites and high-impact pain — that’s pain that actually reduces somebody’s physical activity and ability to do anything really. About 9 years later, they found that key risk factors include sleeplessness, feeling fed up, tiredness, stressful life events, and a body mass index greater than or equal to 30.
They also created a simplified version of their score that they called the risk of pain spreading. I love this. I never heard this as a verb before. They reduced this whole thing into six simple what they called “binarized” answers — that means yes or no. They validated it in the North Finland Birth Cohort and the PREVENT-AD cohort, and showed that it had some predictive performance. They also make an assertion that pain spreads proximally to distal sites in the body.
Rick: I had not thought about the fact that when individuals have pain that it often starts at one site, but then spreads throughout the entire body. That’s the most debilitating type because those are individuals that are more likely to be absent from work, to be socially isolated, to reduce their exercise and result in depression.
When someone starts with pain, are there ways to predict where they will become more debilitated? I agree; the fact that you could ask six simple questions: Do you have difficulty falling asleep? Do you feel that your life has been a constant effort? Do you have a lack of energy or powerless? Have you ever had a mental health problem diagnosed? Have you ever experienced a death or a divorce, or problems with your work history? Number Six, is your body mass index greater than 30?
Those questions will give you insight into which individuals are more likely to develop more widespread pain or more severe pain. The next question is, having that information, can we intervene early to prevent that? That’s where the next step lies.
Elizabeth: Right, and that’s my big problem is that I feel like while this might be kind of interesting from a gee-whiz perspective, I’m not sure what its practical implications are because I’m not sure that we have any notion of how to prevent chronic pain.
Rick: I’m going to take it back to cardiovascular prevention. Do you want to take those people who are considered to be at the highest risk? If you can identify patients with this risk score who have a high probability of developing widespread pain, those are the ones that you want to enroll in the treatment trials. That’s probably the major benefit.
Elizabeth: On that note then, that’s a look at this week’s medical headlines from Texas Tech. I’m Elizabeth Tracey.
Rick: And I’m Rick Lange. Y’all listen up and make healthy choices.
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