Greetings, welcome to CVRx share's preliminary results of the BeAT-HF post-market clinical trials. At this time, all participants are in listen-only mode. A question- and- answer session will follow the formal presentation. If anyone should require operator assistance during the conference, please press star zero on your telephone keypad. As a reminder, this conference is being recorded. It is now my pleasure to introduce your host, Nadim Yared, President and Chief Executive Officer. Thank you. You may begin.
Thank you for joining us today for this important update. I am excited to share with you the preliminary top-line results of the post-market phase of our BeAT-HF trial, as presented at the Technology and Heart Failure Therapeutics conference, or THT, in Boston today by Dr. Michael Zile, Chair of the Executive Steering Committee of the trial. Before we go further, I need to state that the remarks today will contain forward-looking statements, including statements about expected product developments, regulatory matters, and business impacts. The statements are based on plans and expectations as of today, which may change over time. In addition, actual results could differ materially due to a number of risks and uncertainties, including those identified in the press release issued prior to this call and in the company's SEC filings.
The next section of slides that I will walk through are those presented by Dr. Michael Zile on behalf of the Executive Steering Committee of the BeAT-HF trial at THT earlier today. As part of the presentation, Dr. Zile included a disclosure statement of his financial interests. As a reminder, the baroreflex activation therapy device, or Barostim or BAT, consists of two surgically implanted components. The Carotid Sinus Lead is placed under the skin, but outside of the vasculature on the carotid artery, and the pulse generator is placed under the skin in a pocket created just below the clavicle. Electrical stimulation of the carotid baroreceptors results in two balanced efferent signals from the brain. The first increases the parasympathetic activity, also known as the rest and digest mechanism, and the second decreases the sympathetic activity, also known as the fight or flight mechanism.
This type of autonomic modulation produces beneficial cardiovascular responses, such as those shown on this slide. BeAT-HF was a prospective, multicenter, randomized controlled trial. Patients were randomized into 2 groups. Those with BAT, labeled in red in this presentation, received the Barostim device on top of optimal guideline-directed medical therapy. The control group, in blue in this presentation, only received optimal guideline-directed medical therapy. The main eligibility criteria are shown on the slide. Barostim received the Breakthrough Device designation from FDA. To qualify for a Breakthrough Device designation, a device must address an unmet need and show that it has the potential to provide for more effective treatment of life-threatening diseases or irreversibly debilitating conditions. The BeAT-HF trial was performed in 2 phases.
The pre-market phase, in which 4 primary endpoints were examined at 6 months after randomization, led to the FDA approval of Barostim for the improvement of symptoms in 2019. In the post-market phase, the primary endpoint was cardiovascular mortality and heart failure morbidity. Additional pre-specified endpoints were also examined. An intention-to-treat analysis was performed on the 323 randomized patients who experienced 332 primary events over 1,036 patient years of follow-up, with a median follow-up of 3.6 years per patient. The baseline characteristics were well-balanced between the BAT and control groups. Patients in the trial had characteristics typical of patients suffering from heart failure with reduced ejection fraction that are classified as NYHA Class III or Class II with a recent history of Class III. The patients in the trial also had the expected level of comorbid diseases.
The heart failure treatments at baseline for the patients in the trial were well-balanced between the groups and followed the guidelines in place at the time patients were randomized. Especially noteworthy, approximately 80% of patients have previously received an implantable cardio defibrillator. For the post-market phase of the BeAT-HF study, the primary endpoint was a composite of cardiovascular mortality and heart failure morbidity assessed as a negative binomial model. CV mortality was defined as cardiovascular death or receiving an LVAD or a heart transplant. HF morbidity was defined as a non-elective heart failure hospitalization or a heart failure emergency room visit. Additional pre-specified endpoints included a hierarchical composite analysis using win ratio, an all-cause mortality endpoint, and the durability of the safety and patient-centered symptomatic endpoints.
The top-line summary of key evidence from this trial is shown here. This is an outline of the data that I will explain in more detail in the next few slides. For each endpoint, the colored dot represents the observation in the trial, and the horizontal black line represents the confidence interval. Dots on the right of the vertical line favor Barostim. For both the primary endpoint and the components of the primary endpoint, there were no statistically significant differences between Barostim and control. Both all-cause mortality and the hierarchical win ratio were significantly improved in the BAT group. The long-term measures of safety and symptomatic improvement significantly favored Barostim. I will review each of these endpoints in detail. In this chart, the cumulative number of primary endpoint events per patient are plotted in blue for the control arm and red for BAT.
