Go to the Algorithms

As in other disciplines, in recent years there has also been increasing interest in the issue of treatment personalization within the ambit of Diabetology.

Although everyone knows what personalizing treatment means in everyday clinical practice and defining approaches and procedures for its implementation is not an easy task.

The concept of personalized therapy involves an approach to clinical decision-making that is applied to every individual patient and has, as a prerequisite, an accurate characterization of that patient (phenotyping). As a technique, it involves applying knowledge, scientific evidence and common sense, as well as taking the realities of each individual patient’s circumstances into account. Its ultimate aim is to optimize therapeutic responses, whilst improving tolerability and compliance at the same time.

The issue is complicated, because it involves not only medical, but legal aspects as well. Medically, because of the extremes of personalized therapy, there is a risk that health care professionals will feel free to act without adhering to evidence-based medical practice. Legally, to an extent also in our own country, and more so in some others, it is risky, because any failure to follow guidelines assiduously can leave them open to litigation in cases where therapies fail.

Several tentative attempts at a more focused response to the problem have already been proposed (1,2,3,4)..

These proposals have, however, left many questions unanswered, largely because they have not tackled the problem at an individual level, and their attempts to “compartmentalise” patients have not been readily adaptable to the realities of our local situation.

As its background and mission, the Italian Association of Medical Diabetologists (AMD) considered it appropriate to respond to these new needs in Diabetology by developing a paper that addresses two aspects of the problem: the personalization of therapy, and therapeutic pathways aimed at rendering this approach useable (customized treatment pathways).

This paper has been developed, on the basis of previous publications in the literature from other authors (1-5) who have attempted to identify tools for characterizing patients with type 2 diabetes, and uses the latest guidelines from the Finnish Society of Diabetology as a background reference (6). The choice of the latter was motivated because of its innovative approach to ‘typing’ patients into the subcategories most commonly encountered in clinical practice.

The peculiarity of the AMD algorythms lies in the fact they use self-monitoring of blood glucose levels as a guide for selecting which therapies to prescribe. Patients are assigned a “phenotype”, according to the type and prevalence of their various daily blood sugar levels (fasting, pre-, and post-prandial), and this is used as a determining factor in guiding the choice of the most appropriate intervention.

In 2013, after nearly two years since the first edition (7), a third version of the algorithm was produced with major changes required by the introduction of new drugs onto the market, as well as updates to the therapeutic indications for others, and the publication of new guidelines (8) and international consensus on the topic (9-11). Furthermore, the new version was shared with the Italian College of General Practitioners (SIMG, Italian Society of General Medicine).

Once again produced in collaboration with the SIMG, the 2014 update presented major innovation mainly in the site structure and layout, which were improved and made more functional. In addition, new drugs were added and the available, most recent scientific literature directions were taken into consideration, the ones about the different kind of action of the available GLP1-receptor agonists (GLP1-RAs), thus suggesting the use of "short" acting GLP1-RAs (such as exenatide and lixisenatide) mainly when hyperglycemia is predominantly post-prandial, and that of "long" acting GLP1-RAs (such as albiglutide, exenatide LAR, and liraglutide) mainly when hyperglycemia is predominantly on fasting, or on fasting and post-prandial. Finally, the part on the methods for correct insulin administration and storage was updated, and the indications on the use of anti diabetic therapy in renal failure were modified, as well as the permitted combinations of anti diabetic drugs.

In 2016 we added an algorithm for the treatment of patients with previous acute coronary syndrome.

This edition consists of an overall upgrade of the previous algorithms in the light of the new data emerged in recent years on some drugs, again in collaboration with SIMG.

Whilst we are fully aware that the algorithm presented here neither covers all of the possible combinations encountered in daily clinical practice, nor meets the as yet unsatisfied management needs of patients with type 2 diabetes, we hope it will serve as a useful guide to choice during the medical decision-making process.

Il gruppo Terapia personalizzata
Alberto De Micheli (Direttore), Antonino Di Benedetto, Stefano Genovese, Raffaella Mattioni, Basilio Pintaudi, Gabriella Piscitelli. Edoardo Mannucci e Gerardo Medea (consulenti esterni). Alfonso Gigante (referente CDN)


Go to the Algorithms