Scientific “Ultimatums”

The seemingly overwhelming problem with mass consumption of science is the idea that science can find the be-all and end-all of human problems. Science, in conjunction with engineering, can develop technologies to ease life. Science can develop pills to make us work better, run further, and think smarter. And, most importantly, science can cure all ailments in all people, and make death impossible. The general public, and even some scientists, lose perspective when faced with the most recent “miracle breakthrough” and, ignoring rationality and realism, conclude that yes!, finally!, this is the product that will change humankind as we know it! Journalists can only take some of the blame for this – they, like scientists, need to publish or perish. A majority of the blame, though, can be placed on the shoulders of those who chose what research should be funded. Buzzwords like “novel” and “exciting” are thrown around in grant applications as through no other adjectives exist, and it makes logical sense that journalists with minimal scientific training would follow the trend – if the scientists find these ideas exciting, they absolutely must be “transformative,” “groundbreaking,” and “revolutionary.”

Personally though, this medical overhype in scientific journals and newspapers is not terribly worrisome; as mentioned in an article by Julia Belluz, almost all of these “miracle” drugs are not available to the public. She mentions that the worst result of this practice is the creation of hope in the desperate, and while hope is important for healing and mental health, a loss of hope cannot hurt a patient or group of people to the degree that a non-FDA approved, pseudoscience “cure” can. Just yesterday, my mother – a highly trained operating room nurse - called me to ask me to research “MMS drops,” after being unable to find any information on the FDA website. Her friend’s husband, an injured, uninsured immigrant, was given these drops by a “friend” for some back pain a couple of weeks ago, and has been experiencing chest pain since taking them. For those of you that are unfamiliar, MMS, or miracle mineral supplement drops are a toxic solution of NaClO₂, loosely equivalent to dilute bleach. These drops have been falsely proclaimed as a cure for HIV, malaria, hepatitis, flu, common colds, autism, acne, cancer, and much, much more, without a single clinical trial. However, due to a few anecdotal reports and a book by Jim Humble, in conjunction with sale of the product as a “water purifier” to circumvent medical regulations, countless individuals have been throwing their money, hope, and health into a product that realistically causes renal failure, nausea, vomiting, and airway corrosion even at small doses. Countless products like this exist as unregulated “miracles,” and countless people buy into the anecdotal “evidence” in vain hopes for cures that science cannot yet provide.

Instead of focusing on the relatively harmless effects of the failure of scientifically backed – and publicly unattainable – products, the “medical” hype that should be vehemently and much more commonly disputed are products that, in the end, were made to make a profit off of the scientifically ignorant, without fear of consequences.

The Scientific Method Matters Much Less than it Should

With science as my calling and profession, I prefer to think of the scientific (and medical) community, in a positive light.  After all, I along with countless grade-schoolers, learned the scientific method as the gold standard for how we learn and know, well, everything.  As children, the concept of scientific evidence is taught with certainty.  Our readings and countless other examples prove otherwise, of course.

My own irrational faith in the scientific approach caused me to first be taken aback by the statement that Evidence-Based Medicine was really only brought into practice in the '80's.  Yes, the 1980's.  That means we landed on the moon more than 10 years before we thought it would be a good idea to base health care on experimental and reproducible data.

True evidence-based practices need to be receptive of every new piece of evidence to prevent unsupportable biases from controlling common practices.  However, when I realize how many careers and pensions rely on the status quo being upheld, I stop being surprised with blind refusal to greet new evidence with anything other than torches and pitchforks.

