The Peter Attia Drive - November 29, 2021


#185 - Allan Sniderman, M.D.: Cardiovascular disease and why we should change the way we assess risk


Episode Stats

Length

2 hours and 2 minutes

Words per Minute

151.39651

Word Count

18,576

Sentence Count

1,240

Hate Speech Sentences

10


Summary

Dr. Alan Snyderman is a senior scientist at the Research Institute of McGill University Health Center, and the Edwards Professor of Cardiology and Professor of Medicine at McGill University. He is the Director of the Mike Rosenblum Laboratory for Cardiovascular Research at Royal Victoria Hospital in Montreal, and was elected a Fellow of the Royal Society of Canada in 2009.


Transcript

00:00:00.000 Hey everyone, welcome to the drive podcast. I'm your host, Peter Atiyah. This podcast,
00:00:15.480 my website and my weekly newsletter all focus on the goal of translating the science of longevity
00:00:19.800 into something accessible for everyone. Our goal is to provide the best content in health and
00:00:24.760 wellness full stop. And we've assembled a great team of analysts to make this happen.
00:00:28.880 If you enjoy this podcast, we've created a membership program that brings you far more
00:00:33.280 in-depth content. If you want to take your knowledge of the space to the next level at
00:00:37.320 the end of this episode, I'll explain what those benefits are. Or if you want to learn more now,
00:00:41.720 head over to peteratiyahmd.com forward slash subscribe. Now, without further delay, here's
00:00:48.080 today's episode. My guest this week is Dr. Alan Snyderman. Alan is a senior scientist at the
00:00:54.920 Research Institute of McGill University Health Center and the Edwards Professor of Cardiology
00:00:59.140 and Professor of Medicine at McGill University. He's the director of the Mike Rosenblum Laboratory
00:01:05.680 for Cardiovascular Research at Royal Victoria Hospital in Montreal. And he was elected a fellow
00:01:10.760 of the Royal Society of Canada in 2009. He's also been an enormous mentor of mine for the past 10 years.
00:01:17.460 Certainly one of the three or four people I would count that has nearly single-handedly provided me
00:01:24.220 with the education that I try to use today to help understand cardiovascular disease. A number of you
00:01:30.680 may recognize the name Alan. I've certainly included him in some of the things I've written about. And
00:01:35.620 also he's been mentioned a number of times on previous podcasts featuring no less than Tom Dayspring
00:01:41.140 and Ron Krause. His memberships are probably too numerous to mention, but a few of them include
00:01:47.520 the Royal College of Physicians and Surgeons in Canada, the American College of Cardiology,
00:01:52.480 the American College of Physicians, the Canadian Cardiovascular Society, the American Society for
00:01:56.540 Clinical Investigation, the American Federation for Clinical Research, and a number of others.
00:02:02.280 Okay. This is a bit of a complicated topic. We go very deep on cardiovascular medicine,
00:02:09.660 and we actually start this podcast not in a way that I intended to because in the first 10 or 15
00:02:18.640 minutes, Alan lays out some of the most clear, complex, and you might say, well, how can those
00:02:26.580 be used the same? But what I mean is clear thinking of complex concepts that you'll ever hear anybody
00:02:33.380 talk about with respect to ApoB and risk management. It becomes clear to me as I
00:02:39.640 get engulfed in that discussion that I need to back this way up so that everyone listening to
00:02:44.600 this who doesn't already find themselves steeped in that literature can orient themselves. So my
00:02:50.060 first comment here is don't be dissuaded by how complicated the first 10 or 15 minutes of this
00:02:55.080 podcast is. Instead, just try to sit tight and we'll walk you through the journey of what ApoB is
00:03:02.300 and why it is a superior metric for predicting risk of atherosclerosis relative to the far more
00:03:08.380 commonly used metric LDL cholesterol and the metric that is better than LDL cholesterol,
00:03:13.540 but still inferior to ApoB, which is non-HDL cholesterol. We also go into great detail about
00:03:18.820 the role of triglycerides, HDL cholesterol, total cholesterol, et cetera, in the understanding of and
00:03:24.560 prediction of cardiovascular disease. We get into some of the interesting exceptions,
00:03:29.620 i.e. disease states where not knowing ApoB poses an enormous blind spot. And we talk about the
00:03:37.140 challenges that face people like Alan as they try to disseminate the most leading edge and cutting
00:03:44.120 edge science on this topic in an environment that is really wed to guidelines and consensus-based
00:03:52.320 recommendations that don't necessarily incorporate all of the best evidence.
00:03:56.900 We also explain some concepts like Mendelian randomization and how that's been used to
00:04:02.040 further bolster the case for ApoB as the superior metric for risk prediction. And we talk about
00:04:08.080 where coronary artery calcium scoring comes in. This is obviously an important tool used by many
00:04:13.400 physicians and it's important to understand how it's useful and what its blind spots are. So
00:04:18.060 without further delay, please enjoy my conversation with Dr. Alan Snyder.
00:04:26.900 Thanks so much for making time to sit down today. This is one of those discussions I've been meaning
00:04:33.500 to have for over a decade. And I suspect much of what we speak about today will be reminiscent of
00:04:40.140 things we've spoken about, usually in person over a meal over the past decade. So welcome to the show
00:04:45.640 and sorry that we can't be doing this in person. Thank you so much.
00:04:49.380 So I think listeners of the show will be pretty familiar with your name because certainly I've
00:04:55.360 brought it up before, as have other people on the show, most notably probably Tom Dayspring.
00:05:00.140 I've also probably referenced on at least one or two occasions, the textbook you gave me,
00:05:05.940 God, probably about eight years ago. Do you remember what book you gave me?
00:05:09.580 I'm trying to remember which, I think it was the book I did with Jacqueline de Grau.
00:05:14.280 Yeah. That is one of them. But the one I'm referring to is actually, I think it's Herbert
00:05:17.940 Starry, the pathology book. Oh, right, right, right, right, right, right, right. Oh, now I'm
00:05:22.360 with you. Yeah, yeah, yeah. You just immediately blew my mind. I then went out and bought as many
00:05:28.240 of them as I could find on Amazon and they were prohibitively expensive. Tell me and tell the
00:05:32.620 listeners, why did you give me that book? I'm trying to recall. Atherosclerosis, it's a disease in the
00:05:39.800 tissue. And almost everything that lipid people talk about is in plasma. And if we don't understand
00:05:47.380 the natural history of the disease, how can we construct a strategy to prevent it? And although
00:05:55.400 much of my work has been on ApoB, the more important part, I think, has been on understanding
00:06:03.800 how the natural history of atherosclerosis should direct our prevention strategy. What that leads to
00:06:13.300 is that every major guideline in the world bases their selection of subjects for statin prevention
00:06:22.540 prevention on the 10-year risk of disease. And that was a huge step forward in 1980 and 1990.
00:06:33.240 But it totally, or not totally, but it very fundamentally makes prevention of premature
00:06:42.260 disease almost impossible. When you plug in the numbers to calculate somebody's risk for any of the
00:06:51.140 risk algorithms, the American College of Cardiology, 2019 AHA, multi-society, you plug in numbers that
00:06:59.500 belong to that particular patient. And what comes out is what you think is the risk for that particular
00:07:08.740 patient. It actually isn't. But what drives that calculation is the age and the sex of that patient.
00:07:18.480 Things like cholesterol, blood pressure, they contribute minimally to the actual calculation of 10-year risk.
00:07:28.740 So what that means is if you're 35, but there is even a risk calculator for you, but if you get to 40,
00:07:36.200 almost everybody's risk is low at age 40. And it is until you get to about 55, 60, that risk gets you over the
00:07:45.160 threshold for the American prevention guideline treatment. So prevention really starts at 55 to 60.
00:07:54.380 But half, almost half of all infarcts and strokes occur before the age of 60. So how can that be?
00:08:06.380 What Starry and his colleagues established was, for the first three decades or so of life, the disease begins,
00:08:14.720 gets a foothold in the artery. But it's only in the fourth decade that you start to develop the lesions
00:08:21.260 that can actually precipitate a clinical event. But risk is low, and yet the event rate is high.
00:08:28.660 How can that possibly be? Well, the answer is stunningly obvious, which we published. There are
00:08:36.780 a ton more people under 60 than over 60. So the rate of events is low, but the absolute number of events
00:08:47.140 is high. That's problem number one. Problem number two is, say you get to 60 and you didn't have an event.
00:08:56.660 Well, the disease was developing and extending during your 30s, 40s, and 50s. So by the time we start to try
00:09:06.440 and prevent an event, the disease is well advanced in the arteries. That, to me, are the two fatal flaws
00:09:16.540 in the 10-year risk approach. And we published a paper pointing this out in JAMA Cardiology a few years
00:09:23.720 ago. Borden, Nordischgaard, and his colleagues have done exactly the same thing with the European
00:09:28.240 guidelines. You can't beat these numbers. So rather than what Steri taught me, and it took some years
00:09:39.180 before we could develop the methodology, of course risk is a good concept. Of course it is.
00:09:46.120 But we should be selecting people also based on causes. I can measure your ApoB pretty precisely.
00:09:56.400 I could measure your non-HDL cholesterol a little less precisely, but pretty well. And I know it's
00:10:02.980 yours. When I calculate the risk, if I said, okay, Peter, you're my patient, you're a healthy guy,
00:10:11.240 I calculate your risk is 4.1%. Now, what does that number mean? Is that your risk? Nope. It means that
00:10:22.080 out of 100 people at 4.1%, 4.1 of them will have an infarct. But we know that within that category,
00:10:30.900 there's a tremendous variance in real risk. Not everybody's at 4.1. Some are higher, some are lower,
00:10:38.980 some are dead on. So if I had two risk algorithms, the philosopher, A.J. Ayer, the English, the logical
00:10:49.440 positive, he was actually darn good on probability. There's a real challenge predicting singular events.
00:10:58.600 I'm either going to have an infarct in the next year or I'm not. It's not really a probability.
00:11:04.000 So I either am or I'm not. If one algorithm said I had a 10% risk and another one said I had a 15%
00:11:11.560 or 20%, whether I have an infarct or not, both of them were right because they said there was sort
00:11:19.280 of a chance you could and there was a far larger chance you wouldn't. When we say people should be
00:11:27.020 treated with a risk above 7.5%, that means 92.5% of the time, nothing will happen. Well, that's not
00:11:34.840 a great incentive, I think, for helping people understand what's truly going to happen. So the
00:11:41.140 way we can deal with this and what we've done is develop what's called a causal benefit model.
00:11:46.580 We measure it, non-HDL or ApoB, and we can project the risk over 20 or 30 years. If you're 30 years old,
00:11:56.660 the period of time you should care about is up to age at least to 60. And so if you were in a group,
00:12:04.860 let's say, and let's say I make you 35 again, and I say your chances of having an infarct or a stroke
00:12:12.360 before you're 65 are 30%, now that's a number you can deal with. That's a number that has meaning.
00:12:20.240 And we can also calculate how much the risk can be reduced by starting at age 35, or how much you
00:12:28.020 lose by starting at age 45, or how much more you lose by starting at age 55. When I gave you that
00:12:36.560 book, I was starting my own journey on trying to construct an alternative to the present risk model,
00:12:45.520 which with the help of my colleague here at McGill, George Stanisoulis, and Michael Pensina from Duke
00:12:52.040 and Carol Pensina from Harvard, we've done. Something about it, Alan, that also brought home
00:12:58.900 another message that had been somewhat left in the garage of my brain. As you may recall, I trained in
00:13:07.240 general surgery. So the kids in med school who are going to go into surgery, we're not the sharpest tools
00:13:12.920 in the shed, like the kids that go into internal medicine. But I still remembered a couple of things
00:13:18.080 from my pathology class. And one of the things I remembered from pathology A, so it's the first of
00:13:23.760 the three major classes you take in pathology, was something that the professor said, which is he said,
00:13:30.040 no doctor has more experience with what it is to have heart attacks than pathologists. Because 50%
00:13:41.560 of the people who have a heart attack die on their first heart attack. So he said, I'm seeing 50%
00:13:50.360 of the people who have a heart attack and their first presentation is death. So I kind of remembered
00:13:57.220 that. And it's a very sobering fact to think that half the time, and again, I don't think that's true
00:14:02.420 today, but I think 25 years ago, that was the case. The numbers are probably a bit better today.
00:14:06.760 It might be a third of first events are fatal, but nevertheless, it was sobering. So you have this
00:14:13.440 sort of weird factoid that's again, often the recesses of my brain somewhere. And then you hand
00:14:18.580 me this textbook and it actually made sense with what he said, because in addition to going through
00:14:27.340 in great detail, the pathological staging of atherosclerosis, it was littered with autopsy
00:14:32.540 sections of coronary arteries of people who had died for other reasons. And notably they were
00:14:39.340 quite young. So here's a 26 year old male victim of a gunshot wound. Here's a 27 year old female who
