Speaker 1:

Welcome to AACE Podcasts. Thanks for tuning in as we elevate clinical endocrinology by taking deep dives into trends and topics that can help us improve our patient care and global health. Find the latest episodes on aace.com/podcasts. And now let's meet the endocrine experts who will be talking with us today.

Dr. David Lieb:

Hello, and welcome to our AACE podcast, focused on AACE guidance documents. I'm Dr. David Lieb, professor of medicine in the Division of Endocrinology at Eastern Virginia Medical School at Old Dominion University in Norfolk, Virginia. I also serve as our endocrinology fellowship program director.

This episode will feature the 2025 algorithm for the management of adults with dyslipidemia. Joining me today are Dr. Shailendra Patel, chair of the algorithm, Dr. Maria Belalcazar, vice chair, and Dr. Robert Hegele, who was an author and representative from the Canadian Cardiovascular Society. Thank you all for joining me today.

Dr. Patel, could you please introduce yourself and tell us about your area of expertise and your role on the guideline?

Dr. Shailendra B. Patel:

Happy to David, and it's great to do this podcast again. I think we did one together on when the lipid guidelines for AACE came out earlier this year. So, I'm a professor of medicine and an endocrinologist at the University of Cincinnati and also staff attending at the Cincinnati VA, although I'm here primarily from my academic hat. My area of expertise, generally I take care of neuroendocrine tumors in my clinical practice as well. And my claim to fame, I suppose, is that my lab was the one that put the rare disease of sitosterolemia on the map and investigated the pathways for this and showed the mechanism of how some of these proteins work to allow xenosterols to stay out of our bodies. And of course, I'm interested in rare genetic disorders like Smith-Lemli-Opitz Syndrome, and cerebrotendinous xanthomatosism, which are lipid disorders.

And then my role on this particular a-logarithm was to be the chair. And like any good chairs, what you do is you surround yourself with absolutely amazing people who are experts. And to that reason, I have to thank not only Rob who is actually on this panel, and Maria who are a part of this podcast, but the rest of the crew who are really absolutely fabulous and made my life completely very, very easy. And I want to call a shout-out to our colleagues from Venezuela, Dr. Ponte, who represented the Latin American Academy of Study for Lipids and Cardiometabolic Risk. Rob, obviously he represents the Canadian Cardiovascular Society, and Fred Karpe, who was part of the European Association for the Study of Diabetes. And of course Ramiro Balderas from Mexico and Aman Rajpal from California and Samina Afreen, who are part of our panel as well. So, my job was to just get out of the experts way and let them do their job.

Dr. David Lieb:

I love how international this committee was to helped to put together this algorithm. And Dr. Belalcazar, can you tell us a little bit about your background and your role on the guideline of the committee?

Dr. Maria Belalcazar:

Sure. Thank you, David. So, I'm a tenured associate professor in the Division of Endocrinology and Metabolism at the University of Texas Medical Branch in Galveston. I became interested in cardiovascular disease and atherosclerosis before residency. I spent a year isolating lipoprotein fractions to study lipid oxidation in the postprandial state with Rob Evans at University of Pittsburgh.

I completed my fellowship at Baylor College of Medicine, and trained there in clinical and research lipidology with doctors Christie Ballantyne and Larry Chan. And then I moved to Galveston, where I am right now, I founded and co-directed for 10 years our Lipid and Cardiovascular Prevention Clinic.

Currently, I'd say my interest in lipids rests mostly on triglycerides. I just love triglycerides, because of the complexity of triglyceride metabolism, how they're influenced by so many factors, and how lifestyle has such a big impact.

And then as a clinician educator, I enjoy helping trainees and colleagues understand lipid metabolism and the rationales for dyslipidemia treatment. Now, in terms of my role as vice chair of the task force, I echo what Dr. Patel said. I think we had the privilege of working with a great group of colleagues with different backgrounds, different countries on this common goal, which was a creation of this practical tool on lipid management for clinicians.

Dr. David Lieb:

Excellent. Thank you. And Dr. Hegele, can you introduce yourself and tell us about your area of expertise and your role on the guideline?

Dr. Robert Hegele:

Thanks Dr. Lieb. It's really my honor to be here, to be among you, to be asked to participate. So I'm Rob Hegele. I'm an endocrinologist in London, Canada, that's in the province of Ontario. I basically am a lipidologist. I have a lipid clinic and I also have a long-standing interest in the genetics of lipid disorders. So, I also have a research lab where we use next-generation sequencing to look into the genomes of our patients with lipid disorders.

