How Precise Can Obesity Medicine Get?Thursday, January 25, 2018
Another article in the 2018 JAMA special issue on obesity is one by Susan and Jack Yanovski and deals with the issue of using a precision or “personalised” approach to obesity prevention and management.
As we know, there are myriad factors that can lead to obesity (environmental, genetic, psychological, medical, etc., etc., etc.), with each patient having their own story and set of drivers and barriers.
Furthermore, we know that for any given treatment (whether behavioural, medical, or surgical) there is wide variation in individual outcomes.
So, being able to match the right treatment to the right patient, or even better, reliably predict a given patient’s response to a specific treatment could potentially improve outcomes and reduce patient burden and costs.
However, as the authors note, currently the only real predictor to treatment response is how well patients respond during the early part of treatment. Thus, we know that patient who lose a significant amount of weight during the first few weeks of medical treatment, tend to have the best long-term success in terms of weight loss.
However, this approach is also rather limited. In my own practice, I regularly see patients, who initially do well with behavioural, medical or surgical treatments, but eventually struggle, as well as patients who take longer to respond to a treatment before ultimately doing fine in the long term.
We are of course a long way off from having any kind of genetic or other testing that would reliably predict patient responses to treatment.
While this may become possible in the future, I am not holding my breath.
Not only is every patient’s story different, but the many factors that can determine response (societal, behavioural, psychological, biological, etc.) are almost endless and, moreover, can even vary over time in a given individual.
In fact, for most complex chronic diseases (e.g. diabetes, hypertension, depression, etc.), finding the best treatment for a given patient continues to be “trial and error”, or in other words, “empirical”.
Despite all the progress in genetic research, this has not really changed for most other complex chronic diseases like hypertension, type 2 diabetes, or dyslipidemia (despite a few rare but notable exceptions).
Moveover, as the authors point out, there are many other factors that will determine whether or not a given patient even has access to certain treatments, irrespective of whether or not that treatment is indeed the best treatment for them.
Currently, the best we can do, is to try to understand the drivers and barriers that each of our patients face and discuss with them the best treatment options available to them given their situation and circumstances.
Whether a more precise approach is ever likely (as the authors hope), clearly remains to be seen, but based on the progress made in for other complex chronic conditions, for which similar approaches have been tried, I am perhaps far less optimistic than the authors.
But, then again, I am happy to be proven wrong.