00:14:46.200 died in a motor vehicle accident. Here's a so-and-so and so-and-so. And when you look at their coronary
00:14:51.660 arteries, you realize they already have atherosclerosis. They already have oxidized
00:15:01.100 ApoB bearing particles engulfed by macrophages and thickened intima. And while they may not have
00:15:08.400 calcification in their arteries yet, or the types of plaque that would rupture within the ensuing
00:15:14.740 weeks or days or months, they nevertheless had atherosclerosis and they were in their twenties
00:15:19.660 and in their thirties. So all of a sudden what this professor said 20 some odd years earlier
00:15:26.580 made sense, which is this was now an explanation. This was a bridge to explain what otherwise seemed
00:15:33.140 hard to understand. That's the thing I took away from it in the instant you handed it to me, as we
00:15:37.940 were literally looking at it in the restaurant. The thing I'd emphasize is how, when you have
00:15:42.680 atherosclerosis, I mean, as a cardiologist, we're so used to looking at angiograms. We say,
00:15:47.700 oh, there's an LAD lesion. Well, there's an LAD lesion, but the whole damn artery is diseased.
00:15:53.980 And when you destroy the normal architecture of the artery, you can't restore it. So a lot of our
00:16:03.820 statin prevention therapy is to prevent the complications of disease, not to prevent the
00:16:13.020 disease. And statins lower ApoB particle number. That's how they work. Fewer ApoB particles in
00:16:23.300 plasma, fewer get into the arterial wall, fewer get trapped. It's not that complicated.
00:16:30.640 So let's back up for a minute because I think everything we've just talked about for the last,
00:16:35.080 whatever it's been 10 minutes is in many ways, the advanced, advanced seminar on prevention of
00:16:43.180 atherosclerosis. So now let's go back and set the stage for this, because there are going to be a
00:16:49.180 number of people listening to this who perhaps have not heard previous discussions I've had on this
00:16:54.160 subject matter. So let's back way up and start with what is cholesterol and how does it relate to this
00:17:03.180 thing called ApoB that you've mentioned a number of times already? Most people would have heard of
00:17:07.920 cholesterol and most people understand that you can measure it when you take somebody's blood,
00:17:12.960 but this ApoB thing might be new to some people. Cholesterol is obviously a fat, a lipid. It's a
00:17:20.540 critical element in cell structure. It's in all cell membranes. The amount that's in the cell membrane
00:17:27.980 is determinant of the function of the membrane. All the cells in the body can synthesize cholesterol.
00:17:36.220 Only the liver can really break it down in any amount and excrete it. So when we eat, we absorb
00:17:44.600 cholesterol and fatty acids in the form of triglycerides, and they get resynthesized in the
00:17:51.240 intestine into particles. You can't transport cholesterol and triglyceride. Triglycerides are the
00:17:57.720 fatty acids tacked onto a glycerol backbone. They don't mix with water. They're not soluble. So you
00:18:03.780 have to put them in particles, like soap bubbles. And there are a variety of different particles.
00:18:12.260 The ones from the intestine that take the fat that we absorb, the cholesterol and the triglyceride,
00:18:19.220 they're very large particles. There are very few of them. They have a protein called ApoB48 on the
00:18:27.000 outside surface, which gives integrity to the particle, structural integrity. There are also
00:18:33.600 a bunch of other proteins. The chylomicrons deposit, they go to skeletal muscle, adipose tissue,
00:18:41.900 and the heart. And the fatty acids are taken out. They're liberated from the triglycerides and rapidly
00:18:48.800 taken up by these three tissues. The particle that's left is now much smaller because most of the
00:18:54.800 triglyceride has been taken out of it. And it goes to the liver and drops the cholesterol off. So
00:19:00.820 the cholesterol we eat in the diet goes to the liver, and it tends to reduce the synthesis of
00:19:07.260 cholesterol in the liver. The liver gets inundated with fatty acids and cholesterol from all over the
00:19:13.300 place, kilomicrons, HDL, LDL particles. There's a system to regulate the mass of cholesterol and
00:19:24.160 triglyceride in the liver. And that's the VLDL ApoB system. VLDL particles have a molecule of ApoB100,
00:19:35.600 which is longer, twice as long as ApoB48. And that gives a structural integrity of the particle.
00:19:41.820 It does one other thing I'll get to. And that particle removes triglyceride and cholesterol from
00:19:48.320 the liver to maintain the balance in the liver. The triglyceride, just as in the case of chylomicron,
00:19:55.300 gets dropped off in adipose tissue and skeletal muscle and cardiac muscle. So the VLDL particle
00:20:03.180 gets smaller and more cholesterol-rich. And it eventually becomes an LDL particle. And an LDL particle
00:20:11.480 is a cholesterol-rich particle with relatively little triglyceride in it. When we measure the
00:20:17.740 cholesterol in the blood, the total cholesterol is the cholesterol in the VLDL particle, the LDL
00:20:25.060 particle, and the HDL particle, the good guys, quote unquote. The non-HDL cholesterol is the mass of
00:20:33.560 cholesterol in VLDL particles and LDL particles. Now, isn't that enough? Isn't that all we really need
00:20:41.800 to know? It tells you a lot? No question. But I'm going to give you two people. They both have the
00:20:49.740 same LDL cholesterol. Their cholesterol is 125. One of them tends to have larger LDL particles.
00:20:59.580 One of them tends to have smaller LDL particles. In order to carry the same amount of cholesterol,
00:21:06.920 there got to be more little ones than big ones. So their LDL cholesterol is the same. Is there any
00:21:14.720 difference in their atherogenic risk? And the answer is yes, yes, yes, and yes. The one with the
00:21:20.780 increased number of particles has higher atherogenic risk because any cholesterol in the artery only got
00:21:27.760 there within an ApoV particle. It doesn't just float in. It gets there within an ApoV particle, either
00:21:35.040 VLD or LDL, that gets into the arterial wall and gets stuck there. And that's the cause of atherosclerosis.
00:21:45.880 There are lots of things that contribute to multiplying or diminishing the cause, but that's
00:21:52.640 the cause. Sticking of an ApoV particle within the wall. And because cholesterol gets in there within
00:22:00.320 the particles, knowing the number of particles is more important even than knowing the cholesterol level.
00:22:07.020 Alan, when did that historically become apparent? If we take a step way, way, way back, if we go back
00:22:13.180 into the 1950s, Ancel Keys was potentially one of the first people to utilize the then nascent assay for
00:22:23.740 measuring total plasma cholesterol. So to your point earlier, that number, let's say you measure 200
00:22:31.340 milligrams per deciliter. That's simply telling you that that's the sum total of cholesterol in all of
00:22:38.220 the lipoproteins. And what Ancel Keys and others observed, and this was by now we're probably into
00:22:44.380 1957, 1958, was, hey, if you stratify people at the bottom 5% and people at the top 5%, so that might be
00:22:56.000 people whose total cholesterol is less than maybe 100 milligrams per deciliter, and people whose total
00:23:02.120 cholesterol is more than 200 milligrams per deciliter, there's a stark difference in their mortality, or rather
00:23:09.660 in their risk of cardiovascular disease. And became very interesting. It turned out that there wasn't a great
00:23:16.820 way to predict that. So the amount of cholesterol a person ate did not seem to predict that. But nevertheless,
00:23:24.120 other dietary factors, saturated fat intake for one, seemed to predict that difference. It would be, what, maybe
00:23:31.920 20, less than 20, 15 years later, that Friedrichsen, Levy, Lees, and others would start to fractionate
00:23:39.500 those lipoproteins and realize that, well, actually, there's different versions. As you alluded to,
00:23:46.140 there are some that have low density, there are some that have high density. And I don't know exactly
00:23:52.180 when it became clear just how nuanced that was, that ApoA is on one and ApoB is on the other. But when did
00:23:58.920 it become clear that there was a discordance between the cholesterol concentration in the LDL
00:24:08.880 particle and the number of LDL particles? I think Bob Lees, in 1971, he had a paper in Science.
00:24:16.660 He was measuring LDL ApoB, the number of LDL particles. And he showed it had no clear relation
00:24:23.320 to plasma triglycerides or to the cholesterol. I mean, there was sort of a relation, but it wasn't exact.
00:24:29.620 And Ron Krauss, of course, and his colleagues, and I did at least one paper, one or two papers with
00:24:39.180 him at the very beginning, were the ones who actually showed in the John Goffman tradition
00:24:45.300 from Berkeley, showed that there were important differences in size, and these related to differences
00:24:51.600 in the amount of cholesterol mass per particle. So Ron Krauss and the group there, and then a whole
00:24:58.960 bunch of other people, and deserve, I think, the credit. But we're way back in the 70s, late 70s.
00:25:07.280 1980 was my first paper, clinical paper, showing with Peter Quitterich, the late Pete Quitterich from
00:25:14.920 Hopkins. We looked at a bunch of patients with coronary angiography, and we compared people
00:25:22.840 with clean coronaries, like clean, to people with diseased coronaries, like disease. There was a
00:25:29.880 little difference in triglyceride, there was a difference in cholesterol, but there was a marked
00:25:35.100 difference in ApoB. And that was the first, I think, clinically solid observations, along with
00:25:44.520 an Italian group that had much close to the same observations, slightly ahead of us for that matter,
00:25:51.520 saying that, look, particles could be more important than cholesterol. And it seems like forever since
00:25:59.480 then, 1980 to now, trying to, and I think largely now succeeding in developing the evidence that you can
00:26:11.940 say, incontrovertibly, particles more than cholesterol. Now, that hasn't moved the American
00:26:18.820 guidelines. But on the evidence side, there are a handful of studies that show that non-HDL cholesterol
00:26:28.420 may be equal to ApoB. There are more studies that actually show ApoB is better. But we developed a way
00:26:36.100 of looking at it called discordance analysis to identify people who had a high non-HDL cholesterol,
00:26:43.320 which is the total cholesterol in the ApoB particles, but a low ApoB total number of particles,
00:26:50.340 versus low non-HDL, high ApoB. So if you're a cholesterol maven, you got to bet on the one with
00:26:59.340 a high non-HDL. If you're an ApoB aficionado, you bet on the one with a lower non-HDL, higher ApoB.
00:27:07.860 They all show it's ApoB. Now, is the argument, Alan, if one argues that in the at least equivalence
00:27:15.900 of, if not superiority, of non-HDL cholesterol as the superior metric, or at least equivalent metric,
00:27:22.980 is it because you're arguing a different mechanism of action? Or does everybody agree on the mechanism
00:27:28.880 of action, and they're simply saying measuring cholesterol content is a good enough proxy for
00:27:34.980 counting the number of particles? Nobody suggests there's a different mechanism. There are some
00:27:39.880 people who argue that VLDL particles are more atherogenic than LDL particles, and I think they've
00:27:45.140 got a long way to go to prove that. What people did argue was there were problems with the ApoB
00:27:50.960 assay, and that it costs money. And the reality is the ApoB assay was standardized back in 1994.
00:27:59.980 The measurement of HDL cholesterol is not standardized. The measurement of LDL cholesterol,
00:28:05.980 not standardized. The measurement of triglycerides, not standardized.
00:28:10.720 In terms of the cost argument, because I actually had that argument with a physician as recently as
00:28:16.500 three months ago, who accused me of getting ApoB on patients as a way to upcharge them,
00:28:25.920 even though I don't make any money on labs. But I actually called the lab that we use and said,
00:28:31.580 what's your cash price for ApoB? Want to know what it was?
00:28:36.440 Please.
00:28:37.640 $2.50. It's a real moneymaker.
00:28:40.580 Yeah, yeah. You know how much it is in my hospital? It's $2. This cost argument has been used
00:28:47.240 without documentation as a killer argument. And there were labs that charged way too much.
00:28:55.420 Welcome to America. In general, your charges are higher than ours in my little country. But that's
00:29:02.660 a function of how much somebody's billing, not a function of what the assay costs.
00:29:07.060 And ApoB, it really ticks me off. Because if you take India for a moment, or almost anywhere,
00:29:16.840 if a doctor gets a report now, he gets total cholesterol, triglycerides, non-HDLC, LDL-C,
00:29:26.020 HDL-C. Five numbers. Do you think he actually looks at any of those numbers? He's trying to do a
00:29:32.340 good job. He does. But let's say the triglycerides are high. Can he do anything with that? Nope.
00:29:39.080 Because everything is based on LDL-C. So he's got, in reality, four numbers that are doing nothing.
00:29:46.660 Let's explain that to people, Alan, because you and I know the ins and outs of that very well. But I
00:29:51.300 think most people here don't understand the difference between the calculated and measured LDL.
00:29:56.840 So let's start with that. And then let's talk about how VLDL has been estimated. And let's bring this
00:30:03.200 all back in terms of some other work you've done, which is understanding the role of triglyceride
00:30:08.800 in ApoB. So let's start with the basic. You go to the doctor, you get a set of labs done,
00:30:14.180 and the LDL number comes back at 140 milligrams per deciliter. Is that actually what it is? Or is that
00:30:20.360 an estimation? That's an estimation. It's almost always a calculation. And there are at least eight
00:30:27.520 different methods to calculate LDL cholesterol. So if there are eight different methods, they don't
