COMMENTARY

Jun 3, 2022 This Week in Cardiology Podcast

John M. Mandrola, MD

Disclosures

June 03, 2022

Please note that the text below is not a full transcript and has not been copyedited. For more insight and commentary on these stories, subscribe to the This Week in Cardiology podcast on Apple Podcasts, Spotify, or your preferred podcast provider. This podcast is intended for healthcare professionals only.

In This Week’s Podcast

For the week ending June 3, 2022, John Mandrola, MD comments on the following news and features stories.

#TWICPodcast

A brief announcement. This podcast needs a hashtag. TWIC (This Week In Cardiology) won’t work because there are tons of TWICs out there. We have decided on #TWICPodcast.

This reminds me to remind everyone that free podcasts such as this one benefit from ratings and reviews. So, please tell us what you like or don’t like. And give us a rating on whichever podcast app you use.

Interatrial Shunts for Heart Failure

Veteran journalist and nice guy Steve Stiles is covering the European Society of Cardiology Heart Failure (ESC-HF) meeting. He’s reported on a small sub-study looking at the use of interatrial shunts to improve outcomes.

The idea is that left atrial pressure is high in patients with HF and if we could create just the right sized hole in the intra-atrial septum, the left atrium could be unloaded without overloading the right ventricle. Bio-engineering the way it is, surely such a device could be made and implanted. It’s plausible.

Before I tell you this story, before I give you my take, I want to set out the tension between innovation and capitalism. For better or worse, most of the Western world of Medicine depends on profit motive for innovative devices and drugs. If you are smart, lucky, and hard-working you might make a drug or device that helps millions. The companies that made ACE inhibitors and pacemakers and stents have made gazillions. They deserve it.

But the other side of that tension is that not all new things are as clearly beneficial as RAS inhibitors, pacers, and stents. This means consumers of innovation have to be clear-headed about what is innovative and what is flat-of-the-curve low value therapy. We have to be careful not to be bamboozled by spin.

Ok, now the specifics. At ESC-HF, as part of a premiere late-breaking science session, Dr. Julio Nunez Villota from the University of Valencia presented a preliminary analysis of 61 patients implanted with a type of interatrial shunt. This unblinded non-controlled “study” was part of the randomized RELIEVE-HF trial’s roll-in group of patients.

RELIEVE-HF is a company sponsored, 500 patient trial comparing an interatrial shunt with standard of care. The primary endpoints (PEP) will be safety and a hierarchical composite of death, transplant, left ventricular assist device (LVAD), hospitalization for HF (HHF), and change in Kansas City Cardiomyopathy Questionnaire (KCCQ). The trial appears to be ongoing.

  • The 61-patient substudy showed that those initially with an LV ejection fraction (EF) below 40% showed a significant 3.5-point improvement in LVEF at 12 months.

  • The mean gain among those with baseline LVEF less than 50% reached 4.6 points (P = .0078).

  • The shunts remained patent throughout the follow-up.

  • There were also gains in some RV parameters by echo.

Comments. You might think, okay, this sounds good. The device seems to be working. That’s good data. Here are the problems:

  • Problem 1 is the fact that a non-controlled, non-blinded 61-patient series looking at surrogate endpoints gets placed in a late-breaking session at a big meeting.

What have major medical meetings come to, that such “science” is presented in the premiere sections? I don’t want to pick on ESC-HF, as the recent American College of Cardiology (ACC) sessions also had some dubious studies presented in the premiere session.

It’s not just nit-picking here. When an organization puts a study in a late-breaking session, they know media will cover it. If it is biased-towards-an-expensive-industry-product study, that tempts medical consumers to become jaded, even cynical, about science being about marketing rather than science.

  • Problem 2: In February, I covered the REDUCE-LAP-HF-2 randomized controlled trial (RCT), a blinded, sham-controlled, multicenter trial of 626 patients with symptomatic heart failure, an EF of at least 40%. One group got an interatrial shunt and the other a sham interatrial shunt placebo.

  • The PEP was also a hierarchical composite endpoint and the study reported no differences between groups in the primary composite endpoint (win ratio 1.0 [95% confidence interval [CI] 0.8–1.2]; P = 0.85) or in the individual components of the PEP.

So, the baseline knowledge here is that a large trial with a proper sham control found no benefits to one company’s shunt.

Now, another company is doing the RELIEVE HF trial with another device; supposedly it makes a slightly smaller hole in the septum. RELIEVE HF will enroll a slightly different patient population. Well, maybe their Goldilocks-sized interatrial shunt will turn the concept around. But a 61-patient run-in study tells us nothing of any value, other than it gets media coverage and premiere spot at a big meeting.

Then there are comments from William Abraham, MD, who said the negative REDUCE LAP-HF and ongoing RELIEVE-HF had different trial designs, different trial procedures, and different patients. Guess who Dr Abraham is? He is now the chief medical officer at V-Wave, the maker of the new interatrial shunt.

I am open-minded to any procedure that provides value to patients with disease. But the way to show value is simple: Do a proper sham control trial, then tell us the results. So we should just wait for RELIEVE-HF.