Even after the paradigm shift to Evidence-Based Medicine, bias is keeping a dictatorial role over the supposed democracy of the scientific method.  I was immediately reminded of the story of Dr. Barry Marshall, now lauded as Nobel Laureate.  The whole saga of proving a pathogenic cause of stomach ulcers, finally accepted after Dr. Marshall went all medieval on himself and drank an H. pylori soup, is nicely summarized in the video below.  His story underscores the irrational and unnecessary steps scientists/medical professionals must take to overcome bias in the field.  At the time, "Suggesting that ulcers were caused by anything other than stress was career suicide".  This, when the first evidence for a role of bacteria in stomach ulcers was put forward in 1886 by a Polish scientist Dr. W. Jawarski.  The mere fact that his work was published in Polish served as a major stumbling block, but it remained only a 'curiosity' even as evidence continued to grow.  Dr. Lykoudis was thanked for his (successful) treatment of ulcer patients with antibiotics with a rejection of his manuscript and a fine.

In the end, the shift in scientific consensus was not caused by scientific rigor or diligent statistics. It required a visceral, human story of Dr. Marshall putting himself on the line, and turning himself into a case study, where traditional experiments failed.

But when I think about it, this whole story is unsurprising.  Statistics are numbers on a page, no matter how valid they may be.  The same holds true for human interest stories: we can hear that a natural disaster has claimed thousands of lives, but until we hear the personal story of one struggling family.  Yes, rigorous and ethical use of statistics in reporting scientific findings is crucial.  However, often it often has zero impact on how well new ideas are accepted, as seen in Dr. Marshall's vomit-laden path to Stockholm.

Publication bias in my own research

Unbiased research is the “gold standard” of science and aims to prevent scientists from achieving “self-fulfilling prophecies” and deceiving themselves into believing an idea or hypothesis is true when it is actually not true or completely due to random chance. Properly applied statistics, experimental design, replication, among other methods are ways to prevent bias from happening, but preventing bias is actually against our normal human nature as discussed in Dan Ariely’s TED Talk.  Additionally, the many forms that bias takes whether it be known or unknown to the person performing the experiments can confound studies and/or hinder scientific progress. Panucci et al. (2010) reviews numerous types and examples of bias in tangible research situations that most biomedical and/or clinicians will find themselves involved in during their careers, whether it be conducting research with such biases or reviewing it. Even though there are many types of research bias, I think that one of the major forms that I currently face and/or am frustrated with as a fourth year graduate student is publication bias, which in my view is the preference of publishing positive results and/or the inability to publish data that goes against the current paradigm of a particular field.

Recently, I designed an experiment to analyze the cytokine response in nonhuman primates with malaria using two different species of malaria parasites. I went through the standard process of generating my samples, developing and designing the protocol, etc. Then, I proceeded to perform the experiment. In one set of samples, I found that Interferon gamma, a hallmark cytokine in malaria involved in immune responses, was upregulated as we had predicted. In my other set of samples, the cytokine was undetectable. I immediately thought, “How could this be? The assay must be wrong because this has been seen before and is found in all malaria infections from mice to humans to monkeys.” Like a good student, I proceeded to validate the data on a different platform and confirmed my results, which took about three more weeks considering the need to standardize yet another assay, place orders, etc. Whenever I presented the results to my advisor, he or she responded, “I am not surprised; I’ve seen this before.” I was shocked because in the literature, this cytokine is always reported, and my advisor had even advised me to use this cytokine as a “calibrator”. However, it turns out that this cytokine has a temporal dynamic during the infection so if one misses a certain time frame, the cytokine may not be detectable. To my knowledge, not a single paper addresses this observation, and this is largely due to the need to have a positive result to get the data published. Obviously, it is much more interesting to talk about an increase in a particular cytokine than no change at all. Furthermore, the dogma and published literature are skewed to presenting this cytokine as central in malaria so if it is not present in detectable levels, researchers and reviewers begin to question the integrity and quality of the experiment and samples.  

            Publication bias thus caused me to lose time in finishing this component of my project. If the literature was not biased based to current opinions and also by the need for a positive result, I and others likely in my situation would not be surprised by such results and spend time triple checking all aspects of an assay, repeating results too many times, etc. Publishing negative results and results that may go against current understanding or dogma should be welcomed in science and are ultimately what will help current scientists address new and interesting questions in novel way. Of course, this opinion is qualified by the fact that the experiments are designed appropriately and replicated.