The Danger in Assumptions

In an age where practically any information, data, or study can be found through just the click of a button, there are new precautions that patients and doctors alike must take. The main responsibility of a reader is to take what has been read, correctly analyse it, and interpret the information. Doing so is very difficult due to the implications of the information; it can be confusing to understand, whether due to language use or complexity. Information from preventive and personalised medicine is even harder to interpret because it is highly case specific. Medical science is far from being black and white, and thus the art of medicine is understanding the grey. For doctors, the vast amount of new information coming to them through journals and meetings is compounded further by the flood of informal data coming to them through television and online. These pieces of media are the same sources accessible to those without formal medical training, i.e. patients. There are an overwhelming number of situations in which information taken from any of these sources is unfortunately misinterpreted, leading to costly consequences.
An illustration of this point presents when a 52 year old woman is diagnosed with pancreatic cancer. The information of the diagnosis travels to her dentist, who had read previous studies about the potential linkage between the oral bacteria Porphyromonas gingivalis (P.gingivalis) and pancreatic cancer. Indeed, there are several recent studies showing that oral bacteria may have a role in the development of more severe diseases. According to Julie Jacob in Study Links Periodontal Disease Bacteria to Pancreatic Cancer Risk, patients with the presence of P.gingivalis in their oral microbiome have a 59% greater risk of developing pancreatic cancer compared to patients without the bacteria.[1] The dentist relays the information from a given study to his patient, but without the precise use of the phrase “greater risk”. He instead implies that the P.gingivalis has caused the development of the patient’s cancer. It is vital to distinguish the difference between disease association and disease causality. The critical point of error in this situation is when the dentist mistakenly thinks that there have been studies that prove P.gingivalis as a cause of pancreatic cancer. However, there is yet to be literature published addressing the causation link. Due to this oversight, the dentist and the patient believe they need to change the treatment plan for the disease to account for her elevated levels of P.gingivalis.
The patient approaches her surgical oncologist and requests to have the treatment plan for her cancer changed because of the misconception that her P.gingivalis caused her cancer. The surgeon does not recognise the error made by the dentist and uses the information to alter the patient’s treatment. Another error made in the woman’s case is the assumption that the P.gingivalis bacteria is present in the pancreas without any concrete evidence. Further, it is not even known which isotype of P.gingivalis bacteria the woman has. Type 2 P.gingivalis bacteria is at high risk of association to disease, contrary to type 1 which has rarely been associated with disease. If even this small piece of information had been known before jumping to conclusions, the P.gingivalis could have been fully invalidated as a cause of cancer for the woman in the aforementioned case.
Generally, the issue is seen repeating itself in history: readers of scientific literature are incorrectly interpreting the language and therefore making false assumptions about the studies. In most situations, readers, without sufficient skills, are skimming articles where an association between two findings are made. Rather than understanding the association, they will automatically assume that there is causation between the findings. This is incorrect because association and causation do not express the same relationship, and cannot be used interchangeably.
The problem of jumping to false conclusions is becoming more and more prevalent with each passing day. With easy access to social media, there is a risk that readers will skim information and for example, read hypotheses and instead take them as fact. This is especially happening as genetic profiling and personalised medicine become more accessible to the general public. While there is growth in accessibility to information, there is not equivalent growth in education about how to interpret and use this information.
A perfect example of this phenomenon is in genetic tests, such as 23andMe, available at CVS drug stores at very affordable prices. 23andMe gives test users access to over 65 personalised genetic reports by looking at saliva samples. The reports tell patients whether they carry genes that are associated with several illnesses such as cystic fibrosis and sickle cell anaemia. In these cases, the test will tell patients if they are a carrier of the gene, not if they have the illnesses. This means that the patient could pass the gene onto their children, however they may not show symptoms of the disease. A patient who gets their results and sees that they do, in fact, have the sickle cell anaemia gene could use this information in many ways. The patient could effectively take the data into consideration as they come closer to the point of having children, who could possibly get the disorder passed down to them. On the other hand, it is key to note that these tests specifically do not tell patients if they have said illnesses; a multifold risk does not mean that a patient has the disease. Simply stated, tests like 23andMe tell users whether or not they are more likely to develop a specific disease than the average person.
