The more I am involved in the study of various biomarkers, the more convinced I become that they are not ever going to achieve what is hoped for them.
Some medical providers look at various biomarkers like blood pressure, lab values, and the like and determine the patient is sick or not based solely on whether or not the number is above or below “normal ranges.” Many very astute medical providers interpret how these numbers reflect what is going on in the body.
But I have been observing a phenomenon that medical scientists don’t really like to talk about; that their “novel” or “new” biomarker studies may very likely have an inherent bias. You see, when you study biomarkers in a population, you spend a lot of time observing those patients. You also get exposed to their cohort more. As any capable scientist will tell you, larger populations leads to more significant conclusions. As any clinician will tell you, there is no substitute for experience and number of patient contacts.
But this bias may have a positive effect on biomarkers for the purpose of patient care. Some of the researchers I have interacted with have studied their respective biomarker for years, sometimes decades. Anytime they publish a study on their effectiveness the results are usually positive for the marker. They often highly select patient populations to prove their point. Detractors often select the worst possible cohorts to raise questions of effectiveness.
But both of these parties seem to develop an exceptionally accurate intuition in identifying and treating their respective patients.
What is basically demonstrated is it is not the biomarker that is effective, it is the act of studying the biomarker that makes the clinical scientist a more effective clinician. In layman’s terms, it is the journey not the destination that is really important.
I was wondering if clinical trials share a similar bias.
If this is actually the case, neither diagnostics nor treatments will be better for “non-experts,” which is actually the point of trying to verify their usefulness.
Oh well, at least we can still use the studies to convince others to pay for various tests and treatments.