On the Relationship between Pain Variability and Relief in Randomized Clinical Trials
By Siddharth Tiwari
Pain is tricky to study. Along with being the most prevalent chronic medical condition in the world, pain forces us to combine our understanding of physiology and the philosophy of the self and mind. This is because pain is considered a “subjective experience”, limited to the individual themselves … We can think of many examples where two different people are presented with the same stimuli or situation and produce a different response: stubbing a toe or holding a hot object, for example. There are even situations where we may respond to stimuli that shouldn’t result in pain. A famous example from 1995 describes a 29-year-old builder who jumped onto a 7-inch nail. He wailed in pain on his stretcher and the ambulance as the nail stuck out of both sides of his steel-toed boot. But when the doctors peeled off the builder’s boot, they found that the nail hadn’t penetrated any part of his foot. It had passed between his toes, without a scratch … A simple linear regression, used improperly, can be overwrought with bias and confounding effects. With the increased availability of data available to the public, it has become increasingly dangerous to make assumptions of the world around us. It is the premise of the project that I present to you today. My project challenges almost two decades of research that confirms the presence of a statistical phenomena and practice within analgesic clinical trials that could have potentially invalidated their results … Pain or not, to produce a more accurate, working model of the world, it is necessary that the data that we obtain, the methods that we use to analyze them, and the conclusions that we draw, operate on valid assumptions and understanding. This is the power of combining mathematics and science; we’re able to unearth previously invisible relationships around us. There is so much left to operationalize, to reason, to understand. With this in mind, don’t forget to challenge your own assumptions as well as the assumptions of the world around you to bring forth a clearer understanding of the tricky things in our world. This is where the progress of science lies.