Not all existing therapies for type 2 diabetes provide similar glycemic control for every affected patient; with a few notable exceptions, how different responses to therapy relate to specific variations within identifiable subgroups of patients remained, and remains, largely unexplored.

Also on the basis of current uncertainty, the Diabetes Care Editors’ Expert Forum delivered their reflections to help physicians personalize diabetes care (1). Apart from the many given reasons for the need to decode the joint position statement by the American Diabetes Association and the European Association for the Study of Diabetes (EASD) (2), the list could also include recognition of the difficulty of implementing effective personalized therapy in a clinical setting, the need to enlarge consensus, and the panoply of diabetes drugs, which may also imply the “personalization of a niche” for each different antihyperglycemic agent within the 12 drug classes on the U.S. market. However, multiple treatment guidelines, algorithms, and goals periodically released to improve guidance may also enhance uncertainty (3).

Personalized medicine should be based on evidence rather than clinical impression; unfortunately, it still lacks scientific evidence. For example, personalization of HbA1c target for diabetic individuals is paramount as the aggressiveness of any therapy is ultimately based on how low the target is set. A good example of this challenge is the recent INTERVAL trial, which aims to assess the feasibility of setting and achieving individualized targets in elderly (aged 70 years or older) type 2 diabetic patients (4). Although investigators from seven European countries were free to set individualized treatment targets on the basis of age, baseline HbA1c, comorbidities, and frailty status, the mean investigator-defined individualized HbA1c targets were around 7.0%, substantially lower than expected for that elderly population. To our knowledge, this is the only controlled study trying to apply the philosophy of personalized medicine in type 2 diabetes.

Human beings tend to revert to the familiar: given the paucity of pragmatic aid (for example, Web-driven algorithms that estimate the target with simple parameters or tailor pharmacological therapy on the basis of clinical features [5]), personal decisions tend to be conservative and uniform to what is familiar and known. A lesson learned is that physicians need practical help to feel safer with consistent recommendations.

No potential conflicts of interest relevant to this article were reported.

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