Monday, 19 November 2018

Precision medicine cannot turn its back on emotions

Gustavo Tolchinsky

Two weeks ago in his post, Jordi Varela brought us a critical vision of precision medicine, which shows us a somewhat less triumphalist scenario than expected. Precision medicine was born with the intention to give better answers to spaces of uncertainty regarding clinical problems from different areas of medicine such as genomics or big data. Linking with this theme, we shouldn’t forget that even being more effective than what has been proven at the moment, we still depend on the human factor to reach the best possible result. When it comes to decision making, multiple factors are involved. There is a rational part, which we believe we control, but above all there is an emotional part that ends up directing us towards that scenario in which we believe we are going to be more comfortable in.

Montori points out that the tools he uses in decision-making only serve as a support, aware that the emotional factor needs to be guided with the least abstract information possible. In addition to that, our verbal communication carries more than one message: the explicit and the symbolic. The explicit derives from the literal meaning, what we call Verbatim, very limited and of an exact, unequivocal definition, and doesn’t give rise to mistakes of understanding by itself. The symbolic is that which derives from the context, the interpretation and the value of those who understand it in their own way, what we call it Gist.

In the case of oncology, decision-making is often so complex, even for a doctor himself, that Cancer Committees are called upon, to gather rational information and make the best decision for the patient. Precisely for that reason, I suppose that Jordi Varela dedicated a post, in July 2017, about the limitations that can arise from the decision making in oncological patients, since the expert committee doesn’t rely on the “expert on himself”, on the patient and his preferences.

The field we move in goes between offering the patient the best result and what the patient understands is best for him. I had to read the above phrase twice to make sure that it says what I realy mean, and as to set an example we could look at what happens with contralateral prophylactic mastectomies in the United States. Contralateral prophylactic mastectomy has very specific indications, which are based mainly on two factors, a family history and being a carrier of BRCA 1 and 2.

On summer of 2017, STATnews published the article " Why a growing number of women with breast cancer are choosing double mastectomy?", Based on a 2016 Annals of Surgery that published the data of follow-up of Contralateral Prophylactic Mastectomies (CPM) in nearly half a million women in the United States. In the period studied, which goes from 2002 to 2012, the CPM tripled, going from 3.9% of the interventions to 12.7% without improving overall survival regardless of age or hormonal receptors. Moreover, performing CPM is four times more likely in the US than in South Korea or Berlin.

When analysing the causes of this increase, the researchers warn that this growing trend cannot be attributed to the Angelina Jolie effect, since she made her intervention public in 2013. Among the most determining factors is the decision-making model, like other publications confirm, and fear or anxiety of patients of a second breast tumour.

As we said before, we are moving between best evidence and what the patient finds evidently best for her. Much progress has been made in offering the guarantees of better results by individualizing the risk and then we just stumble right into a huge Iceberg in the middle of the Caribbean. Patients, in this case, seem to choose much more aggressive treatments that the ones actually indicated. According to the authors, the patients who chose CPM didn’t meet criteria for it to be recommended. In later studies, a greater preference for white women versus black women to undergo MPC has been identified. This was finally attributed to a lower perception of risk of a new tumour in the contralateral breast by black patients.

As for decision making, another author, Shoshana M. Rosemberg of the Dana-Farber Cancer Institute, has published a study on Annals of Surgical Oncology in which she indicates that the more weight the patient has in the decision, the more likely that the choice would be a CPM up to 3 times more than when there is a shared-decision of doctor and patient. Here there are factors linked to the surgeon himself that due to unawareness, or because, as according to the study, only between 5  to 20% talk about surgical options, leaving the patients to choose with their prejudices and their fears. The same author, in another editorial, summarizes the results of several research groups that compare satisfaction data, quality of life, and ... Surprise! There are only some minor differences later, depending on the type of intervention. So ... What is the best? And for whom?

One could deepen the nuances of the subject, but at this point, the factor on which we can influence and must insist on is the role of professionals. Surely in the case of the MPC in the US there are more factors that trigger those figures, given that in other countries these figures are not given and I very much doubt that it’s only due to communication, but in the US they have seen that the role of the doctor manages to clearly modify that trend and therefore is a powerful tool.

When we talk about precision medicine, we are referring to the ability to offer the most appropriate intervention to obtain the best result in terms of survival, complications and cost-effectiveness for each patient profile based on their biometric characteristics. It’s clear that "throwing the cards" with raw data (verbatim) is not what the person looking at it sees from their own construct (gist). For patients to decide on their health, we need our ability to empathize, discuss with assertiveness and understand the preferences of our patients, which will lead us to calibrate even better precision medicine that comes from the world of data and not from emotions and than avoid possible over-treatments.

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