
Multiple myeloma (ММ) accounts for about 10 % of all hematologic tumors. The diversity of symptoms and variants of clinical course as well as a broad range of potential complications of both the disease itself and chemotherapy, indicate the need for further improvement of personalized treatment principles. The use of medical calculators (MC) integrating clinical, laboratory, and genetic data is becoming an important part of modern medical practice. The application of MC contributes to more credible assessment of the individual prognosis. Besides, current interest is attached to clinical decision support systems (CDSS) designed for the optimization of decision making. This paper reviews the major digital tools employed by professionals at all stages of management of patients with MM. They include laboratory diagnosis, disease staging, comorbidity assessment, complication risk, drug dosage calculations, and drug–drug interaction analysis. Special emphasis is laid on CDSS considering clinical and genetic characteristics of patients to ensure the optimal decision making on the treatment programs with regard to efficacy and safety. This paper provides practical recommendations on the application of the above tools in everyday clinical practice and contains the links to available online calculators and digital services. The implementation of MC and useful digital services facilitates better clinical outcomes, improves quality of life of patients, and optimizes healthcare resources as it contributes to efficacy and safety of MM treatment.
медицинский калькулятор, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, множественная миелома, система поддержки принятия врачебных решени, RC254-282
медицинский калькулятор, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, множественная миелома, система поддержки принятия врачебных решени, RC254-282
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
