[Current views on the treatment of insulinoma].

Relevance: Insulinoma is the most common hormonally active neuroendocrine tumor (NET) of the pancreas. In recent years, there has been a trend towards an increase in the incidence of NET especially insulinoma.

Aim: Summarizing and analyzing current data on various approaches to the treatment of insulinoma. Our review includes a comprehensive assessment of the advantages and disadvantages of currently available insulinoma treatment methods in comparison with past experience, as well as a review of promising methods that are not currently widely used.

Materials and methods: Analysis of literature from such databases as scientific electronic library elibrary.ru, Pubmed, Google Scholar, MedLine, Scopus and Web of Science.

Results: The most common treatment for insulinoma is surgery. For patients with high operative risk, alternative methods such as alcohol ablation, radiofrequency ablation, and tumor embolization may be used. Medications include the use of somatostatin analogues, diazoxide. The literature describes the potential benefit of the use of beta-blockers, phenytoin, glucagon, however, in clinical trials, these drugs have not demonstrated a significant effect. For the treatment of malignant and metastatically advanced insulinoma, targeted therapy (primarily Everolimus), chemotherapy, as well as embolization (including chemoembolization, radioembolization), radiofrequency ablation (RFA), microwave ablation and cryoablation, ultrasound ablation (HIFU), laser ablation, brachytherapy, irreversible electroporation are used.

Conclusion: The study of new drugs is an important task for scientists, among medications the most promising are new generations of somatostatin analogues, targeted drugs and chemotherapy drugs. The rare frequency of insulinoma makes it difficult to conduct randomized controlled trials and prospective studies. That is why physicians and scientists need to maintain close contacts with each other and take into account the experience of treating each patient with such disease, which will help develop effective treatment algorithms in the future.