Twitter for Science Communication:

The European Heart Journal recently published an RCT comparing about 350 published articles that were tweeted out via the ESC feed vs 350 articles that were not Tweeted out. The PEP was citation rate. They also looked at Altmetric score, a measure of media and social media engagement.

  • After about 3 years, articles that were promoted by Twitter had a higher citation rate. The effect size, however, was small, 1.12 (95% CI, 1.08-1.15) This effect was independent of the type of article.

  • Altmetric scores were also higher in the Twitter-arm. These significant results differed from a nonsignificant RCT from Circulation authors in 2015.

  • My explanation for these differences is that 2022 Twitter is likely a lot more active than 2015 Twitter.

Comments. Twitter is two-edged sword. On the one hand, its business model is to enrage and divide people because doing so increases time on its website. This can make parts of Twitter a cesspool of human ugliness. You should always be aware that the algorithm is coming for you. And thus, never Tweet when angry.

But the fact remains that oodles of doctors and scientists use this site. I’ve been focusing on #GoodTwitter in which doctors and scientists share knowledge and opinion. If you avoid COVID, race, gender, and other hot-button policy debates, there remains a nice space for science discussion and learning. For example, I’m working on a project (that I will someday tell you more about) and have crowd-sourced people’s opinions about topics such as, “what are good uses of observational data?” and “what is the most important medical study in the last half-century.” These threads have yielded educational gold.

Finally, as a I told a group of young researchers recently in Denmark, you should absolutely be on Twitter or other forms of social media. When you publish a paper, you should also write a blog post or record a YouTube about it—especially if the article is paywalled. Tell us about your findings. Tell us your limitations. Tell us about the process of science.

Then Tweet it all out in a thread and engage with reasonable discussion. There is no reason to be anonymous about such important work. Forget Janteloven when it comes to your science.

HDL Surprises

JAMA-Cardiology has published an interesting observational study from Emory investigators who looked at the association of very high HDL cholesterol levels in patients with established coronary artery disease (CAD). Emphasis here that these were patients with CAD.

They used the UK Biobank and an Emory Biobank. Total patients were around 20,000; 15,000 were from UK and 5000 from Emory. The exposure was an HDL > 80 mg/dL. The outcome of interest was all-cause death. Secondary outcome, cardiovascular disease (CVD). Follow-up was quite long at 6 to 9 years.

The researchers then focused on three categories of HDL. The control arm, so to speak, included patients with CAD who had HDL levels from 40 to 60 mg/dL. Under 40 mg/dL was an obvious higher risk group, and those with HDL levels above 80 mg/dL were the group of interest.

  • An HDL > 80 mg/dL in patients with known CAD is uncommon but not rare. In both databases, the total number of patients with this HDL level was less than 2%.

  • The main finding was a U-shaped curve of the hazard ratio (HR) of all cause death and HDL.

    • If your HDL was low, you had a higher risk, but if your HDL was higher than 80 mg/dL, you also had a higher risk of all-cause death, even after adjustments.

  • The pattern was strikingly similar in the two databanks. The pattern was also seen with CV death in both cohorts. Compared with a normal HDL, very high HDL levels had an HR of 1.96 for all-cause death.

Another nifty part of the study is that the UK Biobank has genetic risk scores (GRS), and there is one for HDL-C. These U-shaped associations persisted after adjustment for the HDL GRS within the UK Biobank. The GRS did indeed correlate very well with levels of HDL—if you had a high GRS, then you had a higher HDL. After adding the HDL GRS to the fully adjusted models, the association with HDL cholesterol levels greater than 80 mg/dL was not attenuated, indicating that HDL genetic variations in the GRS do not contribute substantially to the risk.

The authors concluded that this data suggested that very high HDL levels are paradoxically associated with higher mortality risk in individuals with CAD, and that this association was independent of the common polymorphisms associated with high HDL levels.

Comments. First thing to say is that these associations pertain only to patients with CAD. A person without CAD in your office who has an HDL of 83 mg/dL may not have the same risk. In fact, whenever you see a study that focuses on a select group of patients—here, those who already had CAD—and then reports a “paradoxical” relationship, you have to be on alert for a collider or selection bias. Thus, I see two possibilities here.

  • One is that, since these patients with high HDL already had CAD, there may be some other confounding factor that led to both having CAD and a high HDL. A collider if you will.

  • The other and I think more likely possibility is that the high HDL is at least partially causal. I say this is more likely because the authors cite other studies that have shown associations of high HDL and increased risk of CV events.

Recall that HDL is reverse transporter in part. It can be high because of high production (good) or because of poor clearance of HDL (bad). University of Michigan professor Venk Murthy reminded me that it is context dependent. A resting systolic blood pressure (SBP) of 95 can be good, but a resting SBP of 95 in sepsis is ominous.

Murthy also sent me a paper from Science that reported that genetic variants in the HDL receptor called Scavenger receptor BI (SR-BI) lead to loss of function and thus higher HDL levels and this gene variant is often associated with more CAD. That’s right. These individuals, and also in a mice model, have receptors that do not allow HDL in the cells, therefore it’s higher in the body, yet they can have a higher risk of CAD. The mechanism behind this is not entirely established.