00:30:32.740 all give the same answer, or you wouldn't have eight different methods. LDL cholesterol can also
00:30:38.140 be measured directly. That assay has never been validated in disease patients. And no one has ever
00:30:45.240 published a paper showing that it's more accurate in terms of disease identification than calculated
00:30:52.580 LDL cholesterol. And yet people have paid good money for that lab test. There's no question that
00:31:01.040 the number of LDL particles is a more accurate index of risk than the LDL cholesterol. The VLDL cholesterol
00:31:09.480 is a cholesterol that's in the very low density lipoprotein particles, the particles that come
00:31:15.400 out of the liver. That cholesterol is atherogenic. There's a lot of triglyceride in that particle.
00:31:22.920 So the people who measure triglyceride say, well, the triglycerides are high. That must be the
00:31:28.100 problem. And there's no question that people with high triglycerides are at increased risk of heart
00:31:33.460 disease. But the people with the high triglycerides who are at increased risk of heart disease
00:31:38.420 have a higher number of LDL particles and VLDL particles. It's the particle. And when you're
00:31:45.400 measuring the triglyceride, you're just measuring a blob of liquid in a bunch of particles, and you
00:31:52.080 need to know the number of them. So it's an important number in the sense of if you're a lipoprotein guy
00:32:00.320 trying to figure things out. If it's extremely high, it increases the risk of pancreatitis.
00:32:05.860 But I haven't seen any solid evidence that triglyceride itself is pro-atherogenic. What's
00:32:11.900 atherogenic is the cholesterol inside the VLDL particles. It's the number of those particles
00:32:17.500 that get into the wall. Now there's a complicating reality. Because in general, all I need to know
00:32:24.180 is the ApoB. But there is a disorder called remnant, type 3 dyslipoproteinemia. And that's a very
00:32:32.000 specific, highly atherogenic condition that manifests with high triglycerides, high cholesterol. But get
00:32:42.120 this, you know, low ApoB. So when I measure my lipids and ApoB, I can recognize that. But if you
00:32:49.840 don't measure the ApoB, and this applies to most of the people who are listening to this podcast,
00:32:55.320 if they go to see their doctors, that condition can't be diagnosed.
00:33:00.460 Can you explain that condition? Walk us through what's happening pathophysiologically. How does
00:33:05.680 that person have high cholesterol, low ApoB, high triglyceride?
00:33:12.320 I'll try. The normal metabolism is the VLDL particles get broken down sequentially as the
00:33:21.000 triglyceride is removed. And they get converted to LDL particles. Some of them are removed by the
00:33:26.480 liver along the way. In type 3, that process breaks down. And for reasons that are not well understood,
00:33:36.020 at the age of 30, 35, or 40, people develop high triglycerides and high cholesterol because the
00:33:43.900 VLDL particles aren't being broken down to LDL particles. That process stalls.
00:33:51.000 Those particles circulate a long time in the blood. And while they're circulating,
00:33:57.080 cholesterol gets deposited into them. So they become very cholesterol-rich, like really,
00:34:02.840 really cholesterol-rich. And those people have a very high risk of coronary disease,
00:34:09.760 peripheral vascular disease. It's a commoner syndrome than familial hypercholesterolemia that gets
00:34:15.880 day and night press, day and night. This one is easily treatable almost all the time. FH needs to
00:34:24.320 be treated, much more challenging. But type 3 cannot be diagnosed in most patients in the United States
00:34:33.480 because ApoB is not measured. The technology that we used to use to diagnose it, it's all gone.
00:34:41.200 Nobody uses it anymore. It's old-fashioned. But it can be diagnosed based on the triglycerides,
00:34:48.140 total cholesterol, and ApoB. There's a formula that we devised. So we can recognize those people
00:34:53.280 and say, hey, you may be 38 years old, but you've got a big problem here. And with treatment,
00:35:00.560 we can take your big problem away. And so the phenotype of that patient is that they have
00:35:06.700 relatively few particles, but they have so much cholesterol because the VLDLs are so large and so
00:35:14.300 cholesterol-full. Yeah, that's right. So what is it, given the relative lack of particles,
00:35:20.480 that makes that such a dangerous condition? I'm not sure we know, really. Compared to normal,
00:35:27.340 there are 40 or 50 times as many of these particles. But I'm not sure I understand
00:35:34.520 why it's so dangerous in terms of particle number. I do know that it means you can't just use the ApoB
00:35:43.960 when you're trying to make a diagnosis. When I follow a patient, I really just look at the ApoB
00:35:50.880 for normal patients that I'm treating with statin. I only have to get one number right.
00:35:55.540 It seems that those particles are more atherogenic sort of in the way that an LP little a is more
00:36:00.680 atherogenic. So if you did a thought experiment and you said you take three people who all have
00:36:07.600 the same ApoB concentration, but they could have three very different predicted risks. If one of them
00:36:14.220 has a very, very high LP little a concentration, another one has a normal phenotype and another one
00:36:21.860 has a type three, as we've just described, the first and the third have a much higher risk,
00:36:28.320 suggesting that on a particle per particle basis, they have more atherogenic particles.
00:36:34.080 Or particles that contribute to clinical events. Yeah, I agree. For my practice, I measure a lipid
00:36:41.140 panel. I measure an LP little a in everybody. And I measure ApoB. I measure the LP little a once.
00:36:47.900 When LP little a is high, but ApoB is normal, LP little a may not add that much to risk.
00:36:55.960 But when you got two of them, it's a double whammy. And that I use as another piece of information
00:37:02.740 in trying to frame for the patient the potential futures that they face.
00:37:08.720 And so Alan, what is the treatment for the patients that are type threes, these patients with
00:37:14.300 many cholesterol rich VLDLs, despite a normal ApoB?
00:37:20.620 Statins and or fibrates, they usually respond very well.
00:37:24.600 The fibrates in that patients remind me their triglycerides are normal or elevated?
00:37:29.060 Triglycerides are elevated. They're VLDL particles, so the triglycerides are elevated.
00:37:32.760 We made up a algorithm that's, I think it's the ApoB app, ApoB app, where you can plug in the
00:37:41.920 total cholesterol triglyceride and ApoB, and you get the diagnosis of any of the atherogenic
00:37:47.060 ApoB dyslipoprotenemiasis. Yeah, that was a fantastic app. I can still
00:37:51.540 use it on my desktop, but for some reason, it stopped working on the phone. Am I the only
00:37:56.200 one to have that issue? It stopped working on Google and Apple, but it's on the web.
00:38:00.320 It's directly available from the web. What's the URL?
00:38:03.920 www.apoBapp. .app, right? A-P-P, I think.
00:38:10.120 No, I think it's just ApoB app.
00:38:12.340 Okay. I saved it in my browser because I remember it was a counterintuitive place. I just actually
00:38:16.960 relied on it. I looked something up a month ago on it, so it's a great little, and it walks you
00:38:21.420 through all the diagnostic steps. Part of the argument against ApoB, people say it makes things
00:38:27.880 too complicated. If I explain to a patient that they've got a lot of bad particles, cholesterol
00:38:34.240 particles, they get it. When I review the results of how well somebody's doing on statins, if their
00:38:41.240 triglycerides were high to begin with, they're unlikely to normalize. The HDL cholesterol is unlikely
00:38:47.180 to normalize. Their ApoB is good. They're good. That's my target of therapy because it's the total
00:38:54.580 number of atherogenic particles. And Nordiskard had a lovely paper recently in, was it JAMA cardiology?
00:39:03.560 On a discordance analysis of non-HDL cholesterol and ApoB, showing that ApoB was a more accurate
00:39:11.900 index on statin treatment than non-HDL cholesterol. It's a lovely paper.
00:39:16.960 Yeah. I mean, frankly, I find it much easier to explain to patients what ApoB is than to explain
00:39:23.040 what non-HDL cholesterol is. I do too. I mean, a non-number is hard to explain.
00:39:30.120 And it's interesting to me that with all the emphasis that so many of the lipid guidelines
00:39:36.840 have put on non-HDL cholesterol, they all still say LDL cholesterol. And the American guidelines
00:39:43.100 clearly state ApoB and non-HDL are better than LDL. But the world has remained. It's a phenomenon
00:39:51.200 that I don't really understand. How resistant the lipid world has been to change. But I think
00:39:59.720 it's important to understand because we'll understand things like Afghanistan
00:40:03.500 and the financial crisis in 2008 and a whole series of bad decisions by good people thinking as hard as
00:40:15.040 they could. But when everybody in the room has the same opinion going in, it's a bad way to solve
00:40:22.460 problems.
00:40:23.960 Yeah. I mean, are you optimistic? I mean, is this just a question of time? I mean, in 10 years,
00:40:30.120 will kids in med school be learning about ApoB instead of LDL?
00:40:33.900 Well, I'm pessimistic. Europe, the 2019 guidelines were very pro-ApoB. The evidence from Mendelian
00:40:41.880 randomization, like the newer technologies, Mendelian randomization, they've just been
00:40:46.440 slam dunk for ApoB.
00:40:48.240 Let's explain that to folks because I want to talk about the causality of this. And this might be the
00:40:54.120 perfect way to actually explain the causality of ApoB in the context of this tool. So can you explain
00:41:00.620 to folks what a Mendelian randomization is? People see this all the time in studies, but I don't think
00:41:07.100 it's entirely clear for the average person what it means.
00:41:10.480 I'll try, okay? It's not my expertise, but I'll try. The conventional ways of taking things apart
00:41:18.040 with prospective observational studies like Framingham, there's a limited amount of the
00:41:23.880 certainty of your conclusions because of confounding you can't deal with. You take measurements at age
00:41:30.600 20 and you follow someone for the next 30 years. Well, a lot of things change in the next 30 years
00:41:36.780 that you don't have a handle on. Your inferences are probable, but not causal. What Mendelian
00:41:44.700 randomization allows you to do is to come a lot closer to causality. Because, for example, you can
00:41:54.320 identify groups of genes that are associated where changes in the gene are associated with a little
00:42:00.180 lower cholesterol. And when you lump together a bunch of those different genes that can have
00:42:08.600 different makeups because you can change the makeup of a gene pretty easily, you can see fairly
00:42:15.600 substantial differences in cholesterol. So what you've got is information on somebody that's fixed
00:42:22.780 at birth. And you see, is that associated with a difference in outcome? You've gotten rid of a lot of
00:42:30.880 stuff in the middle. And what a number of Mendelian randomizations have shown is that APOB includes all
00:42:40.000 the information in triglycerides, LDL cholesterol, and even HDL cholesterol. It sums them, which in the sense
00:42:46.780 of VLDL and LDL makes perfect sense. So there are caveats in Mendelian randomization. You can't just
00:42:55.300 push a button and say, give me the answer. But George Davies Smith, really arguably one of the founders of
00:43:02.760 Mendelian randomization, or not arguably, he was. He's the author of a number of the Mendelian randomizations
00:43:10.200 saying APOB incorporates and therefore beats triglycerides and LDL cholesterol. So that's a
00:43:18.880 huge level of information that isn't even mentioned in almost any of the guidelines.
00:43:28.100 Yeah. So let's make sure people understand everything you just said, because you said a lot
00:43:31.420 of things in there. When you prospectively follow a cohort the way the Framingham cohort was followed,
00:43:38.320 or the Framingham offspring, or the MESA cohort, or any of these cohorts have been followed,
00:43:43.240 you can take a bunch of people and you could measure their APOB or their LDL-C or whatever
00:43:48.340 metric it is that you're trying to determine if it in fact has a causal relationship to the disease
00:43:53.200 of interest. You can follow them over decades and you would demonstrate, as has been demonstrated,
00:43:59.300 that the people with higher B, higher LDL-C, higher non-HDL-C, and lower HDL-C,
00:44:07.480 all have a higher risk of developing atherosclerosis over time. But it's hard to say that that's causal
00:44:14.240 just based on that information, because over the ensuing 20 years that you follow them,
00:44:20.360 they are free to make other choices that may impact those variables of interest and other variables.
00:44:27.520 So the Mendelian randomization attempts to get around that by saying, at the time of,
00:44:34.020 I was going to say birth, but really at the time of conception, we all get randomized to a set of
00:44:40.380 genes. We get assigned a set of genes. I guess they're not perfectly random because they come
00:44:45.360 from our parents, but for the purpose of not changing, they are indeed a random assignment
00:44:50.980 that is fixed. If we can identify which genes map to which phenotype, and we can figure out
00:45:00.780 the genes that map to the phenotype of our interest, namely driving up or down a variable
00:45:07.240 of interest such as APOB, then we don't really have to worry about the confounders that occur
00:45:13.020 in between because the genes can't change. Just to put a bow on that, basically now when you see a
00:45:21.340 difference in outcome, it's much more likely to be causally related to the phenotype of interest,
00:45:28.620 because the gene has not changed that underlies it. Now, what are some of the ways that we can get
00:45:33.980 tripped up with Mendelian randomization? I mean, there's some pretty big ones.
00:45:38.020 Yeah. Before we get there, HDL cholesterol was the rage, okay? The total rage because the
