The Peter Attia Drive - Qualy #65 - The three laws of medicine — Law #1: A strong intuition is much more powerful than a weak test

Episode Date: November 26, 2019

Today's episode of The Qualys is from podcast #32 – Siddhartha Mukherjee, M.D., Ph.D.: new frontiers in cancer therapy, medicine, and the writing process.    The Qualys is a subscriber-exclusive podcast, released Tuesday through Friday, and published exclusively on our private, subscriber-only podcast feed. Qualys is short-hand for “qualifying round,” which are typically the fastest laps driven in a race car—done before the race to determine starting position on the grid for race day. The Qualys are short (i.e., “fast”), typically less than ten minutes, and highlight the best questions, topics, and tactics discussed on The Drive. Occasionally, we will also release an episode on the main podcast feed for non-subscribers, which is what you are listening to now. Learn more: https://peterattiamd.com/podcast/qualys/   Subscribe to receive access to all episodes of The Qualys (and other exclusive subscriber-only content): https://peterattiamd.com/subscribe/  Connect with Peter on Facebook.com/PeterAttiaMD | Twitter.com/PeterAttiaMD | Instagram.com/PeterAttiaMD 

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So without further delay, I hope you enjoy today's quality. I wanna talk about another book you wrote that doesn't get as much attention, which is the laws of medicine. You wrote that after Emperor before the gene, correct? That's right. So laws of medicine is a very different mandate as it were, and that's because the book came out in association with Ted.

They had commissioned 10 books by 10 thinkers around the world, and they asked me to write a book on that, and it's necessarily a small book It's really a you know the mandate was to write basically a 75 page book Expanding on a single very very incisive idea. So that's the laws of medicine. Yes If I if I got them correctly the three laws are a strong intuition is much more powerful than a weak test Uh-huh How did you think of that and And what is the most important application of that law to the way you think about medicine or specifically oncology today?

This to me is one of the great neglected ideas in medicine. Perhaps one of the great neglected ideas in the world. This idea initially comes from Thomas Bayes. This is a Bayesian idea. Thomas Bayes was a cleric, but by evening he was a mathematician and an economist. And he let his work leads to one of the most seminal and funny thought experiments that I've ever encountered, which is the following. And I sometimes quiz my daughters with it, which is the following. This is not Thomas Bayes' own example, but it arises out of Thomas Bayes' work. And he one might imagine going to a street fair and encountering a man whose tossing coins and he tosses coins and your job is to predict whether the next

Flip coin flip is going to be heads or tails and so he tosses the coin 20 times and all 20 times its tails So then he turns to the crowd and he says what's the next coin flip going to be heads or tails? now the crowd and he says, what's the next coin flip going to be heads of tails? Now, the mathematician in the crowd who's the professor of mathematics says 50%. Says 50%. And you know everyone says absolutely right. But the child in the crowd says, no, no, you don't understand. This is a stupid problem. It's the coins rigged. The coin has only, it has two heads or two tails as case may be. And the child's right, and what's important about that insight, is that the mathematician

imagines the world, this in this case, this is not a stab at mathematicians in general, but the professor of mathematics, thinks of the world as having no history, as having no a priori. It's a world that's created in over every time. The coin is flipped and its heads and tails equal every time. But the child knows, and humans know, that in fact the world doesn't behave like that. Everything has priors, and you need to understand

those priors before you can understand the posterias as wisdom in that idea. And it took someone like Thomas Bayes to figure that out that most of our lives, we aren't living our lives like the crazy mathematician, professor. We are living our lives like the child. We're thinking to ourselves, what was the prior antecedent? Imagine this is true for any corner of your life.

The first question you ask yourself when you're trying to solve a problem, trying to understand the cosmos, trying to understand something, you ask yourself, what was the prior life? Did the Sun set in the West last night? And how about the night before? And maybe I don't need to create a formula to figure out whether the sun is going to set on the West or the East tomorrow. It's because it's set on the West every time.

There are obviously loopholes and gaps to this kind of thinking. There are surprises that you can miss. So Bayes' fundamental idea was that you can only interpret a test in the light of what that test is predicted in the past. It's an extraordinarily important idea in the way we think about the universe, that the past performance of a test tells you something, not everything, but tells you something about

the future performance of a test. And you can apply it to many, many things in the world. You can apply it to any kind of thinking, economic thinking, climate change or into thinking, that the past is a guide to the future, not only in a kind of loose way, but you're really using a real stat weighted strongly by the past. And this of course applies to medicine, and it's a forgotten rule in medicine. Although it does seem like one of the things that I've always felt physicians innately do well without realizing it, which is the opposite

of where I want to be, not to take the pot shots, but I think where we do very poorly is an understanding asymmetric risk. I hope you enjoyed today's quality. Now sit tight for that legal disclaimer. This podcast is for general informational purposes only and does not constitute the practice of medicine, nursing or other professional healthcare services, including the giving of medical advice.

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