The overall rate ratio was calculated using a negative binomial model. There was no statistically significant difference between BAT and control. On this slide, the two components of the primary endpoint are plotted separately. The table summarizes the data, which shows the number of events per patient per 100 years in each group. The results were not statistically significant. There are important detailed analysis related to these components that we will discuss later in this presentation. To gain a better understanding of the totality of the data in this study, the Executive Steering Committee performed a pre-specified win ratio analysis. This win ratio method has now been used as a primary endpoint in many cardiovascular randomized controlled trials. Powering a trial for a mortality and morbidity endpoint has two major limitations.
The first limitation is that it only uses information from patients who have had an event, and that may represent only a fraction of all of the patients who are enrolled in a trial. The second is the lack of a hierarchical aspect that treats all events in a similar fashion. Death and a heart failure hospitalization may be equal in what it means to the number of events in a trial, but they are not equal to what they mean to a patient and to their physician. The hierarchical composite analysis using a win ratio method captures the totality of the experience of all of the patients, comparing the outcome for each patient in the BAT arm against each patient in the control arm.
The pre-specified win ratio was assessed using the hierarchy described on this slide, with the order of importance being cardiovascular death, LVAD or transplant, heart failure hospitalization, and then quality of life. Approximately 26,000 possible pairs of patients were analyzed, and the results will be described as a ratio of the total wins for the Barostim arm divided by the total wins for the control. A result greater than 1 means the patients in the Barostim arm were more likely to have a better outcome than control. In BeAT-HF, the pre-specified hierarchical composite endpoint favored the BAT group with a win ratio of 1.26 and a nominal P value of 0.04. This means that BAT patients had a 26% greater likelihood of having a better outcome than control.
Given the increased prevalence and better understanding of win-ratio analysis, I believe this information will be considered very important to patients and their physicians when considering if this therapy is right for them. As shown in this pie chart, each of the three main hierarchical components was balanced and contributed equally to the total win ratio. As was shown previously, the cardiovascular mortality as a component of the primary endpoint was not statistically significant. The all-cause mortality, which tracked all trial patients who stayed alive and did not receive an LVAD or a heart transplant, showed that patients who received Barostim had a relative risk reduction of 34% with a nominal P value of 0.054.
I need to remind everyone that approximately 80% of the patients in the trial had a life-saving ICD already in their chests, and all of the patients were on guideline-directed medical therapy that are also known to reduce mortality. Yet, despite all of these background therapies, we saw a significant reduction in mortality. I believe this information will be considered very important to patients and their physicians when considering if Barostim is right for them. Now we turn our attention to the durability of the safety and patient-centered symptomatic data. As you can see on this slide, the trial demonstrated a MACE-free rate of 97%. This is further evidence that the device and the related procedure are safe. The change in quality of life score from baseline is assessed with a standardized tool, Minnesota Living with Heart Failure Questionnaire. It's plotted here at 6, 12, and 24 months.
The change for QOL for BAT patients from baseline is shown in red, control is in blue. The difference between the two groups is shown in green. Focus your attention on the green. At each time point, there is a significant large improvement in BAT versus control. The difference was shown to be durable in time and sustainable in extent. The change in exercise capacity, as measured by the standardized test of a six-minute hall walk, is shown here at 6 and 12 months. The study protocol did not seek an assessment at 24 months. At each time point, there is a significant large improvement in BAT versus control. Here, the difference was durable in time and sustainable in extent.
Finally, this slide shows that the % of patients that improved by at least one NYHA class was significantly greater in BAT versus control at six, 12, and 24 months. In summary, while the primary endpoint and its components were not statistically significant in BAT versus control, both all-cause mortality and the hierarchical win ratio were significantly improved in the BAT arm. Both safety and measures of symptomatic improvements were durable over the assessment periods at six, 12, and 24 months. These favorable data led the Executive Steering Committee of the trial to conclude that the totality of evidence indicates that BAT is a safe, effective, and durable treatment for patients with heart failure with reduced ejection fraction. There were additional analysis shown during the CVRx-sponsored lunch symposium at THT, where Dr. Abraham, Lindenfeld, McCann, and Zile shared with the audience their interpretation of the data.
In the next set of slides, I will share with you some of the key additional findings that they disclosed with the audience. A clinical stability analysis examines whether patients' clinical status improved, worsened, or stayed the same. Using the analytics defined on the left, similar to those used in the EMPEROR-Reduced HF trial published by Dr. Packer, the executive steering committee performed a pre-specified clinical stability analysis in BeAT-HF. BAT resulted in significantly more patients who improved and fewer patients that worsened. The proportional odds of the analysis was 1.9, and the nominal P value, 0.009. This is a reminder of the win ratio shown earlier with CV mortality, which was the one pre-specified. Note here that CV mortality contributed 34% to the final ratio, as shown on the pie chart.