00:45:46.660 epidemiological evidence couldn't be clearer. In fact, it was four times more clear. My recollection
00:45:53.020 was that Framingham demonstrated low HDLC was four times more predictive of cardiac events than high
00:46:01.940 LDL-C. Am I remembering that correctly? I'm not sure it's that multiple. Yeah, but it's multiples.
00:46:07.060 And it turns out, as we know now, at least from the CTP inhibitors, that you can't manipulate HDL
00:46:14.460 and change outcomes. And that's one of the elements of demonstrating an overall causal relationship.
00:46:21.000 And the Mendelian randomization show HDL is not causal, whereas they show ApoB is. And cholesterol
00:46:28.300 is too, by the way. Those are two very important studies, Alan. I mean, and both of those have been
00:46:33.840 in the last 10 years. Yeah. It's an incredibly technical advance in being able to examine questions
00:46:44.260 and look at numbers of people that would be unimaginable in conventional studies.
00:46:51.720 The Mendelian randomization, they're always talking hundreds of thousands of people because
00:46:55.100 they've got these huge data banks with genes. And those numbers get you around the confounding
00:47:01.040 of things. You have huge numbers. But it's like any methodology. No method is perfect.
00:47:08.940 This one can mislead you too, particularly when you've got a sequence of associated variables.
00:47:16.120 For example, people show using MR that triglycerides were, quote, causal or associated with increased
00:47:23.700 risk. But when you took into account the non-HDL cholesterol or the ApoB, it disappears. So when
00:47:30.240 you've got a linked metabolic chain, you've got to be careful that you've gone to the end of it.
00:47:36.180 You've got the real actor, not act one leading to, that you've got the real persona dramatis.
00:47:43.060 Which is why it's surprising that HDL didn't, at least at the first order, demonstrate causality.
00:47:50.160 Because there's no doubt that phenotypically, the high triglyceride, low HDL phenotype is so
00:47:58.640 associated with metabolic syndrome that it makes up two of the five criteria.
00:48:02.880 That's an incomplete description. That's like you describing yourself as six feet tall,
00:48:12.760 I wish, and not giving your weight and letting me guess your BMI. You cannot characterize any
00:48:19.860 phenotype without the ApoB. It really drives me around the bend. When people speak saying,
00:48:28.040 I got somebody because I got their triglycerides and their HDL. Well, I say, okay, what's their
00:48:32.700 ApoB? How can you pretend you've evaluated the system when you haven't counted the number
00:48:39.420 of atherogenic particles? Because they could be normal, they could be high, or you can have a type
00:48:45.600 three. They don't know. And it's not a phenotype. There is no phenotype without putting an ApoB in
00:48:54.860 there. They're lipoprotein particles. They're disorders of lipoprotein particle metabolism.
00:49:04.240 Of course, the triglycerides and cholesterol are important. But my analogy, I didn't do a good
00:49:09.220 analogy there. But it's so fundamental that it drives me to distraction as to why you wouldn't
00:49:20.020 want to know a core element of knowledge. But it doesn't seem to bother many of my friends.
00:49:27.440 You walked through the pathophysiology of how the ApoB bearing particle wreaks havoc in the artery
00:49:33.400 wall many, many years before we see clinical events. And you also mentioned that there are other
00:49:39.180 factors that can amplify or exacerbate that. I can't remember exactly how you said it, but that was
00:49:43.800 the gist of it. Well, two of those things that are widely accepted to exacerbate risk are smoking
00:49:51.600 and hypertension. In fact, smoking and hypertension probably carry a greater risk for atherosclerosis
00:49:59.160 than ApoB, or is that not the case? It all depends the way you think about it. Because if you just say,
00:50:06.260 what's the risk somebody with hypertension faces? They have high risk, no question. But then you say,
00:50:11.240 what is hypertension? The last 30 or 40 years, there have been almost an infinite number of basic
00:50:19.540 science studies on hypertension. And when you were in medical school, and even before that,
00:50:24.820 when I was in medical school, we talked about pathophysiology of hypertension. And what strikes
00:50:30.800 me is we don't talk about the pathophysiology of hypertension anymore. But the basic science goes on
00:50:39.520 in rats is healthier than ever. And there isn't anything I know of that's come out of that basic
00:50:45.980 science that's been clinically useful in the last 30 years. The drugs we use, we use them because they
00:50:52.700 work. So what is hypertension? It's a higher blood pressure than we should have. And where is the
00:51:01.300 disease that produces that higher blood pressure? Is it resistance? We don't have a clue, okay? We don't
00:51:08.260 have a clue. And it strikes me it's the same thing as much of the debate in lipids about ApoB or the
00:51:14.940 drunk looking for the key under the light because this is where the light is, not where he lost it.
00:51:20.240 Everybody who's anybody has the same viewpoint. My bet is it's in the proximal aorta. My bet is that
00:51:27.580 it isn't that complicated. We lose elastance in the proximal aorta. And that's systolic hypertension.
00:51:33.720 Thank you very much. What could accelerate that process? What's the mainstream view that this is
00:51:40.120 renal? When I read hypertension, I get lost because I get page after page after page of peripheral
00:51:47.380 arteriolar tone and very complex metabolic studies and very sophisticated animal models. There's some
00:51:56.600 renal left. It's a miasma for me, an absolute miasma. I hadn't heard about the proximal aorta,
00:52:03.520 so say a bit more about that. Well, this is me. The proximal aorta is elastic. And if you look at a
00:52:10.040 flow curve, a hydrostatic pressure curve, when we're young, it's rounded because as the left
00:52:16.640 ventricle ejects blood rapidly into the aorta, the aorta expands. So it absorbs some of that energy.
00:52:24.640 You know that wind kessel that they mentioned in school? That's not that big a deal, but the energy
00:52:29.720 is partially captured, partially regained. But the wall isn't battered. The wall can give way.
00:52:39.960 Me, personally, just in the middle of my brain, imagine that if those elastic fibers start to go,
00:52:48.160 then the wall's stiff. So now when the left ventricle ejects blood, the pressure goes up more rapidly,
00:52:54.140 and it falls more rapidly in diastole. And that's why you get systolic hypertension with normal
00:53:00.560 diastolic pressures. So my bet would be, if I was not the age I am, I would be looking at factors like
00:53:07.980 cardiac output again, which used to be way back when, or factors that alter the behavior of the
00:53:13.500 proximal aorta. As much as something that's, to me, pathophysiologically, much more likely to be
00:53:22.200 involved. So once I got hypertension, okay, then I've got a driving force to push particles into
00:53:28.860 the wall. And so you think it's the actual increase in the pressure of the plasma?
00:53:35.280 And the response of the wall. I think there are responses to the wall. The wall thickens up. It
00:53:39.840 gets harder for particles to go through. Does it also damage the endothelium? Do you think that plays
00:53:44.600 a role? That's right. I don't understand endothelial dysfunction. It's more a language thing to me than it
00:53:50.680 is a reality. I know the endothelium is critically important. It functions abnormally, and that's
00:53:56.140 endothelial dysfunction. How that fits into the overall thing, I don't know. My bet is ApoB particles
00:54:03.640 are part of the process of inducing endothelial dysfunction, but I don't know that clearly
00:54:08.880 experimentally. So going back then to the question at the top, does it make sense to even compare
00:54:17.320 hypertension to ApoB? They both seem to play a causal role. Is one more causal than the other, or is that
00:54:24.180 a silly question because they're not binary and static? I think that's not the right question. I think
00:54:30.520 our blood pressure goes up as we age. I mean, hypertension involves so much of the population
00:54:36.780 that it's not clear to me what the word disease means. The prevalence as we age is so high
00:54:43.460 that to me, it's becoming almost a aging process because we're lasting a lot longer than we were
00:54:50.320 probably designed to go. So you have this repetitive injury to the proximal aorta. It gets a
00:54:57.000 little progressively less able to deal with it. So with a time where 50, what percent? 60% have higher
00:55:03.400 blood pressure. I mean, the figures are staggering. Is it really that high? I'm not sure. Don't quote me
00:55:09.280 on that, but it's high, high, high. But doesn't ApoB also rise with age? It does rise with age,
00:55:15.860 but not that much. When we look at people at age 35, we can pretty accurately categorize the group
00:55:24.560 they belong to at age 35. Not that they won't change somewhat. So if you're high at age 35,
00:55:31.000 you've got about a 95% chance of staying high. 5% will go out of the high zone. They won't go low,
00:55:38.420 low. So if you're high at age 35, I wouldn't bet anything's going to move you down. That's why I
00:55:46.860 think it's such a good signal for when we should start thinking about treating people. And if you're
00:55:52.340 low, some people go from low towards high, but the majority don't. And we keep following them.
00:55:59.060 But if you're high, no, we've published a fair amount of this. If you're high, it's not a hundred
00:56:06.260 percent, but it's about 90% that you're going to be high. Is there a gender difference? At least
00:56:11.820 clinically, I seem to see women as they go through menopause experience dyslipidemia that men wouldn't
00:56:18.480 experience over that same decade or even five-year transition. I think there are changes and ApoB goes
00:56:24.300 up with menopause. I'd like there to be more data. I think part of the reason it's held ApoB back is
00:56:30.240 that people didn't measure it. So they were sort of, well, what I measured has to be important because
00:56:35.680 I can't answer your question. Hopefully more data will be coming. But I agree with you. People can
00:56:41.500 change at the menopause. So I'm not saying we don't keep looking at people. But when you have somebody
00:56:46.480 at age 35 to 40 who's high, the odds are high that they're going to stay high.
00:56:52.540 Are we doing a better job treating hypertension than dyslipidemia?
00:56:56.080 I have no idea. The incidence of coronary disease is going up in the last five years. And that's
00:57:03.120 despite statin therapy. And that's the obesity diabetes. So I think we've been too quick to
00:57:11.440 congratulate ourselves at how well we're doing. There are many reasons that treatment is not
00:57:17.640 succeeding as well as it should. And I think the complexity of the lipid phenotype of the lipid
00:57:23.780 model is part of the answer. It's easy for me. I get the ApoB where I want it to go.
00:57:30.360 Yeah. I mean, an explanation for your observation would be if in the last five to 10 years,
00:57:35.000 the incidence of atherosclerosis or major adverse cardiac events is rising despite the advances we
00:57:41.700 have, you would argue or could argue that if we're measuring LDL-C and that's our proxy for treatment,
00:57:49.320 but as dyslipidemia is growing in the metabolic context, meaning if you have more medicine and
00:57:55.900 more insulin resistance and more type two diabetes, we know that those phenotypes are associated with
00:58:00.540 greater discordance between ApoB and LDL-C, suggesting that you'd have a greater and greater
00:58:05.860 portion of the population that is being undiagnosed or being underdiagnosed because you're treating their
00:58:12.400 LDL-C and you believe that it's lower than their risk actually is because their ApoB is higher. I
00:58:18.460 know you know what I just said. I hope the listener understands what I just said.
00:58:22.340 Yeah. What you just said was important. It's another example, an unfortunate, sad example,
00:58:29.380 that trying to quantify lipoproteins based just on lipids is not adequate. You're not capturing all
00:58:36.880 the information that you should. So let's talk about smoking for a second. Do you have a sense,
00:58:42.480 I know it's again, not the thing that you study day and night, but what is it about smoking that
00:58:47.680 drives risk of atherosclerosis so much? Truth is, I don't know. It certainly does. And it drives
00:58:55.040 the treatment decision. I think smokers are wonderful human beings who deserve to be treated as human
00:59:00.120 beings. But I don't think that if you choose to continue smoking, that should prioritize you for
00:59:06.020 statin treatment. Whereas based on my concern about people who have high ApoB levels, they should be
00:59:13.240 treated because of their longer term risk. Smoking gets you up the category to have your life saved.
00:59:19.100 So bad behavior gets you closer to having your life saved. Is that a Canadian thing?
00:59:25.480 No, it's an American thing. It's in your risk calculator. If you're a smoker, your risk goes up.
00:59:29.820 Oh, I see what you're saying. Not based on a coverage issue, but simply based on a change in
00:59:35.720 prioritization. That's right. Because everything is risk, bad behavior increases risk. So you get
00:59:42.480 more medical attention. Now, I think bad behavior is our responsibility to help people deal with.
00:59:48.780 But I don't think it should put you to the head of the line for preventive therapy.
00:59:53.780 I mean, I would argue there is no line. Anybody who wants preventative therapy should be getting it.
00:59:59.140 Are we resource limited on that front?
01:00:01.140 We're not giving patients the information that they deserve. We published a paper in circulation.
01:00:07.120 I think it's 2019, which I referred to before, looking at what are the costs of delay of intervention
01:00:13.960 starting at age 35, 45, and 55. And if your non-HDL is low, yes, you'll get some gains starting at 35,