When patients assume that the risk factor is equivalent to actually having the illness, there are numerous consequences. According to the chair of a roundtable discussion, Dr. Burke, “there is insufficient evidence at this point to claim clinical benefit from personal genomics and that there may be reason to be concerned about potential harms, such as cascade effects, false positive results, false reassurance, or about relatively trivial risks taking up practitioners’ time”.[2] To elaborate on one of Dr. Burke’s points, customers may request tests to be performed that are unnecessary and serve no purpose. Beyond serving no purpose, running nonessential tests wastes time of medical professionals and space available in medical facilities. In a similar manner, when customers jump to conclusions, they will often waste money to get to the bottom of their “diagnosis.” In reality, the test is not a diagnosis, but just a piece of information. There is no way nor need to do anything with the information until it becomes scientifically found that there are signs or evidence of the disease in one’s body. Lastly, there are possible emotional responses to genetic testing. Learning about the multifold risk a patient has for a disease can cause stress and anxiety about the future. Unless the stress is productively used to do research for the future, it is unnecessary and, in some cases, harmful. There have been numerous studies examining “actual or potential psychological effects of receiving direct-to-consumer genetic testing results. Studies posing hypothetical scenarios to participants suggest the potential for increased psychological distress and anxiety in response to positive test results” says Roberts and Ostergren. It was found in one study that “40% of participants anticipated feeling more worried and anxious after seeing their genetic profile, with higher levels of disease risk associated with greater anticipated worry and anxiety”.[3] In conclusion, as genetic tests like 23andMe become increasingly popular and more easily accessible it is essential to inform people on how to read these tests and what the data really means. Educating people about the difference between a multifold risk and a diagnosis is needed in going forward with the spread of tests like 23andMe. Without knowing what the information given by genetic tests means, the profile that a patient receives cannot be used as a resource and is therefore not valuable to the patient. The best way to get value from the results is to understand what the genetic profile is presenting and possibly talking through the results with a healthcare professional.
Whether it be a doctor or a customer that is inaccurately interpreting data and language in literature and genetic tests, the results are the same. These misunderstandings lead to increased levels of stress and anxiety, and possibly an increased amount of wasted medical resources and money on further research and treatment for the patient. The risk grows even stronger as health care professionals misinterpret genetic information; patients will naturally take medical information coming from a professional more seriously. In the case of the woman with pancreatic cancer, many inaccurate conclusions were jumped to by the dentist. He falsely believed that the oral bacteria was living in her pancreas. He also assumed that her cancer was the same as the one that was studied in all of his readings. In actuality, after performing the necessary tests, she had a different form of pancreatic cancer than the one that was actually linked to P.gingivalis.
The risk of jumping to further conclusions is also prevalent in the misinterpretation of data or language. Another possibly life-threatening risk to making assumptions about data and language is that the treatment plan for a patient may be altered. The woman with pancreatic cancer unnecessarily discussed treatment plans that targeted bacteria with her surgeon.
In the future, as access to genetic profiling increases and more scientific papers are published, all levels of scientific readers need to be more cautious and educated. Being informed and interested in scientific information can be beneficial, but only when the material is fully understood. With access to research and gene make-up, comes the responsibility that information is accurately interpreted and utilised.

  1. Julie A Jacob,. “Study Links Periodontal Disease Bacteria to Pancreatic Cancer Risk.” Jama, vol. 315, no. 24, 28 June 2016, pp. 2653–2654.
  2. Institute of Medicine (US) Roundtable on Translating Genomic-Based Research for Health. The Value of Genetic and Genomic Technologies: Workshop Summary. Washington (DC): National Academies Press (US); 2010. 4, Genomic Profiling.
  3. J. Scott Roberts, and Jenny Ostergren. “Direct-to-Consumer Genetic Testing and Personal Genomics Services: A Review of Recent Empirical Studies.” Current genetic medicine reports 1.3 (2013): 182–200.

About the Author

Serena Laing, USA
Originally from the Boston area, Serena now lives in Minnesota where she is completing high school. Next year, she plans on attending Tufts University, where she will study chemistry and food systems. When Serena has free time, she enjoys hanging out with friends, spending time outdoors hammocking, or playing with her dog.

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