Humans have always searched for truth by finding rules in the midst of uncertainty, and medicine is no exception. Medicine has developed treatments based on empirical data, but uncertainty remains when it comes to applying them to individual patients. Modern medicine is based on scientific principles, but because of its limitations and complexity, it is not a perfect science and relies on imperfect science.
Human history has been a constant struggle to find certainty in the face of uncertainty. Humans have tried to find truth in various fields, including religion, philosophy, and science. In ancient philosophy, the discussion of the Ideas was a quest to know the nature of things, and in science, Newton’s laws were an attempt to understand the laws of motion. There is one important common thread in all of these truth-seeking endeavors. Reasoning from rules. Long ago, humans discovered the rules of cyclical climate change and used them to predict future climate, which helped us evolve from a hunter-gatherer society to an agricultural one.
Medicine is similar to this. Doctors have categorized a myriad of pathological symptoms into rules to define specific diseases, and have developed appropriate treatments based on past clinical experience. When a patient comes to the doctor, they use these rules to deduce a diagnosis and treatment. Medicine is also a discipline that starts from uncertainty and seeks certainty. Along the way, medicine still contains many uncertainties. However, rather than recognizing this uncertainty, people tend to see medicine as a discipline of refined certainty. For example, when a doctor tells a terminally ill cancer patient how long they have left to live, this is often misunderstood as the “exact time of death. However, the timeframe they mention only means that, on average, patients are more likely to die in that timeframe, not that all patients will not make it. Also, after surgery, when a doctor explains the different possibilities to a patient’s family, they may ask, “At the end of the day, is he going to live or is he going to die?”
Even in modern medicine, uncertainty still exists, and there are questions about whether it will ever be fully resolved. Paradoxically, the more advanced medicine becomes, the greater the uncertainty. As testing technology improves and new drugs and treatments are developed, the diagnosis and treatment of disease becomes more refined and complex. The result is a tangle of medical rules that are increasingly difficult to interpret and apply in diagnosis and treatment.
The uncertainty of medicine can be traced back to its very definition. It is “the study of the structure and function of the human body, the various phenomena of health and disease, and the development of techniques for maintaining health and preventing and treating disease.” The words “human body” and “treatment” are important here. The human body is very complex, and every individual is different. In dealing with this complexity, doctors must apply universal rules based on empirical statistics. But even those universal rules are myriad and varied. This creates uncertainty about how to interpret and apply collective data to individual patients.
For example, when we say that a particular cancer drug works, we mean “it worked in a valid percentage of patients in clinical trials,” not “it works in all patients.” There’s also no guarantee that people with a particular disease will always follow the same course. Similarly, even if a patient is diagnosed with “appendicitis” based on a combination of symptoms, there is no guarantee that it is 100% appendicitis. In fact, 60% of patients are likely to have appendicitis, but the remaining 40% could have something else.
Modern “evidence-based medicine” is based on reproducibility and universality – the assumption that the same treatment will produce the same results and can be applied anywhere. But can medicine really be called a science when it’s ruled by uncertainty? What parts of medicine are scientific and what parts are unscientific?
Let’s start with the process of devising treatments. There are two main ways in which treatments are developed. The first is when a treatment is proven to work empirically by chance and then recognized as a treatment through research. The second is when a scientific theory is applied to develop a treatment for a specific condition. An example of the first is the anti-inflammatory drug aspirin, which was recorded in Egyptian papyri in 1500 BC. The second example is antivascular therapies based on VEGF receptors, for example, which came from the study of neovascularization in tumors. The latter is scientific because it was developed based on scientific principles. However, the former is based on empirical statistics, so it’s hard to call it scientific.
In the case of aspirin, it was initially used empirically, but then scientific research revealed its principles. Aspirin has been shown to reduce inflammation and pain by inhibiting the enzyme cyclooxygenase, and to produce an antipyretic effect by acting on the central body temperature regulation system. Aspirin is a classic example of a drug that started as a non-scientific experience and became scientifically based.
Similar uncertainty exists in the process of diagnosis and prescription by doctors. A particular symptom can be a symptom of many diseases, and the probability is not 100%. Doctors use a combination of symptoms and data to make a diagnosis, but the process is fraught with uncertainty. And even if a treatment is approved, it’s not certain that it will work for a particular patient. In the end, even if we follow the rules of medicine, it’s not scientific to synthesize all of these processes, and the final judgment is made by imperfect humans.
Therefore, medicine is an “imperfect science. Medicine seeks probabilistic diagnosis and treatment through rules, but the nature and complexity of individual patients often prevents a perfect scientific approach.