01:00:24.220 but it's not a lot. It's actually quite small. Your gain is in the people with the high non-HDL.
01:00:31.900 We don't have to be giving pills to everybody at the age of 35. If we use our physiological and
01:00:40.340 epidemiological knowledge, there's about 20% of the population is at evident high risk, and they should
01:00:49.080 consider it. And part of the information they need to know is, how much do I gain now? How much is
01:00:55.280 gained now? Versus how much is lost by weighting? And that's why these methodologies of calculating
01:01:01.980 benefit are so important. Do you have a sense, Alan, of what fraction of the population has relatively
01:01:09.520 normal ApoB, relatively normal triglycerides, and yet has accelerated atherosclerosis through
01:01:17.900 some combination of yet-to-be-identified polygenic risk factors. So you see atherosclerosis that runs
01:01:25.820 in families, and there's not an obvious cause, right? They don't have FH, they don't have LP little
01:01:32.580 a, and frankly, their ApoB is harboring around the 50th percentile of the population, but they
01:01:38.100 disproportionately get afflicted young. So they're all having first events before 60.
01:01:44.180 I don't know. I think that's where research needs to be done. And I would look at factors
01:01:48.760 that affect the trapping of the ApoB particle within the arterial wall. I think Kevin, John
01:01:53.280 Williams from Philadelphia, they've done an amazing job, amazing job in putting this all together.
01:01:59.760 And wouldn't that factor into our decision-making then? I mean, would we, if we had two people who
01:02:04.960 were both, say, 40, let's just say they were identical in terms of lipids and lipoproteins,
01:02:09.860 they both had the same blood pressure, they were both not smokers, et cetera, but one had that family
01:02:14.580 history, the other did not. Are you treating them different? It would factor into my decision.
01:02:21.140 If the ApoB is actually low, I'd be less inclined to let it influence me.
01:02:27.240 Let's say they're both at the 50th percentile.
01:02:29.740 If they're 50th, 60th percentile, that makes me more antsy. The higher they are, the more antsy
01:02:35.600 I get. A lot of these decisions at the individual level actually aren't that difficult when you're
01:02:41.560 speaking to a particular patient because they have their own objectives and goals. If we give
01:02:47.300 people medications, our medications have risks associated with them. I don't think we fully
01:02:52.060 understand the relationship of statins and diabetes. I don't think we do. So statin therapy
01:02:58.560 is amazing, but it's not a no cost. But when you talk to an individual human being, at least at this
01:03:09.400 stage of my career, it's been easier to make clinical decisions individually than to write
01:03:14.420 rules for groups. Yeah, there's no question about that. Let's now look at yet another predictive
01:03:21.280 tool, which is the coronary artery calcium score. So maybe tell folks what a CAC is. I suspect a number
01:03:29.620 of people listening to this will have had it, but enough will not have. So it's worth explaining
01:03:33.820 what the test is. Coronary calcium is an important step forward in cardiovascular imaging. And it's a
01:03:43.500 process where you can accurately and pretty safely determine using x-ray techniques, whether there's
01:03:53.040 calcium, bone, in the coronary arteries. And calcification is a feature of advanced atherosclerosis.
01:04:04.340 There's very strong evidence that people who have coronary calcification are at higher risk
01:04:13.500 of a heart attack or stroke than people who do not have coronary calcification. That's an important
01:04:21.460 piece of information. But there's several facts you also have to appreciate. First, the frequency of a
01:04:30.200 positive coronary calcium goes up as we age. So does the risk of disease. So by the time a man is 60,
01:04:38.160 all American men are at high risk, according to your current guidelines. Women are five to 10 years
01:04:46.200 later. So at the point where the test is most commonly positive, I don't even need it. Because
01:04:54.800 that person, we were talking a while back about the natural history and stare and stuff, that stuff is
01:05:02.400 for real. Our arteries in the majority of us have become substantially transformed in bad ways by the
01:05:11.280 time we're 60. Now, in people who are younger than 60, can this give you extra information if you're on
01:05:18.640 the cusp of saying, should you be treated or not? And I think the answer is yes. If you or the patient
01:05:27.060 says, I want more information, I'm not convinced, I personally are in a situation where I should be
01:05:35.480 taking medications, and you have a positive coronary calcium, I think that can be extremely helpful.
01:05:41.760 It's what's taken as the corollary, that if your coronary calcium is negative, you're okay. That's the
01:05:49.640 problem. For me, from my knowledge and interpretation of literature, and the pathological studies,
01:05:58.020 coronary calcification is an advanced disease. It means advanced disease is present. When people have
01:06:05.000 a heart attack, they don't just have one little area of their arteries that are abnormal. That's the
01:06:09.880 area where the plaque broke, where the endothelium eroded. But the artery is diseased, and there's a
01:06:17.780 chance of an event a sonometer down or a sonometer closer. So if somebody has a high ApoB, the fact
01:06:26.460 that their coronary calcium is negative doesn't mean they don't have a lot of disease, and that the
01:06:33.720 disease isn't developing at a rapid rate, it could well be there. So there's an argument saying, well,
01:06:40.520 if your coronary calcium is negative, nothing's going to happen to you in the next five or 10 years, and
01:06:44.960 maybe, but the disease is going to develop, and we can't make the disease go away. We can modify the
01:06:52.820 effects of the disease, modify the consequences. But when we talk about, I mean, LDL cholesterol and
01:06:59.160 ApoB levels are now so low, but you still have an artery that's destroyed. You're going to have
01:07:04.240 a substantial number of events. John Wilkins and Don Lloyd-Jones from Northwestern have a paper in
01:07:11.720 Jaha, and it's a terrible paper to read because it's so complicated, and I wish they hadn't presented
01:07:17.420 it in as complex a form as they did. They're friends of mine, so I can criticize them. But within it are
01:07:24.240 the observations that starting to treat waiting for a coronary calcium is a bad idea. So I'm a
01:07:32.620 conservative physician. It may not be my politics, but I want to protect patients, give them the option,
01:07:41.100 because it's the patient's choice. Of course it is. Give them the option to have the best outcome
01:07:45.940 possible when they appear to be in danger. So I wouldn't use a negative coronary calcium
01:07:51.660 to change my clinical decision when I have a high ApoB or another cause of vascular disease present.
01:08:00.760 So I think it's a good test, but relatively limited utility for me.
01:08:06.160 The way I've talked about it, maybe even on the podcast, but certainly the way I talk about it
01:08:10.680 with patients every day, it would seem, is I describe it as a two-by-two matrix. So we think
01:08:17.540 about how this test is helpful in people who are young and people who are old. Now, I usually use
01:08:22.580 50 as the cutoff. It sounds like you use 60 as the over-under, but let's just say it's somewhere in
01:08:28.420 that sixth decade. And then is it zero or is it non-zero? I agree with what I'm hearing is your
01:08:35.700 assessment, which is in the older patient, the positive score is not very informative. So when I
01:08:43.800 have a 70-year-old patient whose calcium score is 50, it's sort of like, so what? You're normal.
01:08:50.620 That doesn't tell me much. Conversely, when I have an older patient whose score is zero and they're
01:09:01.600 adamant about not getting treatment, it becomes an easier decision to accept because you can say,
01:09:08.040 well, gosh, you're pretty fortunate to be 73 years old. And despite having an ApoB of 140 milligrams
01:09:16.360 per deciliter, your calcium score is zero, there must be some other protective mechanisms in you.
01:09:22.400 The bounds of our knowledge are really quite limited. And it's important that we admit that
01:09:27.600 to ourselves and to our patients as well. I look at it maybe a bit differently. I say,
01:09:33.640 yes, I would say the same thing. And I would say, yeah, but even so.
01:09:38.940 To me, there's an asymmetry, which I want to come to in a moment. On the flip side of things,
01:09:43.160 the young patient who has a positive calcium score, really, that's a four-alarm fire.
01:09:50.100 That's a no-brainer.
01:09:51.240 Regardless of the ApoB. If you're under 50 and you have a speck of calcium in your coronary arteries,
01:09:57.340 even if it's a low enough speck that it would predict a 10-year risk of 4%, that's still utterly
01:10:04.820 unacceptable. If it's positive, it's positive. It's only going to go up.
01:10:09.920 And more to your point, it's what it says about the milieu of the entire system. So that might be
01:10:19.020 the one area in the middle of your left anterior descending artery where you're at such an advanced
01:10:25.720 stage that you've already laid calcium there. It's sort of like looking at the concrete that's
01:10:30.740 been poured over Chernobyl and trying to infer what's going on in the 10 miles around Chernobyl.
01:10:36.940 It's all bad. Yeah, that's correct. Where I find the most challenge, there's the group think that
01:10:43.980 says, if a person's calcium score is zero, no treatment is needed. And this kind of gets back
01:10:50.780 to your paper from JAMA, I think 2018, maybe 2017, looking at the 30-year risk, the causal model,
01:10:58.540 which I want to come back to. You mentioned it very briefly at the outset, but it's so important
01:11:01.620 that I want to now use this as a jumping point to go there, which is you take that 45-year-old person
01:11:08.640 who you expect their calcium score to be zero. It is zero, but their APOB is higher than it should
01:11:15.800 be or you would like it to be. That calcium score of zero hasn't really added much information to my
01:11:20.340 decision-making. No, because your time horizon is different. We use 20, 30 years. If you're 45,
01:11:27.740 you want to get to further than 55. Your career, your children, your enjoyment of things,
01:11:35.400 surely you're not just planning to age 55. And you should be thinking, well, what am I going to be
01:11:41.340 like at 65 or 75? That's reasonable. And it's also by taking it out to that, you can get to numbers that
01:11:48.840 are really meaningful. When somebody's at a 30% chance, like one in three, that's a number most people
01:11:55.920 can understand. And it starts to become a truly a meaningful number for an individual. When
01:12:02.980 somebody's at 7.8% risk, that's tough to absorb in any way that means something. When you're in one of
01:12:11.820 these higher risk groups, it doesn't mean you're doomed, but you're in company with a lot of folks
01:12:19.340 who are. And we can say that absolutely accurately. Yes, it's limited. It may not be you. Make your
01:12:27.000 bet. I might even be more risk afraid. You're saying that if a person's 10-year risk is 5%,
01:12:35.860 how can you get somebody excited about a 5% event in the next decade? If somebody's 50,
01:12:43.640 so somebody's 50 and you say you've got a 5% event risk by 60, and you're saying, well, the two things
01:12:50.240 that are wrong with that are, one, you shouldn't just be thinking about being 60. You should be
01:12:55.000 thinking about being 80, which I completely agree with. We expect you to live a minimum of 30 more
01:12:59.900 years, if not more. And secondly, you're saying, well, 5% is not that much to get excited about.
01:13:04.620 Well, let me turn the table. I want you to pretend you're 50, Alan. And I say to you, Alan,
01:13:10.120 there is a 5% chance that in the next decade you will die on a commercial plane. How would you
01:13:16.900 change your behavior as a result of that? I don't think I would. You wouldn't stop flying?
01:13:22.060 No, because there's a 95% chance I won't. Okay. I think 5% is a bigger risk than people
01:13:29.060 realize. I get it. It's bigger than one in a thousand. Okay. Well, not only that, in the case
01:13:35.820 that I just gave you, the treatment would be don't fly for 10 years, which is a real impediment
01:13:42.320 to your lifestyle versus the treatment to lower lipids, which is far less of a burden and the
01:13:53.280 risks of it can be combated. Let me come back to you. What are the confidence intervals on that
01:13:59.180 number of 5%? Well, that's a good question. Let's say I can tell you it's plus or minus 2%.
01:14:05.680 How do you tell me that? Where's that number? Have you ever seen that number?
01:14:10.360 At the population level. Let's pretend I'm able to tell you that at the population level.
01:14:14.560 You've never seen it. I've never seen it.
01:14:17.400 Well, we can't do it at the individual level, of course.
01:14:19.820 No, no, no, no, no. I'm saying, what are the confidence intervals for that prediction?
01:14:23.780 Have you ever seen them published? And the answer is, nope. I'm not sure how much of your audience
01:14:29.840 does confidence intervals and this kind of thing. But as scientists, for any result, we get the result
01:14:38.400 and we get the range of possible results. Then we know how accurate the prediction is.
01:14:45.540 If the confidence, let's say it's 5% and the confidence interval is 4.5 to 5.5, well,
01:14:52.220 you're there. If the confidence interval is 0 to 70, which it could be, by the way, maybe it isn't.
01:15:03.440 So I'm saying we got an industry that captured clinical care that doesn't include error.
01:15:12.580 Well, why is that? That seems, now that you mention it, almost impossible to believe.
01:15:16.640 Please reassure your audience, I'm telling the truth. Because we've become less critical. This
01:15:25.440 process of forming opinion in medical care that's appeared over the last 30 or 40 years
01:15:32.000 has damped down the essential element of science, which is challenge, different viewpoints,