I would also note that while this paper used a cut-off of HDL of 80 mg/dL, the authors also report that even a level of 60 to 80 mg/dL led to increased risk in patients with CAD.

I believe the simple story about HDL and good cholesterol is overly soft thinking. We’ve had the idea that high HDL levels are protective, and two-times good or three times good has to be better, right? Well, if that were true, why would HDL-raising drugs fail to improve outcomes?

I guess if most of us were lipid experts, we would know about Scavenger receptors and the complex biology surrounding HDL. But we aren’t experts, and this paper reminds us that high HDL-C levels, even in patients with CAD, are not rare; and it reiterates how little we know, and how careful we should be labeling surrogate markers or signs as bad or good without context. The complexity, the vast knowledge gaps is why I love Medicine so much.

Dubious Sub-studies

We have to talk about the novel, first in class cardiac myosin activator Omecamtiv mecarbil (OM). The reason we have to discuss it is sad.

Let’s start from the beginning. The drug, which is not yet approved by the US Food and Drug Administration (FDA), augments cardiac contractility by selectively binding to cardiac myosin, thus increasing the number of force generators (myosin heads) that can bind to the actin filament and initiate a power stroke at the start of systole.

In other words, it’s a positive inotrope and you know how these have worked out in chronic HF. Hint: Not good.

The first pivotal trial called GALACTIC-HF randomly assigned about 8500 patients with symptomatic chronic HF and an EF < 35 to OM or placebo. The primary outcome was a typical HF primary: a composite of a first HF event (hospitalization or urgent visit for heart failure) or death from CV causes.

  • The trial was technically positive; 37% of patients in OM group had a PEP vs 39.1% in the placebo arm.

  • The HR or relative risk reduction was only 8%; HR 0.92.

  • The CI went from 0.86 (a 14% reduction) to 0.99 (a 1% reduction) and the P-value snuck by at 0.03.

  • There were no significant reductions in overall death, CV death or quality of life (QOL) measures. This is quite remarkable since nearly 20% of both arms had a CV death, so it wasn’t because event rates were so low.

Chapter 2 of the OM story came at ACC 2022 where we learned the results of the METEORIC-HF trial. METEORIC was a multicenter trial of 276 patients with HF with reduced EF who were randomly assigned to OM vs placebo. The PEP was the change in peak oxygen consumption (VO2) from baseline to 20 weeks on CPET.

  • There was very little change in either arm over the treatment period.

  • The between-group difference at 20 weeks favored placebo but was not significant (P = 0.13).

  • Absolutely negative; no effect on exercise capacity.

So here we have a new drug, with no effect on QOL, no effect on exercise capacity, no reduction in CV death or overall death, and a statistically fragile tiny effect in an outcomes trial. Even Amgen, one of the makers of the drug bailed on it last year. “The Big Biotech walked, passing the rights to the program back to Cytokinetics in November and ending a nearly 15-year collaboration.” Cytokinetics aims to get the drug FDA approved.

This week, the European Heart Journal published a sub study of GALACTIC. For this study the authors considered two groups: those who had a baseline SBP < 100 mmHg (about 18%) and those who had a baseline SBP > 100 mmHg (about 82%). They then looked at the primary outcome in these two groups.

  • The primary outcome occurred in 715 (48.5%) and 2,415 (35.7%) patients with SBP ≤100 mmHg and >100 mmHg, respectively.

  • For those with low BP, the HR was 0.81; 95% CI, 0.70-0.94.

  • For those with SBP >100 mmHg, HR was 0.95; 95% CI, 0.88-1.03; P-value for interaction = 0.051.

The authors conclude: “In GALACTIC-HF, risk reduction of heart failure outcomes with Omecamtiv mecarbil compared with placebo was large and significant in patients with low SBP.”

Comments. My friends, when you see stuff like this, my advice is to go immediately to the paragraph on limitations. Here are the first three sentences, in the authors’ words:

  • First, it represents a post-hoc analysis of the GALACTIC-HF randomized trial since no subgroup analysis was pre-specified.

  • The SBP categories chosen in our study were arbitrary.

  • Furthermore, subgroup analyses may have limited statistical power because of limited sample size and number of events.

I am so depressed about this. The main trial barely made significance and had a clinically insignificant effect size. A separate RCT found no effect on exercise capacity. Then the authors of GALACTIC come up with an arbitrary BP cutoff and do an after-the-fact analysis that finds a positive result.

  • Post hoc analysis means they had seen the results already and did a separate analysis.

  • And a major journal publishes it.

  • Then you read the disclosures, and two of the authors are industry employees.

The reason this depresses me is that it reduces trust. If conflicted authors do dubious analyses that lead to favorable conclusions for the product being tested, and journals publish it without strong accompanying editorials, then what happens when important studies come along? How are we to trust the scientific process?

I guess all we can do is keep our guard up. Ultimately, if we don’t prescribe dubious low-value therapies, such as OM, CARDIOMEMS, Watchman, it doesn’t matter if the FDA approves things. But it’s hard to resist the therapeutic fashion of the day. I get that. But I will keep trying.

Comments

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