The Laws of Medicine Quotes

“It’s easy to make perfect decisions with perfect information. Medicine asks you to make perfect decisions with imperfect information.”
― Siddhartha Mukherjee, The Laws of Medicine: Field Notes from an Uncertain Science

“The greatest clinicians who I know seem to have a sixth sense for biases. They understand, almost instinctively, when prior bits of scattered knowledge apply to their patients—but, more important, when they don’t apply to their patients.”
― Siddhartha Mukherjee, The Laws of Medicine: Field Notes from an Uncertain Science

“The moral and medical lessons from this story are even more relevant today. Medicine is in the midst of a vast reorganization of fundamental principles. Most of our models of illness are hybrid models; past knowledge is mishmashed with present knowledge. These hybrid models produce the illusion of a systematic understanding of a disease—but the understanding is, in fact, incomplete. Everything seems to work spectacularly, until one planet begins to move backward on the horizon. We have invented many rules to understand normalcy—but we still lack a deeper, more unified understanding of physiology and pathology.”
― Siddhartha Mukherjee, The Laws of Medicine: Field Notes from an Uncertain Science

“The discipline of medicine concerns the manipulation of knowledge under uncertainty.”
― Siddhartha Mukherjee, The Laws of Medicine: Field Notes from an Uncertain Science

“I had never expected medicine to be such a lawless, uncertain world. I wondered if the compulsive naming of parts, diseases, and chemical reactions— frenulum, otitis, glycolysis— was a mechanism invented by doctors to defend themselves against a largely unknowable sphere of knowledge. The profusion of facts obscured a deeper and more significant problem: the reconciliation between knowledge (certain, fixed, perfect, concrete) and clinical wisdom (uncertain, fluid, imperfect, abstract).”
― Siddhartha Mukherjee, The Laws of Medicine: Field Notes from an Uncertain Science

“Is medicine a science?”
― Siddhartha Mukherjee, The Laws of Medicine: Field Notes from an Uncertain Science

“I had never expected medicine to be such a lawless, uncertain world.”
― Siddhartha Mukherjee, The Laws of Medicine: Field Notes from an Uncertain Science

“Every diagnostic challenge in medicine can be imagined as a probability game. This is how you play the game: you assign a probability that a patient’s symptoms can be explained by some pathological dysfunction—heart failure, say, or rheumatoid arthritis—and then you summon evidence to increase or decrease the probability. Every scrap of evidence—a patient’s medical history, a doctor’s instincts, findings from a physical examination, past experiences, rumors, hunches, behaviors, gossip—raises or lowers the probability.”
― Siddhartha Mukherjee, The Laws of Medicine: Field Notes from an Uncertain Science

“If medicine is a science at all, it is a much softer science. There is gravity in medicine, although it cannot be captured by Newton’s equations. There is a half-life of grief, even if there is no instrument designed to measure it.”
― Siddhartha Mukherjee, The Laws of Medicine: Field Notes from an Uncertain Science

“Think about the vast range of medicines and surgical procedures not as therapeutic interventions but as investigational probes.”
― Siddhartha Mukherjee, The Laws of Medicine: Field Notes from an Uncertain Science

“Perhaps the most striking illustration of Bayes’s theorem comes from a riddle that a mathematics teacher that I knew would pose to his students on the first day of their class. Suppose, he would ask, you go to a roadside fair and meet a man tossing coins. The first toss lands “heads.” So does the second. And the third, fourth . . . and so forth, for twelve straight tosses. What are the chances that the next toss will land “heads” ? Most of the students in the class, trained in standard statistics and probability, would nod knowingly and say: 50 percent. But even a child knows the real answer: it’s the coin that is rigged. Pure statistical reasoning cannot tell you the answer to the question—but common sense does. The fact that the coin has landed “heads” twelve times tells you more about its future chances of landing “heads” than any abstract formula. If you fail to use prior information, you will inevitably make foolish judgments about the future. This is the way we intuit the world, Bayes argued. There is no absolute knowledge; there is only conditional knowledge. History repeats itself—and so do statistical patterns. The past is the best guide to the future.”
― Siddhartha Mukherjee, The Laws of Medicine: Field Notes from an Uncertain Science

“It is here that an insight enters our discussion—and it might sound peculiar at first: a test can only be interpreted sanely in the context of prior probabilities.”
― Siddhartha Mukherjee, The Laws of Medicine: Field Notes from an Uncertain Science

“In 1980, nearly eight decades after Halsted’s first operation, a randomized trial comparing radical mastectomy with a more conservative surgery was formally launched. (Bernie Fisher, the surgeon leading the trial, wrote, “In God we trust. All others must bring data.”)”
― Siddhartha Mukherjee, The Laws of Medicine: Field Notes from an Uncertain Science

“He had inverted a paradigm: rather than spending an enormous effort trying to figure out why a drug had commonly failed, as most of his colleagues might have, he would try to understand why it had occasionally succeeded. He would try to map the landscape of the valley of death—not by querying all those who had fallen into it, but by asking the one or two patients who had clambered out.”
― Siddhartha Mukherjee, The Laws of Medicine: Field Notes from an Uncertain Science

“These “outlying” questions are the Mars problems of medicine: they point to systematic flaws in our understanding, and therefore to potentially new ways of organizing the cosmos. Every outlier represents an opportunity to refine our understanding of illness.”
― Siddhartha Mukherjee, The Laws of Medicine: Field Notes from an Uncertain Science

“It is easy to appreciate the theological import of this line of reasoning. Standard probability theory asks us to predict consequences from abstract knowledge: Knowing God’s vision, what can you predict about Man? But Bayes’s theorem takes the more pragmatic and humble approach to inference. It is based on real, observable knowledge: Knowing Man’s world, Bayes asks, what can you guess about the mind of God?”
― Siddhartha Mukherjee, The Laws of Medicine: Field Notes from an Uncertain Science

“technological innovations do not define a science; they merely prove that medicine is scientific—i.e.,”
― Siddhartha Mukherjee, The Laws of Medicine: Field Notes from an Uncertain Science