01:15:42.460 the contention of ideas, the creation of an experiment to say, this is the right way, or
01:15:49.000 someone with a different view creates a different experiment. Science is a democratic activity where
01:15:55.820 legitimate, contending legitimate views have equal, differing views that are legitimate have a chance
01:16:04.300 to contend. I'm not saying every crazy theory has equal, it doesn't.
01:16:09.320 So that's exactly what I was going to come back and ask you, Alan, is who is the arbitrator of what's
01:16:14.740 a legitimate, differing hypothesis? In science, it's called the experiment. That's what's different
01:16:21.240 about science. An experiment is done to test a hypothesis. If the hypothesis is sustained,
01:16:28.120 you can continue to hold the hypothesis. If the hypothesis falls, then you must reframe your
01:16:35.040 understanding. And we do experiments to gain understanding. It's our tool. But it's not as
01:16:43.680 easy as it sounds. Our experiments are, the methods could become complicated. The methods we use to
01:16:52.000 analyze them statistically can become complicated, are complicated. And the conclusions we draw from them
01:16:58.440 may or may not be correct. Error occurs. When I was a medical student, the major medical meeting of the
01:17:07.460 year was in Atlantic City, and the big professors would contend the elephants. And there were different
01:17:13.460 views, and they would argue them out. And it was a contentious, open battle. Evidence-based medicine
01:17:20.720 came along, which has lots of pluses, in which it says we should use randomized clinical trials as part
01:17:27.980 of our knowledge base. But we developed the belief that it was easy to assess knowledge. And it's not.
01:17:37.320 It's not easy to assess experiments all the time. Some of them are straightforward. Most of them actually
01:17:44.000 aren't. Most of them, there's uncertainty involved. And it's important that we acknowledge the
01:17:50.300 uncertainty and say, well, maybe there's another way of looking at this that's even better. But we
01:17:56.220 developed tools like statins. There's very good evidence can save lives. So this process of consensus
01:18:04.360 came along saying, this is too complicated for regular doctors. And it is. They don't have the time to
01:18:11.940 analyze all the evidence. So we'll analyze the evidence for them and write it out in a way that tells them
01:18:19.680 what's the best we can do now. And there's a lot of good in that. But there's potential
01:18:25.520 weakness. And I think a lot of the weakness is happening. Because you get a view that becomes
01:18:35.380 the conventional view, and it hangs on longer than it should. Science is about change. If we're still
01:18:42.540 saying the same things we said 30 years ago, it could be a problem. Because we should have learned
01:18:48.160 how to say it better, more accurately. In these consensus conferences, I don't know if your
01:18:53.560 listeners appreciate, the recommendations are unanimous. The Supreme Court isn't unanimous often.
01:19:00.340 There's a majority view. The minority says this, that, and the other thing. And it can turn out that
01:19:05.460 the minority, over time, we see the wisdom in the minority. Any process that has unanimous
01:19:11.800 recommendations has a weakness. Any process where the decisions become larger than the individuals who
01:19:20.900 propose them has a weakness. Like the recommendations are the American College of Cardiology, American
01:19:26.800 Heart Association, blah, blah, and about 30 other groups. There are actually 100 people. They're good
01:19:32.940 people. But there's only whatever number it is, 100 of them. But by cloaking it in the anonymity of the
01:19:41.300 group, they become impervious to criticism, even when there's obvious inadequacies. And that's not
01:19:50.220 science. If you write a paper, I could do an experiment and try and overturn your paper, or confirm it. But
01:19:59.320 when you have the guidelines, they're the judgment that's cast in stone to the next group of guidelines.
01:20:06.400 Depending on which people write them, it can influence what you see.
01:20:13.560 I completely agree with that. I would add even more complexity to it, which is,
01:20:18.420 if you go through what the critical steps are in the elucidation of knowledge, the first presumably
01:20:24.140 would be the formation of a hypothesis. The second might be designing an experiment to test that
01:20:30.160 hypothesis, then conducting that experiment, analyzing the results of that experiment,
01:20:36.560 then interpreting it. Again, I'm oversimplifying a little bit, but these are quite discrete steps.
01:20:41.080 And as you pointed out, any one of these steps offers infinite ways to do it wrong and a relatively
01:20:46.780 few ways to do it right. I'll give you an example that's near and dear to both of our hearts.
01:20:51.420 So just yesterday, I was having an email debate with a friend. I forget what spawned it. Oh,
01:20:58.060 he had sent me an article about something lipid related. And it somehow led to a discussion about
01:21:04.520 the Fourier trial, which for listeners is the trial that looked at one of the two PCSK9 inhibitors.
01:21:11.280 This was Repatha. And it demonstrated that on patients who were on a very high level of statins
01:21:17.960 and had a very low LDLC, I think their average LDLC was in the neighborhood of 70 milligrams per
01:21:23.560 deciliter. Over a five-year period, they had a reduction in cardiac revascularization, but no
01:21:29.580 change in mortality. His point was, how can these drugs be tolerated? How is it that we live in a
01:21:37.580 society where insurance companies are paying for these drugs or people are using these drugs and
01:21:41.760 doctors are prescribing these drugs where they didn't even demonstrate a reduction in mortality?
01:21:47.260 All they demonstrated was a reduction in revascularization. I can't remember if there
01:21:51.880 was a reduction in events because I sometimes confuse Odyssey and Fourier. To which I said,
01:21:57.040 well, it's really interesting because the time course of that study was so short in a group of
01:22:02.140 patients who were already so heavily statinized that it's my interpretation of that study when it
01:22:07.440 came out, which is probably six years ago, it's actually a miracle it showed anything at all.
01:22:11.760 Because if these patients are walking around with an LDLC that's at the fifth percentile of the
01:22:16.740 population, and then you give them another agent that lowers LDLC to the first percentile of the
01:22:23.340 population, and we're talking about a disease that takes at least four decades to take hold,
01:22:29.260 and you study them for just five years, would you really expect to see an event difference?
01:22:35.680 Which, by the way, you did see in Odyssey, probably because using a very similar drug,
01:22:41.780 those patients were started out at a higher level of LDLC, so you saw potentially a greater
01:22:47.120 risk reduction. So here you could have two relatively smart people looking at the same
01:22:52.220 presumably well-done experiment with the same reasonably legitimate statistics,
01:22:57.340 but we have a different lens for what the disease is and therefore draw a completely different
01:23:02.560 conclusion. Is your point that no consensus can ever basically resolve that? And the way that
01:23:09.260 medicine has to progress is that each of us needs to progress on the basis of our own understanding,
01:23:14.860 or how would you referee the debate between my friend and I? We can only understand as individuals.
01:23:21.520 There is no such thing as a group understanding. We can't get beyond ourselves. Really, it's not
01:23:27.720 possible. And when you talk about thinking, I can't think about every issue that's out there that's
01:23:35.380 important, either in medicine or my car or my woodworking. I have to delegate a lot. I'm writing
01:23:47.100 a paper now about familial hypercholesterolemia. And there's a study that's the core study for
01:23:54.880 demonstrating that patients with familial hypercholesterolemia and whom you can demonstrate
01:23:59.960 genetic abnormality are at much, much, much, much higher risk than people with similar
01:24:06.340 LDL cholesterols, but without the genetic abnormality. Now, that study has been accepted by everybody
01:24:12.520 as being well-done and decisive. And I mean, by everybody, everybody.
01:24:19.400 Just to make sure I understand what you said, you can have two patients who are phenotypically
01:24:24.020 identical, but the one who has the genetic abnormality of FH, which is simply a phenotypic
01:24:32.080 disease, by the way. It's not a genetic. The disease is defined by the phenotype. You're
01:24:36.720 saying they carry a residual risk that's not present in the wild type.
01:24:41.460 That's correct. Three to five times that risk. 300%.
01:24:45.420 That's unbelievable.
01:24:47.240 I thought so too. I read the study and I read it again and I re-read it. I couldn't understand
01:24:53.360 it. And then it dawned on me after a lot of re-readings, I think they made a mistake in
01:24:59.800 their methodology. I think they made a grade school error. Now, maybe I'm wrong because
01:25:05.300 I'm writing this up. I'll subject it to review and criticism. And I'm given that I'm saying
01:25:12.820 every authority in the field is wrong. Chances of coming out on positive and this are pretty
01:25:17.400 slim. But the error in the methodology that I think is present is so simple, it's decisive.
01:25:25.940 Just putting, maybe I'm wrong, but my bet is I'm actually right, is that thinking is damn
01:25:33.800 difficult. And we have to continue to think and discuss with ourselves. HDL cholesterol, everybody
01:25:41.020 believed it till they didn't. I mean, how many dissenters were there until everybody said it was
01:25:46.400 obvious there was nothing there. And we're human beings. We search for validation. But science isn't
01:25:55.960 about that, real science. And it turns out that the world is a very slippery thing to get your
01:26:05.120 mind around. I gave the example at the beginning of this talk about risk. If I asked you what risk was,
01:26:11.880 I wouldn't do that to you because you're the boss of this podcast. But risk is the number of events
01:26:19.540 per standard number of people over a defined period of time. We leave out the standard number of people.
01:26:32.180 When we say your risk is 5%, we say, well, that's 1 in 20. Well, it's per standard group of people.
01:26:41.360 That's why I said risk is low if you're under 60. The number of events per 100 people is low,
01:26:48.860 but the number of 100 people is a lot larger than over 60. That's why the absolute number of events
01:26:56.460 is so high. So a difference of words, tremendous difference in action, because it means I don't
01:27:04.120 use the 10-year risk model. Okay? And even though that has been published, and even though that has
01:27:12.840 been reproduced by other investigators, that has not changed the guidelines. And that's wrong.
01:27:22.680 When I look at the guidelines, and I have enormous respect for people who serve on them,
01:27:28.120 I can look at the literature on an issue. I can tell you who wrote the guideline.
01:27:31.480 There was a recent guideline from Europe that was negative about ApoB. One paper cited,
01:27:39.400 one paper, and that became the guideline. So I'm not talking about throwing out the process.
01:27:45.940 The process of reviewing knowledge in a group is positive. I'm saying that we better watch out
01:27:52.580 for the process. We need to do much more to ensure that the process includes a multiplicity of views,
01:28:00.100 so we don't wind up with bad decisions. And if you don't think we can't make bad decisions,
01:28:05.220 just look at all the bad decisions the politicians and the business guys make. We're no different.
01:28:11.900 So if you did what you're suggesting, Alan, if you brought in a more heterogeneous group of views,
01:28:20.060 and greater diversity of priors, by definition, you could probably never arrive at a unanimous decision.
01:28:27.580 So what's wrong with that? Nothing's wrong with that. Well, is everything right with that?
01:28:32.900 Yeah, exactly. My question is, what does the guideline look like? So now let's take it back to
01:28:38.600 the doctor who has to see 40 patients in a day, will never listen to this podcast, let alone read the
01:28:48.720 show notes of this podcast, which are probably going to be 150 pages of the backup of everything
01:28:55.980 we've talked about in every study that's been cited, et cetera, et cetera. They literally just want to
01:29:00.680 know what to do in the moment with the person sitting in front of them. And currently they look
01:29:07.020 to the guidelines, which are unanimous, expert run, revised often enough that it gives you the feeling
01:29:14.680 that, Hey, they're keeping up with the science, right? Every five to 10 years, I'll get a new one
01:29:18.280 of these. Now it's going to be this complicated legal document. That's like reading the dissents
01:29:24.580 and reading the in favors. And I mean, again, I'm not saying that we shouldn't be doing this, but
01:29:29.360 how does it translate to the field? How did the guidelines read now?
01:29:33.560 Oh, they're pretty miserable. No mistake about it.
01:29:36.060 Not pretty miserable. They're totally miserable. I mean, you talked about legal documents,
01:29:41.280 but there's a summary and that's what the doctors typically read, right? The doctors will read
01:29:46.020 the one page executive summary that basically says, and that gets hammered home. And do you know
01:29:54.260 what? I get this rebuttal all the time. We've got to do this because the doctor who sees 40 patients
01:30:00.400 isn't going to do anything unless we dumb this down. I don't think most doctors are dumb. I think
01:30:07.340 they're caring. I think doctors want to do good jobs. I think we need to learn more about how we
01:30:13.980 present information. I don't think we should ever compromise on truth because when you do, you say,
01:30:22.620 I've got to do this in order to get to here. And I don't want to use your political history in the
01:30:28.900 United States negatively. But Afghanistan, I can't think of anybody right, left, or center who thinks