Many physicians prefer to consider the hierarchical win ratio with all-cause mortality instead of the cardiovascular mortality, as they consider it to be more representative. This win ratio with all-cause mortality was performed as a sensitivity analysis. The results remain consistent and significant. As shown in the pie chart, the hierarchical components were still balanced, but importantly, all-cause mortality contributed to 41% of the win ratio. Back to the primary endpoint and the graph I've shown you earlier. If you look closely, you can see during the time period between 1 and 2.5 years post-randomization, there appears to be at least some separation between BAT and control. We will look more closely at this time period the next slide. At 1 and 2 years, BAT decreased the primary endpoint event rate by 24% and 18% respectively, neither reaching statistical significance.
COVID-19 has been shown to have a significant impact on previously reported randomized clinical trials such as GUIDE-HF, the executive steering committee examined first the effect of COVID-19. In the inserts, which we have shown earlier, heart failure morbidity data is plotted with all patients starting at time zero when they were randomized in the trial. In the main graph on this slide, the same exact data is plotted according to a calendar date. This explains the visual differences between the graphs, and importantly, shows the clear and significant effect that COVID had on the event rate.
In the control group, the heart failure morbidity event rate fell significantly during COVID, while in the BAT group there were little to no changes in the event rates comparing before and during COVID. The table clearly demonstrates that the primary effect of COVID was in the control group, where the heart failure morbidity event rate fell from 29% to 7% during that period. In all other years before or after COVID, the average event rate was 26% in the BAT group compared to 29% in the control group. This data led the executive steering committee to believe that COVID definitely impacted the hospitalization rate of the study. The COVID impact was differentially expressed more in the control group than in the BAT group. Why COVID had these differential effects has not been thoroughly investigated yet.
Whether and to what extent COVID acted to limit the ability of BeAT-HF to identify an effect of BAT on the heart failure hospitalization awaits further analysis. In summary, despite the potential confounding effect of COVID and other potential confounding factors on the primary endpoint, both all-cause mortality and the hierarchical win ratio were significantly improved in the BAT group. Both safety and measures of symptomatic improvements were durable over the assessment periods at 6, 12, and 24 months. These favorable data are leading the committee to conclude that the totality of evidence indicates that BAT is a safe, effective, and durable treatment for patients with heart failure with reduced ejection fraction. Now to our own takeaways. Barostim is currently FDA-approved for the improvement of heart failure symptoms based on the pre-market phase of BeAT-HF trial at 6 months.
The post-market phase of BeAT-HF confirmed the long-term durability of safety and symptomatic improvements and the sustainability of the extent of the improvements. The survival free from LVAD transplant is meaningful by showing a 34% reduction with a nominal P value of 0.054. The pre-specified hierarchical composite endpoint was well-balanced and demonstrated meaningful benefit by showing a win ratio of 1.26 with a nominal P value of 0.04, which was stable over multiple sensitivity analysis despite the presence of multiple confounders, including COVID-19. One or more manuscripts will be written by the Executive Steering Committee for submission to peer-reviewed journals. The PMA technical report is being prepared by CVRx to be submitted to FDA to seek an expansion of the labeling commensurate with the recommendation of the Executive Steering Committee of BeAT-HF.
We agree with the committee that the totality of evidence supports the use of Barostim as a treatment for heart failure. I appreciate all of you taking the time to join us today to hear the more detailed explanations of the results of BeAT-HF. I hope that we were able to communicate with you our enthusiasm for the results. With that, I would like to open the line for questions. Operator.
Thank you. Ladies and gentlemen, at this time, we will be conducting a question-and-answer session. If you'd like to ask a question, you may press star one on your telephone keypad. A confirmation tone will indicate your line is in the question queue. You may press star two if you would like to remove your question from the queue. For participants using speaker equipment, it may be necessary to pick up your handset before pressing the star key. Our first question comes from the line of Robbie Marcus with JP Morgan. Please proceed with your question.
Hi, this is Alan on for Robbie. Thanks for taking the question. You know, I guess just to start off, I think that, you know, the main value proposition of Barostim and really why it's been adopted up until now has been improvements in QOL. It's definitely encouraging to see that maintained out to 24 months. You know, while it is disappointing to see that the primary endpoint didn't read clinical significance, as you said, there's some confounding factors and definitely some areas where it does look like Barostim has a meaningful benefit to mortality, morbidity. How should we really think about, you know, the physician response that you've, you know, seen so far at the conference to the data? How do you see it really affecting your adoption given the lack of a clinical meaningful primary endpoint?
