Reviews,  Science

Are there Laws of Medicine?

"The discipline of medicine concerns the manipulation of knowledge under uncertainty."
(page 70)

Book review, Title The Laws of Medicine, Author Siddhartha Mukherjee, Rating 3.5, Are there laws of medicine?

The Laws of Medicine

Siddhartha Mukherjee

Book review

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Modern medicine began embracing scientific methods during the last couple of centuries, and in the past one hundred years this has produced an explosion of medical technologies that have aided physicians in significantly controlling some diseases and in particular, extending lives. Today in developed countries, many tests are available for diagnosis and many drugs are available for possible treatment. So why can't physicians today just run a comprehensive battery of tests for every sick patient and spit out a clear diagnosis, and with that, a clear prognosis and plan for a cure? Siddhartha Mukherjee proffers an answer via his Laws of Medicine.

Oncologist Siddhartha Mukherjee writes with polish and passion about the practice of medicine. He points out that much is still not well understood in biology, and by extension, in the human biology which underpins modern medicine. He formulates three simple Laws of Medicine that underscore the difference between medical laws and the laws of physics: The complexity of living organisms is vast, and resists the kind of rigorous mathematical description that physics has achieved, leaving a formulation that highlights the art of marrying medical science with careful observation of individual patients.

Dr. Mukherjee characterizes these as "laws of uncertainty, imprecision, and incompleteness. They apply equally to all disciplines of knowledge where these forces come into play. They are laws of imperfection."(p. 6) 

Law 1: Priors. A strong intuition is much more powerful than a weak test.

The first law seems to imply that feelings are better than scientific measurements. Rather what Dr. Mukherjee alludes to is that every test result can be simply wrong some portion of the time. This has to be accounted for during the diagnostic process. If someone tests HIV positive, and he has a prior history of drug addiction, and drug addicts have a much higher prevalence of HIV infection, then the probability of the HIV positive test being valid increases.

In other words, a physician must employ Bayesian logic in evaluating a test result, based on priors: a patient’s history, examination results, and previous tests. He suggests that for many tests, "if patients are screened without any prior knowledge about their risks, then the false-positive or false-negative rates can confound any attempt at diagnosis."(p. 28)  The intuition is the physician’s application of his experience examining and treating patients, and doing what "the most incisive doctors do: he is weighing evidence and making inferences. He is playing with probability."(p. 29) 

"A test is not a Delphic oracle, Bayes reminds us; it is not a predictor of perfect truths. It is, rather, a machine that modifies probabilities."(p. 33) 

Law 2: Outliers. “Normals” teach us rules; “outliers” teach us laws.

The young science of medicine is much more likely to see outliers than the mature physics of say, the mechanical behavior of materials. Since there is still much not understood about human biology, outliers are more common, and are indicators of areas to be explored: "we have little understanding of what makes an individual lie outside the normal range."(p. 51)  An “outlier” patient, one whose symptoms fall outside of established rules, is treated with the best experience the physician can bring to bear, and the outcomes, good or bad, form the basis for future increase of knowledge to refine the rules, to finally mature the rules into a law.

Law 3: Biases. For every perfect medical experiment, there is a perfect human bias.

Hope plays a large role in medicine: A patient hopes for a return to health, healthcare professionals hope to provide a cure. It is also a large source for the introduction of biases on the part of patient and physician, which can distort good diagnoses and treatment. Medical experiments ultimately must be made on human populations, and bias unavoidably creeps in to all experiments, even rigorous double-blind protocols. Physicians must be watchful for bias, including their own. Patients own biases can produce inaccurate histories, or distorted responses to experimental protocols.

Priors, outliers and biases are central to the practice of medicine. Medical science has dramatically increased the ability for physicians to diagnose and treat ill health, but it not only has not eliminated the imprecision of past medical treatment, it has placed a premium on a physicians ability to sort out what is relevant to the particular patient under care.

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