And as mentioned, I was representing Canada, I'm a member of the Canadian Cardiovascular Society. And so, I over the years have been an author on the Canadian guidelines for lipids, for management of lipids in the adults, and I've also been invited to serve on European guidelines, European Atherosclerosis Society guidelines. So, I've actually have quite a long involvement in translation of knowledge and trying to implement clinical care [inaudible 00:06:30] anyway. And this group was really a fantastic group of people to work with, and really was a pleasure and an honor to be involved.

Dr. David Lieb:

Thank you all. Today we're discussing the new AACE dyslipidemia algorithm. This is an update to the 2020 algorithm, and was informed by the recent AACE Clinical Practice Guideline for the pharmacologic management of adults with dyslipidemia. Dr. Patel, can you tell us why it was important to update the algorithm in addition to the guideline?

Dr. Shailendra B. Patel:

Like everything in life, I think that these are documents that need updating. And so, the need to update, I think, happens to be something that we have to do every time we have new science, new data, and new ways of practicing. So, this was high time, 2025 is a good time to update something that's at least five years old. Plus we are now entering a different level of sophistication in clinical science. So, we initially had science that was just translated, but people interpreted it. We are now getting much more professional in saying, let's look at the evidence base, and then we come out with guidelines that are just evidence-based. And that evidence base has improved because our ability to do really high quality clinical science has really improved.

We don't have just little case reports or whatever, we have amazingly good studies. So, that evolution has led us to this point. And I think that our update of the guidelines in January that was published, January or February, was really based on the fact that we are now beginning to use new tools to evaluate the science base, and our updated guidelines did that. And of course, it's natural to say now that we've got this, we need to update what really matters to the practicing clinician, the practicing healthcare worker who's going to be dealing with this and say, "We can't give them a very stodgy set of digested evidence base." But something that comes down to give me a quick way of quickly understanding the base and understanding what the practical matters are. And so, this a-logarithm set is really long time overdue.

And the biggest thing when we were discussing this internally was these are things that are universal, and if they're universal, we need to be able to say, around the world, who can we get to participate so that we come up with something that's going to last a little longer and be more applicable so more people can use it?

And we clearly reached out to our professional societies around... We ended up getting the Europeans and the Latin Americans to participate, which I think is just amazing. And that improves our ability to say that when we give this advice, it applies to everyone and it will last a little longer. So, that's the reason for doing the updates. And I think that the goal of this a-logarithm is to provide someone a very quick way of looking at a problem and saying, "How do I dissect it quickly but base it in science, so that the advice that's given, simple as it, is really supported by some very strong science behind the scenes."

Dr. David Lieb:

And that's a great lead into my next question, Dr. Belalcazar, can you tell us what's new or different in the 2025 algorithm compared to the 2020 algorithm?

Dr. Maria Belalcazar:

Sure. So, when I reviewed the 2020 algorithm, I was struck by how well organized and easy to follow the content was. The key information needed to evaluate and treat lipid disorders could just be found by looking at the figures in the document. This was something we wanted to emulate in the 2025 version, and I think thanks to the excellent team of lipid experts, our AACE editor, our graphic designers, I believe we were quite successful.

We have a series of easy to read, colorful, updated evidence-based slides that summarize what you need to know about lipid management, and a narrative that provides more details and a rationale were needed. Now, in terms of the content, I would say that both algorithms recommend a patient-centered risk-based approach. But the 2025 version places a greater emphasis on shared decision making, health equity, individualized care. And I think part of that is because we had the intention of reflecting the AACE grade dyslipidemia guidelines that we used as a framework.

Now, in terms of specific examples of things in the algorithm that are new, for one thing, I think we did a pretty good job expanding on the management of hypertriglyceridemia. So, this algorithm details dietary and pharmacological interventions that vary, depending on the degree and the severity of the hypertriglyceridemia and the treatment goals. Use of fibroids is limited to certain patients with severe hypertriglyceridemia for prevention of pancreatitis, and niacin is no longer recommended in this algorithm.

But one of my favorite updates, I think, is that we are offering a primer on lipid management for special populations. So, we address the issue of people with HIV, pregnant patients, survivors of childhood cancer, et cetera. And we have those slides that are easily accessible and the narratives that gives further details. And then finally, like Dr. Hegele pointed out, we do have a detailed slide on genetic dyslipidemias, and they summarize the clinical assessment, provide information on the genes, and I think this is becoming more and more important as genetic testing is now more accessible than it was five years ago, say.

Dr. David Lieb:

Absolutely. Thank you. And Dr. Hegele, I was going to ask more about the special populations. As Dr. Belalcazar mentioned the updated algorithm highlights a variety of special populations. Can you share some more insight into those groups and how best to care for them?