01:30:36.940 that the process getting in and throughout it represents the best efforts of the minds of
01:30:43.520 America. It doesn't. You guys are really smart, wonderful people. But it's what happens when you
01:30:51.460 boil the options down to two and you got to get it down to a one-liner. And life isn't a one-liner,
01:30:59.580 not real life. And if we're going to learn to make decisions that are to present information to our
01:31:06.300 patients, we're going to have to learn how to deal with doubt. That's what it's all about.
01:31:10.540 Yeah. It's funny. Just as you said that, I was about to say, the real problem here, Alan,
01:31:17.080 is we are not trained to be comfortable with uncertainty.
01:31:22.440 I think we are. I think that's what medicine's all about.
01:31:26.300 I think it is for things that can't be measured. And I think it's not. I think there's a false degree of
01:31:34.000 confidence that comes from things that can be measured. So you're absolutely right. In the olden
01:31:38.040 days, when a surgeon went down to the ER to evaluate somebody for appendicitis. So this was
01:31:43.700 long before the days when every one of those patients had a CT scan, right? This is based on
01:31:48.420 the books that I used to read from the great surgeons of the fifties and sixties, where this
01:31:53.320 was a purely clinical diagnosis. So you know, 7% of people in their lifetime are going to have
01:31:59.500 appendicitis. And you know that the pretest probability on this person is a heck of a lot
01:32:04.280 higher than 7% because they're sitting here right in front of you presenting with these signs or that
01:32:08.620 signs. But you also know that there's an asymmetry in your decision. In other words, there's two wrong
01:32:16.300 decisions that can be made here, operating on the person without appendicitis and not operating on the
01:32:21.920 person with appendicitis. And you also understand that you have to calibrate your decision making around
01:32:27.940 that uncertainty so that one mistake is more likely than the other. And so I think you're absolutely
01:32:33.780 right. I think most physicians are very good at doing that. Somehow that doesn't translate into the
01:32:42.040 type of uncertainty that I think is necessary to do what you want to be able to do, which is rather
01:32:49.160 than give people a unanimously agreed upon consensus that is so distilled down to simplicity that it borders
01:32:57.620 on being incorrect. You'd like to be able to give them the range of thoughts on a subject,
01:33:04.420 acknowledging that you can't tell them which one is correct. I think, for example, there are different
01:33:11.000 audiences. There's the practicing doctor, there's a practicing family doctor, there's a practicing
01:33:16.880 internist, there's the academic internist, there are the experts in the field. I think at a minimum,
01:33:26.360 you've got to have a range of opinion and the experts in the field. And I don't think we meet that
01:33:31.580 minimum. And I think that when there's doubt, you ought to be able to write, I'm not sure about this,
01:33:41.280 which we do when we have weak recommendations, but they're also always unanimous. What happens when
01:33:48.020 you put five people in a room, doctors, experts are no different. The one with the loudest voice
01:33:53.480 can carry the day. The one who claims the greatest expertise in the area can carry the day. And then
01:34:01.540 we wind up with documents that are very difficult to read and read like 20 years ago with minor
01:34:08.340 modifications. You can't say anything was wrong. Well, good gracious, we learned it was. Okay,
01:34:14.560 what's our problem? Who are we here for? Ourselves or our patients? And the truth. And so I think you
01:34:23.460 can write clearly and people can read and make informed choices. In the end of the day, what this
01:34:30.800 is saying is that people are too stupid to make a real choice. And I don't believe that. I believe
01:34:36.580 that when we tell people, when I've treated patients and made recommendations, were they always the right
01:34:42.140 ones? Of course not. They were what I thought was best to advise, but I can't claim they were always
01:34:48.880 right. And in knowing I could be wrong, then I calibrate the safest way through for my patient.
01:34:56.360 That's what makes me, if I was good, that's what helped me. If I'm wrong about this, how can I set up
01:35:01.960 something to catch it? How can I hedge my bet here? Or I got to go a little stronger here because I could
01:35:08.540 be missing this. Algorithms help us. Of course they do. But when we treat algorithms just by algorithms,
01:35:16.460 then that isn't what's called clinical medicine or clinical surgery. That's algorithms. And we have
01:35:22.640 good healthcare professionals who are more driven by algorithms and more advanced healthcare
01:35:29.020 professionals who can take the algorithms and work within them and around them. And everybody's doing
01:35:34.700 a good job. But we got to respect the fact that our understanding is limited and that science requires
01:35:45.180 different views to contend equally and that we need to write the truth. I mean, do you think that we've
01:35:52.880 seen an acceleration of the forcing function around a uniform voice? I mean, it seems to me that the past
01:36:01.740 18 months with COVID has really amplified what you're describing. I think there are lots of dissenting views
01:36:11.220 out there for how COVID could be managed, what the potential efficacy is for repurposed drugs.
01:36:20.460 And truthfully, I've struggled to wade through the literature on this stuff. And you know, you'll always
01:36:25.700 find somebody who's made it their mission to understand how this drug or that drug or this intervention
01:36:31.540 or that intervention is the solution to the problem. But there's no denying that such people have been
01:36:37.620 pretty roundly silenced
01:36:41.020 for this. And it begs the question,
01:36:44.260 should we be paying more attention to these views? And when do these views become so fringe and marginal
01:36:49.520 that they're actually harmful?
01:36:50.760 Because they can be. They can be. The first level of discussion is, should be amongst experts,
01:36:57.780 where you can call out views that are so divorced from experimental evidence that they're not serious
01:37:08.680 views. COVID is a great example. I heard good people express somewhat different views at different
01:37:16.620 times on different issues. Not the same person, but one person had a view and you say, gee,
01:37:23.340 that's a good point. But they were all within a channel that made sense to me as a physician,
01:37:29.600 not an infectious disease expert. So I'm not talking about legitimizing any possible view because it's a
01:37:38.260 possible view. I am saying that people were pointing out different aspects of a complex
01:37:45.880 problem. And they might put a little more emphasis here, but the result would be,
01:37:51.320 I understand more clearly that there is a series of choices involved and it's challenging to go
01:37:58.400 through them. In Canada, the government, we had much longer periods between the first and second
01:38:03.840 vaccination. So more people got their first dose before the second. So I get that. That's a decision
01:38:12.180 in real time that's a real challenge. You can't be sure that you got it right at the moment you're
01:38:19.340 making it. But you're the responsible person. You got to deal with it. But it was in the open so you
01:38:26.180 know it was being done. I'm good with that process because I know what happened and we can assess the outcomes.
01:38:33.840 I'm not good with someone just shrieking. What I'm against is saying because we can't have somebody
01:38:42.120 shrieking, we can't have any debate. That's wrong. That's totally wrong. Because it winds up then
01:38:49.220 we make mistakes where we don't have to make mistakes. The responsibilities we have to make
01:38:56.580 recommendations to our patients are so awesome. We need to be humble and say, okay,
01:39:03.840 give me your best shot. I'll give you my best shot. And we're colleagues. We're not enemies.
01:39:08.800 I mean, I disagree with lots of people because I have a scientific viewpoint, but they're not my
01:39:14.500 enemies. And we have ways of discussing this. And if I'm in the room, I can say, hey, you said that
01:39:21.800 I'll show you line 26 in your paper, which contradicts you. And he has to respond in front of other
01:39:28.060 people. That's what I believe in, is the testing of the argument in a jury of your peers.
01:39:35.920 Is that culture being watered down in science? Is it the same today as it was 30 years ago?
01:39:40.900 No, I think that's the weakness. I think that's the crucial weakness. I think inside the room,
01:39:46.020 that's what's not occurring. And I judge that by the product that comes out.
01:39:50.500 But why do you think that is? Why has this process become diluted?
01:39:55.160 People get attached to views because there's emphasis on consensus and unanimity.
01:40:01.120 You don't want Snyderman in the room because he's going to argue for Apo B.
01:40:04.560 You can deal with me. I'm not hard to deal with. You can say, okay, I heard you,
01:40:11.200 but here's what's wrong with you. Your argument, not me personally. Here's what's wrong with your
01:40:16.120 argument. But has something changed to make it that ideas are more personal? What is the factor
01:40:21.900 that has led to, or factors that have led to that? I think people are invested in what came out.
01:40:28.000 In a way that they weren't before? No. I mean, I think people used to become
01:40:31.620 known for their own science. Now, if you're on the guidelines, that's your science. You're very
01:40:39.020 prominent because you're on the guidelines. Not that you did the science, you're on the guidelines.
01:40:43.400 And we have so much science that's done, like the clinical trials. I mean, I think clinical trials
01:40:48.940 are wonderful, but they're limited tools. I think the composition of the committees needs to be
01:40:55.240 re-examined. And I think you ought to be able to criticize what comes out. Apo B is my thing.
01:41:01.880 I wrote a critique of the 2018 American guidelines. How many references were there on the comparison of
01:41:09.600 MAPO B and LDL cholesterol and non-HDL cholesterol? In the guideline? Yeah. Five?
01:41:16.060 There were four. Two from a group opposed and two from me. And mine weren't even correctly cited.
01:41:22.820 That's one issue. They dealt with a whole bunch of issues. But that's not adequate. That wouldn't
01:41:28.840 get you a passing grade in school. And we're not limited now by space in dealing with issues. We can
01:41:34.680 put anything out on the internet for anybody who wants to read it. And what that represented to me
01:41:40.920 was that I can't tell what happened inside the room, was there wasn't a full discussion. We didn't
01:41:47.700 have these processes when I was young. Contending ideas could contend more easily. I think Apo B,
01:41:54.980 I don't think it's going to happen. Not because there is value, but I think there were a group of
01:42:00.400 people who just weren't interested. And that's sad. And you think that ultimately there are still
01:42:06.260 that many physicians who are going to defer to the guidelines. Reimbursement's not an issue,
01:42:13.460 right? Apo B bills your insurance company $4 and its cash pay is $2.50. I mean, this is not a cost
01:42:20.620 issue. This is really an awareness issue on the part of physicians. That's really all it comes down to at
01:42:25.560 this point. Well, the guidelines presented as a cost issue. That's the argument against Apo B.
01:42:30.700 Right. But the guidelines must have failed to actually look at the cost then.
01:42:34.280 That's correct. That's correct. I know that. But I can't say that because the guidelines are the
01:42:41.340 guidelines. That's what I'm objecting to. Of course you can say it, as that's what we're
01:42:45.180 talking about here. I mean, that might be your next paper is do a survey of the laboratory cost of
01:42:51.380 Apo B and the average Medicare reimbursement rate on it across the United States or something to that
01:42:56.700 effect. Those are valuable exercises, right? I think they are. And we did a cost analysis
01:43:03.260 on Apo B, I think using a charge of $10 and looking at the cost of care. And I think it contributed
01:43:13.080 0.01% to the cost of care, something like that. Okay. The concept that a $10 test really changes
01:43:21.520 the cost of care. The whole thing is so idiotic. The last time I looked in the United States,
01:43:27.340 and admittedly, we're spending infinitely more than we should and infinitely more than anybody else.
01:43:32.900 This is 10-year-old data. You know it's probably closer to 10,000 now. But 10 years ago in the United
01:43:39.500 States, our healthcare spending was $7,000 per person per year. That's 10 years ago. So again,
01:43:45.220 I don't see how it's less than $10,000 per person per year in the United States today.
01:43:51.000 So if the Apo B test cost $100, which again is 20 times more than it actually costs, so what?
01:44:01.040 Atherosclerosis, when last I checked, is the number one killer of men and women. It kills
01:44:07.500 women at a rate that is more than 10 times that of breast cancer. I mean, are we missing something
01:44:14.260 here? Is there some part of this that you haven't told me? That's my frustration. That's my sadness.
01:44:22.200 You're absolutely correct. This is Pennywise, Pound Foolish, where it's lives that are being lost.
01:44:28.820 And we've calculated the number of lives and heart attacks that could be avoided. Lives saved,
01:44:35.280 heart attacks are avoided if we switched to Apo B. The American College of Clinical Chemistry,
01:44:41.580 the European clinical chemists, they have a series of reports saying Apo B can be measured more
01:44:47.740 accurately than LDL cholesterol or non-HDL cholesterol. No question. Is that in any of the guidelines?
01:44:54.440 Accuracy of measurement? No. That's what's so hard to deal with when you say you're criticizing the
01:45:02.640 guidelines. Maybe it's just you. Who are you? You're a nobody, which is true. But I'm saying,