Thanks, Alan, for joining us. Great question. You are correct. We've been commercializing Barostim so far based on the 6-month symptomatic data, and we've seen a very nice traction so far. Now we're showing that this 6-month data is sustainable to 12 and 24, and safety is sustainable too. We're answering the question on whether there is a cost to the improvement of symptoms. Let me explain that in a second. The current medical treatment for those patients is the guideline-directed medical therapy, 4 classes of drug, all 4 improve mortality. None of them improve symptoms. Yet when patients knock on the door of a physician, they first want a better life. Not a longer life, a better life. Some physicians discuss with the patients the possibility for the patients to take inotropes drugs.
Those are not part of the guideline-directed medical therapy, and they are known to shorten the life. Patients are willing to trade a shorter life for a better quality of life by taking those positive inotrope drug. Now we come forward with a proposition says, "Hey, wait, you don't have to do this. You can get Barostim, and it improves much better, much more. The quality of life. It doesn't require compliance. It doesn't require taking even more drugs, more pills. Now we can say, "And this doesn't come at a cost of shortening your life, and maybe it could prolong your life." That alone, Alan, is a very interesting value proposition that most of the physicians here at THT that listened to the presentation today, and came back and interacted with me, they were repeating this over and over again.
There's been a lot written about this. What to do, you know, with data like this. Do you go the dogmatic way and you say, no, you missed the endpoint, you don't look at anything else? Or do you go the pragmatic way where you say, No, it's the totality of evidence. We cannot ignore the rest. Often what happens is if a trial wins the primary endpoint, but there is a negative signal somewhere else. Let's take the opposite example for a second. If we had a 34% increase in mortality with a P value of 0.1, do you think physicians would have ignored that? Do you think FDA would have ignored that? Absolutely not. We'll be digging right now trying to understand, is that really a mortal risk to patients?
Why would we, in one case, assume that it's important and when it's positive, assume that it's not important, right? That asymmetry in the interpretation of the data works to our advantage in this way, at this time, because we do have a good data. It's a 34%. Answering one of the questions today, during the symposium, I think it was Dr. Abraham asked Dr. Zile about the number needed to treat with this therapy at the median follow-up, around four years. The answer from Dr. Zile was 10.4. 10.4 is an amazingly low number of patients needed to be treated to save a life if this was a primary powered endpoint. I think here is we cannot ignore the data.
I think physicians will not ignore the data, and patients definitely will not ignore the data. We don't know yet about regulators and payers, right? That would be a different question. To the question of adoption, it's a little bit early right now to speculate. We've had a good run so far. We plan to continue on the run. You know, you may want to ask me this question maybe in six months or nine months when we've had more clarity from FDA and some more time with this data with physicians and see how, you know, whether it's impacting the number of activation of new centers or the number of implants in activated centers.
Got it. That was really comprehensive. I'll just leave, you know. Just a final quick one. You know, obviously the effect of COVID seems pretty drastic in 2020, but, you know, to my eye, it's a little confusing why it would have had such a dramatic effect on the control arm and not on the BAT arm. You know, you're looking into it yourself already, but do you have any preliminary theories for why that might have led to such a marked difference in HF morbidity for control but not for the Barostim arm? Thank you.
Great question, and secondly, very good question. We don't believe we have the full picture yet, neither did our steering committee, to answer this question. However, we do have some hypothesis and some speculations at this stage. One of the elements in here is the asymmetry of treatment of the patients in the trial. When COVID hit, the Heart Failure Collaboratory that gathers, you know, academicians, FDA, and industry discussed this issue, particularly based on the data that was observed at Vanderbilt with the reduction of hospitalizations. And we added, you know, all of the safeguards in the trial to ensure that we're collecting the COVID data, but also we offer the opportunity of doing remote follow-up for patients.
While remote follow-ups could be done in patients without a device, it is almost impossible to do it with a device when you need to reprogram the device, particularly in the titration phase. That's one difference between the two arms. The second idea or hypothesis came to us from an a very prominent statistician who was blinded to the data. This statistician did not see the data until today. This statistician, when we asked him, "What should we consider in regard to the COVID analysis?" His answer was to look at the adjudication differences. The stricter the rules about what to consider being a heart failure hospitalization primary event and whatnot, the more difference you might see during COVID, these were his words. Let me try to explain this in layman's terms.
How do we collect heart failure hospitalizations? The site report an event. This event is sent to an independent adjudication committee that looks at all of the documents. There is a very developed charter that they have to go through it and verify if this qualifies as a primary event or not. You know what the site declared as being a heart failure hospitalization might not be one. That ratio, we will be analyzing it and looking carefully because one of the hypothesis from the statistician is that during COVID, hospitals were overloaded. The flow of information collected and reported back would have been inadequate at best. And that would have made the adjudication almost impossible. That would be differential between the two arms because the Barostim patients or patients who have received the Barostim would have gone to the site that implanted the Barostim.