Dr. Robert Hegele:

I think this is one of the many unique features of this algorithm. So, I think in general, the whole effort, the whole project, is just a quantum leap above what I'm aware of that's already out there in the literature. But specifically, Dr. Lieb, about your question on special population. So, in addition to what Dr. Belalcazar mentioned, so there is also the older adult, this is a question I get all the time in CMEs, what do you do for older adults? And are there any special considerations, different? And so, that's one of the special populations that's dealt with.

Adults with autoimmune disorders. So, there is a huge overlap from many mechanistic points of view between autoimmune disorders and actually medications and dyslipidemia. And then Dr. Belalcazar mentioned adults who are childhood cancer survivors. And then transplant, again, same issue in terms of the primary comorbidity of the condition that required transplantation, but then also medications that are being used in transplantation.

And then really some very innovative that I really haven't seen anywhere else, but for example, adults receiving gender-affirming care, and obviously that has major impact potentially on lipid metabolism. So, these are just some of the examples of some really unique aspects of this particular document. The other thing is in the genetics, the way that the genetics, again, both Dr. Patel and Dr. Belalcazar have mentioned the genetic populations, and it's a rare subset. But then in terms of when we are in the lipid clinic, they end up being enriched. There's an enrichment, and just the way we've set that algorithm up, rather than starting, say, with the gene or the diagnosis, or these Fredrickson types that everybody was forced to memorize. So, we thrown that out and we just start, okay, what's the primary lipid disturbance? And then just follow the algorithm down, and is it primarily triglyceride, or is it a combined hyperlipidemia, or is it an HDL problem?

And then very logically the causal genes and then even going down into clinical features and the treatment pathway. So, I think in addition to just focusing on these special populations, I think just the whole logic and the whole structure of this algorithm and these set of algorithms is unique, from what I've seen in the early return.

Dr. David Lieb:

I love how practical this is, because this is definitely something that I know endocrine fellows often struggle right before they take the board, there's all these different very specific genetic mutations and things to memorize, and I think you can get fixated on some of the minutiae, when really you've got to see the patient in front of you with the very specific lipid abnormalities and then start from there. So, it's incredibly straightforward, I think, in that way for the practicing clinician, for the people that I see in clinic.

So, now I'm going to ask all three of you a question, and the question is, what key points should clinicians keep in mind when applying the new dyslipidemia algorithm in everyday practice? And I'll start by asking Dr. Patel.

Dr. Shailendra B. Patel:

What key points would a practicing clinician want to do? I think that from any disease, any pathology that you are trying to tackle, I think it's what's important for the patient? What are the goals of that therapy? And then what you hope to present to them as therapeutic options, what's the science base behind it? I think that if you keep it simple and say, "What's important to the patient?" That's very important. And I think that being more centric to that, and that means not only what the patient thinks, but what their background is, what their culture is, what their economic status is, that allows them to figure out whether things that we recommend are also affordable is important.

And I think at the end of the day, for atherosclerosis and lipids, let's admit it, our primary goal is nearly always going to be focused around the atherosclerotic disease pathway, right? Why would you treat lipids unless there was clearly some pathobiology and the biggest pathobiology is atherosclerosis, and that means are we making sure that we're changing, bending the curve away from cardiovascular mobility mortality?

So, I think those are the important things. And you want to be able to make sure that the patient is also able to understand. So, the provider needs to be able to translate the explanation of lipids to the patient, because if the patient doesn't get the buy-in, it doesn't matter how smart you are, you're not going to be successful. And I think our a-logarithm, by actually focusing on the simplification, means that if a clinician were able to share that with the patient, I would hope that the patient actually gets to understand aspects of it as well.

So, you don't need in-depth training to be able to read something that's simple. We started this process, and I hope that next time someone revives it they can actually build on some of these concepts so that they can make it better too. That's my spin on it.

Dr. David Lieb:

Absolutely. And Dr. Belalcazar, same question.

Dr. Maria Belalcazar:

So, what I was thinking is what I would like for this algorithm to do in the clinic is to increase awareness that lipid management goes beyond statins, and that there are many patients that we see routinely in clinic that we don't even think that they need to be put on a lipid medication. You have patients with MASLD, or patients with HIV, like we said, that really would benefit.

So, I invite our colleagues to look at the algorithm, have it in the clinic and see how it can be applied. I also think it's important that we share it with our trainees, like you mentioned. This is a great learning tool for students, for residents, and for fellows.

Dr. David Lieb:

For sure. And Dr. Hegele?

Dr. Robert Hegele:

Yeah. So, just actually just expanding on what was previously said, so the thing that's really struck me with it, with the key figures, is that it is really amenable. I could see it being applied at the point of care.

