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

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

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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. 0.99

00:15:53.980 And when you destroy the normal architecture of the artery, you can't restore it. So a lot of our 0.94

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, 0.99

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 0.78

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. 0.99

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 0.92

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 0.86

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 0.89

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 0.55

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%. 0.97

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, 0.98

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 0.99

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 1.00

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 1.00

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 0.75

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, 1.00

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. 1.00

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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The Peter Attia Drive - November 29, 2021

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

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