01:45:08.880 look, it's a laboratory test. Surely the quality of the measurement is something that should be
01:45:15.660 mentioned. The diagnosis of type 3 can't be done without Apo B. So any hypertragalistratomy
01:45:23.360 patient needs an Apo B. Not done. Not mentioned type 3. So I can't beat on you with sadness and stuff.
01:45:32.640 I've been incredibly privileged to have the opportunity to try and understand the world
01:45:40.540 around me. My background is not a, would have normally led someone like me to have that chance,
01:45:46.520 nor to work with the quality of people that I've had the privilege of working with. And I've been
01:45:53.440 able to write and record the images of the world that looked real to me. And how few human beings ever
01:46:01.960 get that privilege? And I'm just sad that it won't help. It won't help people. I'm sad about that.
01:46:09.620 And I'm sad that you go so far in the thinking and then somebody can take it to the next step.
01:46:15.200 It's not like I've done that much. Somebody can see this and say, oh, wow, if that's so,
01:46:21.980 let's go there. And it's not going to happen.
01:46:24.960 I don't agree on two levels. The first, I'm going to call you out on this, Alan. For a guy who
01:46:31.340 understands uncertainty and probability and risk, you're using awfully black and light white language
01:46:38.120 right now. It's not going to happen. With what certainty can you say that?
01:46:43.960 So you're right. You're right. And it's self-pity. And it's not attractive to me either.
01:46:50.640 Okay. And I'm not saying that to belittle the point of view. What I'm really saying is
01:46:55.620 there's a beautiful story about the guy that's hitting the stone, right? The mason who's
01:47:00.820 hammering away on the stone for 10,000 strikes. And on the 10,001st strike, when he hits the stone,
01:47:10.220 it finally fractures. Now to the person watching it, it was that 10,001st strike that fractured the
01:47:18.180 stone. But of course, the stonemason knows that it was that strike plus the 10,000 that came before
01:47:25.180 it. And so you just have to accept the non-linearity of the advancement of knowledge. It's embarrassing
01:47:31.960 that I would even attempt to try to say that to you because you know that so much better than I do,
01:47:35.640 of course. But maybe in this one situation, Alan, you're just closer to it than I am. And therefore,
01:47:42.960 you're just too close to the political environment of it. Because at the end of the day, these consensus
01:47:48.680 statements are largely political. They're far more based on who you are and who you know and how long
01:47:54.340 you've been on the committee than the strength of the evidence. But I wouldn't bet against the truth.
01:47:59.620 I think that in the end, the truth generally wins in science. Not always, but it also depends on your
01:48:05.700 time course. It just wouldn't surprise me if in 10 years, 20 years, we're going to look back at this
01:48:12.460 just as we are looking back today at HDLC. I mean, that was not that long ago, Alan, that people thought
01:48:19.220 HDLC was everything. And today, thanks to the CTEP trials, the MRs, we now know HDLC is A,
01:48:31.020 much more complicated than we ever thought. And B, probably not something we should be trying to
01:48:37.440 manipulate in an effort to improve outcomes. At the end of it all, that's what I'll hope for.
01:48:44.000 You need to pick yourself up and keep fighting. We have a new observation that we think is
01:48:50.600 even different, more startling than anything you've heard. And we'll try. To quit is wrong.
01:48:58.260 Part of this is for yourself just to see, can you understand what looks like chaos? Is there any
01:49:05.860 pattern to what looks like there's no pattern? How does blood sugar and lipids and how do they
01:49:14.060 combine to hurt us? So just to have the privilege of looking at those questions and to write down your
01:49:24.560 thoughts in a manuscript and to publish the manuscript. So few people ever have that privilege.
01:49:30.300 I mean, I've just been extraordinarily rewarded for the very little bit that I've been able to achieve.
01:49:39.420 So I have a short fuse and it annoys me. Stupidity annoys me. Ignorance annoys me.
01:49:47.340 And pretentiousness annoys me deeply.
01:49:50.180 Look, I think those are all things worth being annoyed at. Another one of your strengths, Alan,
01:49:55.080 that I've observed over the 10 years that we've known each other, maybe longer,
01:49:59.020 is you have an insatiable curiosity about things that are theoretically or in quotes,
01:50:04.240 theoretically outside of your lane. And we've probably exchanged as many emails on the
01:50:08.580 mechanisms of insulin resistance as we have on everything that's related to lipids. So
01:50:14.700 I think that that's a very important part of your success, which you've been very modest in downplaying
01:50:21.540 is the breadth to which you think about this problem. I think that's why you've been able to
01:50:28.040 spot patterns that are not obvious to others. Before we wrap, there's one thing I want to go
01:50:33.780 back to because we spoke about it quite briefly, but I think it is so important. And when we spoke about
01:50:40.560 it at the outset, we hadn't given the listener the full landscape of the disease, but now that we
01:50:46.260 have, I think they will understand more what you mean when you talk about the causal model of risk,
01:50:52.980 this 30 year causal model versus just a risk calculator. So let's go back to that. You go to
01:51:00.040 a Framingham risk calculator and you plug in a few variables. I'm this old. I do smoke or I don't
01:51:06.500 smoke. My HDL cholesterol is this. My blood pressure is this. What is my 10 year risk? And
01:51:14.040 you hit click on the button and a number comes up. And most of the guidelines say, if that number is
01:51:22.920 below something, the typical response would be if the 10 year risk is below 5%, there is no need to
01:51:31.780 treat carry on as normal. I'm exaggerating a little bit, but that's the gist of it.
01:51:36.500 I practice medicine a very different way because I have a very different goal. I have an objective
01:51:42.300 for how long a person might be able to live disease free. And I also tend to be influenced
01:51:48.800 by people like you who have taught me how long it takes for this disease to take hold. So the analogy
01:51:55.180 I would use is imagine there was a calculator that told you how much money you should be saving for
01:52:03.900 retirement, but it could only predict 10 years into the future. It wouldn't be a very useful tool
01:52:09.800 because a 30 year old isn't going to be retired in 10 years. So how has your thinking,
01:52:18.380 which has influenced me greatly, how did you come to the 30 year model that is based on the
01:52:25.540 causal relationship? What are the types of yields that we see there?
01:52:29.780 Part of it is utilitarian. 30 years was the longest stretch we had reliable data for. And part of it
01:52:37.880 was that the period of uncertainty is greatest between age 30 and I'm saying 60, but 55, whatever. That's
01:52:49.760 where the 10 year falls down. And we originally did these models based on 10 year risk. And you could
01:52:58.320 say, you're right. We're going to miss most premature disease. Let's just lower the risk. Instead of 5%,
01:53:06.240 we'll make it 2.5%. And you could do that. The problem is it's not cost effective because you're
01:53:12.580 multiplying the number you need to treat more than you would need if you start off with a cause.
01:53:18.700 Now, let's say I categorize you by your ApoB or your non-HCL cholesterol. Let's say you have a high
01:53:24.600 ApoB. So you're in this group of about 25% of the population because I use 25%, 75% to get you there.
01:53:33.520 So that group has over 30 years, a 30% event rate. It's a lot. It's not just the ApoB that's doing it.
01:53:43.060 Age is still a big driver.
01:53:45.040 Age is a driver, but they'll be fatter at the start. Their blood pressure will be a little higher at the
01:53:50.380 start. It's not that the other things are being left out. You're catching them. You're just selecting
01:53:56.540 differently. And I would submit you're selecting more accurately because I can measure ApoB or
01:54:04.160 non-HCL cholesterol with much less error than I can measure your risk. The variables that we know
01:54:13.040 Michael Pincin has calculated, we account for about 20% of the variance in risk. That's about it.
01:54:18.780 That's a small number. So from a utilitarian perspective, by stretching up and using the
01:54:26.520 idea of cause and precision of measurement, I group you. Then I can present a patient with what
01:54:33.760 we know about the group and they can make their decision. There are people who say, thank you,
01:54:39.900 I'll pass. They come back in six months, a year. We can have the same discussion again.
01:54:46.320 I didn't lose anything. They've lost some and we can show that. But these aren't decisions that you
01:54:52.820 can't revisit. If someone starts on therapy, they can decide to stop it. Patients are free agents.
01:55:00.300 I mean, I respect that. And it's up to us to present our arguments and continue to present them
01:55:05.140 as we frame them to what we think is their best interest and the best we can do. So I like to
01:55:11.360 maintain contact with my patients who are in this sort of thing to make sure that they know
01:55:16.000 they can change their mind, but I can also show them progress. If their APOB started at 120 and we're
01:55:24.040 down to 60, I know they're taking the medication. I really do. Otherwise it would be 120. And they can
01:55:33.040 see and appreciate the extent of change that's occurred. For me and for the patients I've cared for,
01:55:39.400 that tends to work. One of the things that I find very helpful to explain this, because it's
01:55:44.980 non-linear, and I think non-linearity is not innate to us. I don't think evolution needed us to be able
01:55:51.780 to think non-linearly. I think linear thought was good enough, and that included linearity with time
01:55:57.600 and chance. But this problem doesn't lend itself to that. And therefore, I think it's not intuitive
01:56:04.340 to somebody who hasn't fiddled with numbers a lot, or hasn't spent time looking at things that
01:56:10.260 compound. Even if you were just to look at a risk-based model that was short-term, there's a
01:56:17.660 significant benefit to reducing risk from 4% to 2% over a decade. Because even though that might only
01:56:27.860 mean there's a 2% risk reduction over the next decade, the amount that that amplifies over 2,
01:56:35.120 3, and 4 decades is amazingly counterintuitive, just in the way it is if you think about saving
01:56:42.000 for retirement. If you're 40 years old, or hopefully younger when you start saving for retirement, if
01:56:47.400 you're 30 years old when you really start in earnest to saving for retirement, and you have
01:56:53.500 one option that's going to generate a return of 7%, and another that generates a return of 10%,
01:57:01.200 or 9%, there's a two percentage point difference, that's not going to yield an enormous difference
01:57:06.360 by the time you're 40. But by the time you're 70, it does. I've done the math on these, and you can
01:57:12.060 easily show how it can literally double the nest egg, just based on relatively small changes up front.
01:57:18.440 So I think that's also part of the issue here, is just understanding what compounding does,
01:57:24.280 and how it works in your benefit when you're talking about investing, but understanding how
01:57:28.600 it works against you when you're talking about a disease like atherosclerosis.
01:57:32.720 We've done some of these calculations, and you're right, starting early pays off later. And when you
01:57:40.100 start later, what you're doing essentially is to try and modify the disease that's already present.
01:57:46.720 When you're starting early, what you're actually doing is stopping disease from developing.
01:57:52.600 And if you can stop a lesion developing, that's 100% success. Trying to treat, modify through one
01:58:00.460 process, a complex set of outcomes at this end, much less likely to succeed. So stopping disease
01:58:12.300 is perfect prevention. Treating disease is partial prevention, and it has to be partial. Can't be
01:58:19.900 more. Yeah, I think that's a very important point, because although we haven't stated it explicitly,
01:58:27.000 the undertone of everything we've said is not only that ApoB is causal, but that it's a necessary but
01:58:34.040 not sufficient driver of atherosclerosis. And I think that's important because necessary but not
01:58:40.320 sufficient creates a lot of confusion in medicine, doesn't it? Necessary means you have to have an
01:58:46.700 ApoB particle traffic a lipid into an artery wall. If that doesn't happen, you don't get atherosclerosis.
01:58:52.640 Sufficient means if that's the only thing that happens, do you necessarily get disease? No,
01:58:58.060 you don't. Each of us could rattle off tons of patients who somehow make it into their 90s
01:59:02.360 with high ApoB and don't have disease. But from a prevention standpoint, it's much easier to go
01:59:09.360 after something that's necessary because you only have to block that versus once the disease has
01:59:15.760 already taken hold, you're advancing something that's multifactorial. So I think that's a very
01:59:21.700 important point you raise, and I don't think it gets made enough. Well, Alan, you were a little
01:59:26.640 reluctant to sit down. You didn't see the value in doing a podcast, but I'm glad we twisted your arm a
01:59:31.780 little bit. It's funny. I didn't realize until a little while ago that you were 80. You always
01:59:36.800 come across as so much younger to me. So that explains to me why you've got lots of miles left
01:59:41.640 in terms of the ApoB work and the crusade here. So I'm very optimistic.
01:59:47.140 It was nice to... Dinner would be even nicer, but this was nice to speak with you again.
01:59:53.000 We'll make that dinner happen again at some point. So, Alan, thanks so much.
01:59:56.240 You're very welcome.
01:59:58.020 Thank you for listening to this week's episode of The Drive.
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