While patients in the control arm, if they had a congestive event, they would go to the nearest hospital that is not on lockdown. those are two examples where we could have a differential impact, and it's we don't have proofs yet. It will require a few more weeks of analysis here to understand it. I tell you here, everyone's asking the same question, why and what are the explanations? oh, wow, it looks eerily similar to what CardioMEMS Abbott have seen during GUIDE-HF, but not a single physician told us that they don't believe this or where are we looking at this? It's, you know, as soon as they look at this chart, the answer is, "Wow, there is an impact." Thank you for the questions.
Matt O'Brien with Piper Sandler. Please proceed with your question.
Hi, this is Sam on for Matt. Thank you for taking our question, and congrats on the data today. I guess, first of all, kind of a follow-up to the prior question as well. We were hoping you could give us just a little bit more detail on kind of potential label expansions and what to expect there and maybe when we could expect it. Then also maybe as it pertains to the, maybe what all data would be included and maybe some of this COVID and adjudication analysis maybe could be in there as well. Any thoughts there? Thank you.
Oh, thank you, Sam. Great questions. The first one I, you know, I have to be careful in here to make sure that preface, I will preface everything I say saying this is our position as a company, and we take this position. We don't know how FDA would react to our position, our interpretation of the data and the arguments we make versus their own interpretation and the analysis they make. That said, based on the recommendation from the steering committee, we agree with them that we should upgrade our labeling from being considered a device that improves symptoms of heart failure to a device that treats heart failure. That word treatment is not used lightly in this context.
It took a lot of discussions internally within the steering committee, between the steering committee and CVRx and inside CVRx, to make sure that this is what we want to go with. It is an important claim. If we get this claim that this device treats heart failure and not just the symptoms of heart failure, I believe that's a significant upgrade to where we are today. That said, we could elect to go with a lesser one, which will be about the durability of symptoms, longer term, et cetera, and/or we could go for more aggressive stance saying, you know, this reduces or improves outcome in patients, right? Based on the win ratio.
I would say right now the position is we will go for treatment and everything else will be discussed with FDA, and we might end up combining the treatment labeling with durable symptoms as well. You had a second question, Sam, and you I think you mentioned about whether the COVID analysis will be presented.
Yes. Yes. That's right.
Yeah. I don't know yet if the COVID analysis will make its way in the first, the main manuscript, or whether it justifies having a separate manuscript just to focus on the COVID impact. That has not been decided. Clearly, our PMA submission to FDA will include all of the analysis that we would have concluded to date. It will be the list and the exhaustive list of all of the analysis that we as a company and the steering committee have done. All of this will be submitted to FDA. The submission to FDA is confidential, and FDA has 180 days, so 6 months to respond to it if everything goes to plan. They could also decide to go faster. We don't know.
The baseline here is after we've submit, it will be up to 180 days for an FDA response.
Great. Thank you so much. We appreciate it.
Thank you.
Our next question comes from the line of Margaret Kaczor with William Blair. Please proceed with your question.
Hey, good afternoon, everyone. Thanks for taking the question. I wanted to maybe start with, you know, there's been a few discussions this week on the pros and cons of the win ratio, and you spoke a lot about that. There's also been this discussion over win odds and taking that into account, you know, ties, if you will. If you look at the 1.26 hierarchical composite win ratio, but you didn't disclose a win odds ratio, I guess, have you looked at that, and how maybe your win ratio compares to other heart failure trials, you know, trial limited of course coming into play and collapsed kind of being discussed as well? Or are they just?
Yeah, no. Great question, Margaret, and very nice hearing from you. Listen, the win ratio I'm more familiar with is the tricuspid valve TRILUMINATE that was presented at ACC two weeks ago. You are correct. Some people received it very favorably that they won the primary endpoint. Some others says, "Well, wait a second. The reason they win or they won it is about 50% of the effect was driven by the symptomatic endpoint, which was a KCCQ of 15 points or more. There were a lot of ties, a lot of inconclusive comparisons between pairs of patients. In our situation, and although this number was not presented today, it's not a material number, but I can go and tell you about 5% of the comparison ended up in a tie.
The competitor we have for the quality of life is at least 5-point improvement in the Minnesota Living with Heart Failure Questionnaire. 95% of the comparisons led to a winner one way or the other. In my opinion, it's much harder to criticize our analysis the way the data played out. The reason we showed the sensitivity analysis was to strengthen that point, because one of the criticisms would be to say, "Well, wait a second, you're showing, you know, cardiovascular mortality, that's not the way to do, win ratio and so forth." We went during the symposium, and we've shown the all mortality version of the win ratio, even though this was not the pre-specified analysis. We're showing it as a sensitivity analysis, but actually it doesn't weaken the argument.