So, in our clinic, for instance, we have the desktop computers and then the screen, and then often we turn them around and then show the patient, or try to do teaching off those. But then all of these algorithms fit so nicely, it's just essentially on the PowerPoint landscape format onto the screen, and very simple flow and logical. And so, even just then to use it to remind yourself, for the practitioner, at the point of care, okay how... So, I think it would be in real time, almost iterative, you're going and using it. So it is useful in that way.

And then I think also depending on [inaudible 00:20:57] not for every patient, but depending on the patient, it can also be used... So, certainly training for our trainees, but then even possibly for the patient, just to show the principles, the logic, here's what you have, it has a name and there's a lot of people have done some thinking behind it, and so on. So I think it's a fantastic roadmap, and I'm starting to use it in my clinic in that way, just as a point of care tool.

Dr. David Lieb:

I love that you're using it in your clinic. So, if one of the experts who's writing this algorithm is using it in their clinic themselves when they're in clinical practice, I think that says it all, Dr. Belalcazar. Where are some of the areas where we need more research or more evidence?

Dr. Maria Belalcazar:

Yeah, so first of all, I think it's important that we remember that clinical outcome data is really needed, and that we can't just go by surrogate data. And this is the case, for example, for inclisiran, one of the medications that we talk about in the algorithm. We have good safety data. We show that it significantly reduces LDL cholesterol, but we really don't have the cardiovascular outcome data yet. So, there's a gap.

Then of course we have major gaps involving patients who are usually excluded from clinical trials. So, the patients with severe hypertriglyceridemia, they're out. Pregnant patients. So we devote quite a bit in our algorithm to that specific population, but we need more data. And then finally, I think there's a big gap in practice that needs to be resolved, and that's the lack of access to the new lipid medications that we face with many of our patients, because they're so expensive.

Dr. David Lieb:

I'm so happy that you brought that up, because I think that's an incredibly important barrier for a lot of the people that we take care of, so it's important that those things are all included. Dr. Hegele, are there medications on the horizon that we need to be paying attention to as endocrinologists?

Dr. Robert Hegele:

Yeah, absolutely, for sure, Dr. Lieb. So, I think the main ones right now they're very imminent. And so, these are these biologics. So, the RNA-directed therapies against apo-CIII. So these have names like olezarsen, which is an antisense oligonucleotide, and then there's plozasiran or plozasiran, which is a short-interfering RNA. So, same principle as say inclisiran or LDL. Then plozasiran and olezarsen are targeting RNA that is involved in triglyceride, the apo-CIII, which is involved in triglyceride metabolism.

Anyway, these drugs have been extremely promising in the early phase clinical trials. In fact, olezarsen's already available, and it has a place for severe hypertriglyceridemia. So the patient with familial chylomicronemia syndrome, or even refractory. So, some patients that may not be purely Mendelian genetic, but we all have them, the patient that you try everything, they do the good faith effort, and they're still running triglycerides over a thousand. They're at the risk of pancreatitis, and we didn't have, up until now, we have not really had great treatment options.

So, those are a couple of examples. The other thing is there are a lot of drugs now being tested against Lp(a). We didn't really talk very much about Lp(a), but this is something to keep an eye on. I think we need to see the outcome trials. I've always been a little bit circumspect about Lp(a) for my whole career. I think it's amazing, I think it's very interesting, but show me the outcome trial. So, we'll have to wait and see.

A lot of other very interesting fringe therapies, I think those are the main ones. I think really, especially the high triglyceride drugs, I think those are ones that would be of interest, particularly to endocrinologists.

Dr. David Lieb:

It's exciting. I was working with the third year medical student today in clinic, and we saw an individual with familial hypercholesterolemia, and just talking about all of the new drugs that have come out in the last five to 10 years, and all the new drugs that are on the way, lipidology is really one of the most exciting areas, I think, within endocrinology.

And I love having something colorful, logical, straightforward to go through with learners, but also like you mentioned, with patients. It makes it easier, I think, for people to understand and accept the therapies, once they understand why they need them, like Dr. Patel, like you mentioned.

Well, thank you all for joining me today. This algorithm is a practical and valuable resource, very valuable resource, that will help clinicians care for patients with dyslipidemia. By distilling the latest research into clear visuals and actionable guidance, it supports better treatment decisions and ultimately improves the care that we provide. To read the full algorithm, visit Pro.AACE.com\clinical-guidance. Thank you.

Speaker 1:

Thanks for listening to another great AACE podcast. Join us for another episode at aace.com/podcasts and help us in our mission to elevate clinical endocrinology. Together we are AACE.