Challenges Faced by Clinicians in the Personalized Treatment Planning: A Literature Review and the First Results of the Russian National Cancer Program.

Autor: Shegai PV; Federal State Budgetary Institution National Medical Research Radiological Center of the Ministry of Health of the Russian Federation, Kaluga Region, Koroleva Str. 4., Obninsk 249036, Russia., Shatalov PA; Federal State Budgetary Institution National Medical Research Radiological Center of the Ministry of Health of the Russian Federation, Kaluga Region, Koroleva Str. 4., Obninsk 249036, Russia., Zabolotneva AA; Pirogov Russian National Research Medical University, Ostrovitianov Str. 1, Moscow 117997, Russia., Falaleeva NA; A. Tsyb Medical Radiological Research Center-Branch of the Federal State Budgetary Institution National Medical Research Radiological Center of the Ministry of Health of the Russian Federation, Zhukova Str. 10, Kaluga Region, Obninsk 249031, Russia., Ivanov SA; A. Tsyb Medical Radiological Research Center-Branch of the Federal State Budgetary Institution National Medical Research Radiological Center of the Ministry of Health of the Russian Federation, Zhukova Str. 10, Kaluga Region, Obninsk 249031, Russia., Kaprin AD; Federal State Budgetary Institution National Medical Research Radiological Center of the Ministry of Health of the Russian Federation, Kaluga Region, Koroleva Str. 4., Obninsk 249036, Russia.
Jazyk: angličtina
Zdroj: Critical care research and practice [Crit Care Res Pract] 2021 Sep 23; Vol. 2021, pp. 6649771. Date of Electronic Publication: 2021 Sep 23 (Print Publication: 2021).
DOI: 10.1155/2021/6649771
Abstrakt: Advances in cancer molecular profiling have enabled the development of more effective approaches to the diagnosis and personalized treatment of tumors. However, treatment planning has become more labor intensive, requiring hours or even days of clinician effort to optimize an individual patient case in a trial-and-error manner. Lessons learned from the world cancer programs provide insights into ways to develop approaches for the treatment strategy definition which can be introduced into clinical practice. This article highlights the variety of breakthroughs in patients' cancer treatment and some challenges that this field faces now in Russia. In this report, we consider the key characteristics for planning an optimal clinical treatment regimen and which should be included in the algorithm of clinical decision support systems. We discuss the perspectives of implementing artificial intelligence-based systems in cancer treatment planning in Russia.
Competing Interests: The authors declare no conflicts of interest regarding the publication of this article.
(Copyright © 2021 P. V. Shegai et al.)
Databáze: MEDLINE
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