It strengthened the argument by showing now that most of the effect is driven by the mortality or a higher effect is driven by mortality than previously. Also footnote in the Dr. Zile's presentation that we did not mention, there was a 24-month comparison as well. The way the win ratio analysis works, all of the data is compared. The quality of life that was used was the 12 month. This was the pre-specified. As you know, we also collected quality of life at 24 months. We ran this as well as a sensitivity analysis, and I think you can see it in the footnote of the slide. It shows 1.34 with a P value of 0.01. No matter which way we are cutting or slicing this win ratio data.
Our next question comes from the line of Bill Plovanic with Canaccord. Please proceed with your questions.
Great. Thanks for taking my questions and good seeing you at the conference and the presentations. Most of the questions have been asked. I just have a couple of follow-ups here. One is, you know, one of the comments by the physicians was something regarding the FDA TAP program for HFpEF and HFmrEF. Just any thoughts on, you know, as next steps for the company in terms of clinical trials to run and data to gather? You know, any thoughts on priorities in terms of do you think you need to go get more data in the HFrEF market or you're going to look for more label expansion into other areas?
Hello, Bill. Nice hearing you. Can you hear me okay?
I can, yes.
Oh, perfect. Yeah, I thought I may have lost the connection. You know, I'm becoming paranoid with this. Yeah. What is the TAP advisory program, the TAP? This is part of the MDUFA V program that FDA started. They're accepting 15 programs this year, all of them in cardiovascular. We were, I think, the first to submit the request. The request required is the product to be a Breakthrough Device designation to be considered in the TAP program. Think about it like a Breakthrough Device designation on steroids. It doesn't mean that we have decided to start the program now. To answer your second question, I can come back to this first one. I don't think we need to conduct more trial in HFrEF. We will be conducting more health economic data collection in the future.
We may be requested to do other, you know, data collection registries or so forth for coverage purposes with private payers or CMS. That's different. We don't intend to run a double-blinded or a blinded randomized trial in HFrEF. As we think about our future clinical trial investments, they'll most likely be in adjacent therapies. You know that we have two breakthrough designations, one in HFpEF and the second in hypertension, resistant hypertension. The one that we submitted a request to FDA to upgrade the breakthrough designation to a TAP program is the one with HFpEF, which actually, when you look at the definition that we're using for the ejection fraction, it's more HFpEF plus HFpEF. I'm sorry about these. HFmrEF, which is heart failure with mid-range EF, and the HFpEF, which is heart failure with preserved ejection fraction.
Those are the terminologies based on different ranges of EF. That's the status here, Bill.
Okay. I think this was asked, I just want to clarify. You know, just in the past, I mean, can you give us examples of FDA really looking at the win ratio in terms of approvals and labeling and, you know, what their kind of position is, at least in your opinion?
Yes. Actually the latest one is the TRILUMINATE. It was accepted by FDA to be their primary endpoint, and they met it, and they're submitting now the request to be approved for the tricuspid valve repair. You want an example of a product that has been approved with the win ratio? I don't have one right now. I thought the COAPT was one. One of the things to consider is the win ratio methodology did not exist for a long time. Meaning it's pretty recent. For this to have happened, you have had to have a program that selected win ratio as a primary endpoint, finished the trial, submitted to FDA and got approval. I don't have an example right now, Bill, in this regard. That said, let me disclose one interesting tidbit here.
We were not aware of the win ratio analysis as a methodology when we designed this trial. You know very well that we worked very interactively and very collaboratively with FDA when we're designing this trial. The audience yesterday in the FDA session here at THT heard so many examples talking about the BeAT-HF trial as plowing the way in here for the new way of developing clinical trials. Part of those conversations and interactions we had with FDA, they actually hinted to us that we should add in the statistical analysis plan a win ratio analysis. When we heard this, it was like, what is that? Right. We went and did the investigation and figured out that a statistician, a famous statistician by the name of Dr.
Stuart Pocock from the U.K., has taken an existing approach and is applying it to cardiovascular trials and so forth. We worked with him to verify that the approach that we're using is valid and so forth. That's the story, right? It's not a foreign concept to FDA. I don't have an example where FDA approved a product yet based on it, and I will research it and get back to you with it when I find one.
Thank you. My last question, Nadim, is, you know, you and I have talked about this, but, you know, as we sit here at THT, you know, how do you feel that the physician attitude is relative to endpoints in these trials, you know, today versus maybe 3 or 5 years ago, as it pertains to, you know, mortality, hospitalization, quality of life? I'll end it on that. Thanks.
Yeah. It's a long answer to your question, Bill, here. Let me try to select a road where I don't go down deep into the weeds. listen, the, I don't know, you know, in my presentation, I mentioned that this trial, the analysis were done on an intent to treat basis. There was a trial for AF ablation recently where the data on an intent to treat basis did not show any effects because a lot of the patients crossed between one arm and the others. When they did it on a per protocol basis, the data strengthened and was statistically significant. Yet you see where AF ablation is these days in terms of penetration. I think it depends on the physician.
You have some that are very theoretical, academic, dogmatic in their approach. You've got some others who are very clinical, down-to-earth, pragmatic. Depending on where they sit on the spectrum, they could have a different appreciation of the data. In regard to the quality of life versus duration of life, I think that language has changed dramatically over the past 5 years. When we started this program 5 years ago, cardiologists will basically criticize us because we're focusing on quality of life instead of focusing on the double quote here, the real outcome, which is mortality. 5 years later now, they are realizing, the community at large, that actually what patients want when they knock on the door of a doctor, they want a better living. That is more about the living experience rather than the duration of life that they need.
That's what patients are asking for, and physicians are starting to respond to this. What has helped in this dialogue is a study that was conducted under the Science of Patient Input initiative that was driven by FDA and the Medical Device Innovation Consortium, MDIC. Heart failure was the first project selected. 6 companies, cardiovascular, all 5 large and 1 small, CVRx was the smallest, plus FDA contributed financially to this project, and the study was done right at Duke. The statistics were conducted by MIT, and the results were published, where it was clearly shown that when you ask patients using a conjoint analysis about comparing quality of life versus duration of life, almost 3 to 1 ratio, they prefer quality over quantity.
I think that is helping to change a little bit the attitude here of many physicians towards that debate, you know, quality of life versus outcome. Now, we don't have to ask this question anymore at CVRx. I think we have relatively good outcome data when you look at the totality of evidence. I think we've got both of both worlds here, the best of both worlds. Thanks, Bill.
That takes my questions.
Our next question comes from the line of Alex Nowak with Craig-Hallum. Please proceed with your question.
Okay, great. Good afternoon, everyone. On the cardiovascular mortality and also on the all-cause mortality, there was this huge split that really occurred at the years for the patient groups. I'm just curious, as you dig into the data there, what's really the biggest factor with that, you know, that major split occurring at that time point?
Alex, great question. We don't know. We don't know the answer. It could be that we're trying to read too much into it because those curves, you have to think about it like they are surrounded by a cloud of uncertainty. Those are the 95% confidence interval around each of these lines. The line is just happened to be a line, and you're trying to figure out where it is within that cloud. It could split earlier, it could split later. You know, you know what I'm saying? I don't think there is a physiological reason. Some might speculate that, hey, you know what, 50% of the patients with heart failure end up dying after five years, you know, based on the AHA statistics, et cetera.
That's why you're seeing that type of curve in the control arm, while as in the BAT arm, it's pretty steady. I think that's a speculation. I think that's reading way too much into the data. Maybe I'm not enough of a salesperson here, too much of a scientist, but that's my interpretation of the data.
Okay, that makes sense. In the prepared remarks you mentioned beyond COVID that you hinted that there is potentially other confounders that would have impacted the morbidity side of the study. Could you maybe expand on that? you know, what are you seeing in the data when you look at it patient by patient that would have maybe hurt the morbidity result, not necessarily the mortality piece?
Yeah. There are two other confounders that we can talk about. The first one is the competing risk of death. We know from the all-cause mortality data that we had more death and LVAD and heart transplant, so more censoring terminal events in the control arm than the BAT arm. Let me ask a question, and I'll answer it. Who are the patients who would die or get an LVAD or a heart transplant? They are the sickest patients. You're taking a control arm and you're taking the sickest patients and more of those, and you're exiting the trial because they get these events. Who is left in the control arm? Lesser sick patients. More so or lesser sick in the control arm than in the device arm.
You think about those recurring heart failure hospitalization events, now you have that risk of shortening the population in the control arm and focusing on the healthiest patients because the sickest patients left the trial in the control arm and trying to compare it with the device arm. You have also the other element, which is the difference between the ER visit and heart failure hospitalization. This one will have to wait for the manuscript. There'll be very interesting data in there. There is another one, which is the interventions during the trial. The drug uptake and device uptake during the trial. LVAD being one, but there are others, you know, CardioMEMS, other devices, other drugs added, Entresto SGLT2i what was made available. The question is: Was the uptake equivalent between the arms?
If it is not, it could be a confounder. Because I'm mentioning here that there was a confounder, I'm saying that this uptake was not the same in both arms. Again, we'll have to wait here for the manuscript for all of this data to get out in the public domain.
Okay, makes sense. Just one quick clarification. Timing for the FDA submission, then would you expect a panel meeting based on the data you have in hand?
The timing of the submission, I would say not immediately. It's going to take us some while. I estimated the document that we submit to FDA to have about 600 pages. That's my own estimate. It is going to take a while to verify every single number, every single table, the text surrounding it and route it with our advisors, our steering committee and so forth. It's going to be a few weeks down the road here. I don't have a specific time to say. It will be up to 6 months for a response from FDA. Do I expect a panel? I don't know. I really don't know.
FDA had a panel to discuss heart failure, both for CardioMEMS and for Impulse Dynamics, they already know the feedback from physicians about what is important in terms of efficacy, symptomatic and mortality, morbidity, and the safety. If FDA doesn't feel that the data needs to have a vote from an independent panel, that the data speaks for itself, like what happened with our data back in April of 2019, they would not convene a panel. They don't need to. Convening a panel is an expensive avenue for FDA. It requires a lot of time of preparation. It's expensive for the company. FDA does not take that decision lightly. They will convene a panel if they believe they need one. If they don't need one, they will not convene a panel.
Okay. Thank you for the update. Appreciate it.
Thanks, Alex.
Our next question is a follow-up question from the line of Margaret Kaczor with William Blair. Please proceed with your question.
Hey, guys. Sorry, I seemed to have been knocked off earlier, so I'm gonna follow up with one more. Just a commercial question, you know, I'm just trying to get a sense, you know, based on the data today, now that we've seen it, you know, are you guys gonna, I guess, invest more aggressively or cautiously as you kind of push or educate on Barostim? You know, would you, I guess, wait in some ways until you get the indication expansion or commercial reimbursement approval to change that behavior set?
Margaret, thank you. Apologies, I thought the problem was on my side when you were cut off. Every time I try to answer a question, last time happened the same thing. I really apologize for this. Listen, the... It's the latter. I will wait until we know what we have in hand from FDA, before we make a decision to change our investment trajectory. Right now, you know, we gave a guidance for the year, and we will keep investing toward that same guidance.
Okay. I guess a follow-up to my follow-up and no problem, it happens. What do you consider, I guess, a success? Whether it's 6 months, 12 months, 18 months from now. If you kinda look at it in chunks, what would you consider both kind of a commercial and regulatory success? Thank you, guys.
Yeah. I mean, from my perspective, I'm modest. I would love to continue with the same trajectory that we've been on now the past couple of years in the United States. I sure hope that this data would help us to change the trajectory in Europe. It's a bit early to know that in Germany, right? To get a similar trajectory, that's a hope. If we stay on that same trajectory, that has been very aggressive, and as we grow, it become harder over time, right? To stay at that growth rate. If we stay at that, I will consider this a success. I don't know if I answered your question here.
No, that helps. You brought up Europe. I guess six months from now, you're pretty certain that you're going to have filed for approval at that point, right?
Oh, under that.
Then we're waiting to hear back from the FDA, right? So 12 months from now you should get a good sense of, you know, whether it's an indication, an expansion, et cetera. That's, I guess, what I'm looking for. Thanks.
Yeah. I'm sorry, I misunderstood your question. Margaret, from that regard, it's just one word. If we can get that treatment word in our labeling, that this Barostim device treats heart failure, that for me is a huge success. I don't know if I'm the only one who sees this as a big deal, but it is a big deal.
Okay.
Do we need this? No. We've been doing very well without it. The long-term symptomatic endpoint and the fact that now we have long-term symptomatic improvement in a safe way that does not shorten the life of patients, and we have the proof for that, will be helpful and will help us keep on this growth trajectory. Having that treatment will be really nice.
Great. Thank you, guys. Appreciate it.
Thank you, Margaret.
There are no further questions in the queue. I'd like to hand the call back to management for closing remarks.
Yeah. It seems Jared got it easy this time. I had to answer all of the questions. Well, with this, thank you, operator. I would like to thank everybody here for joining us today for our update call. Also like to extend my sincere thanks and gratitude here to all of the patients, physicians, investigators, nurses, regulators who helped us with this trial. The first part of it is closed. We still have a lot of work to do to get the paper published and everything else. As soon as those will be available, we'd be very glad to share this with you. Now with this, we look forward to updating you on our progress during our next quarterly earnings call. Thanks, everyone.
Ladies and gentlemen, this does conclude today's teleconference. Thank you for your participation. You may disconnect your lines at this time, and have a wonderful day.