Background. The introduction of artificial intelligence (AI)-driven computer vision programs (CVPs) into medical diagnostics has imposed stricter requirements on the quality of input photographic images. Imaging conditions vary significantly across medical fields, necessitating the establishment of field-specific reference ranges for photometric and textural parameters to ensure that AI models maintain reproducible diagnostic accuracy. A systematic analysis of the causes of erroneous classifications by CVPs is essential for their clinical application and further improvement. Objective: To develop a generalized methodology for analyzing the causes of classification errors in photographic images by processed by AI-driven CVPs. The proposed methodology enables the establishment of reference ranges for photometric and textural parameters for specific medical imaging applications, as well as the development of criteria for excluding images with anomalous values when during preprocessing in medical software systems. Material and methods. The methodology includes eight sequential stages. A dataset of photographic images verified by histological and dermatoscopic examinations was compiled, classified using the CVPs, and assigned to either of the four standard categories (true positive, true negative, false positive, and false negative). For each photographic image, thirteen photometric and textural quality metrics were calculated, including: brightness, contrast, sharpness, entropy, high-frequency saturation, proportions of overexposed and underexposed pixels, and mean values and standard deviations of the color channels. Systematic between-group differences were identified using one-way ANalysis Of VAriance (ANOVA), Welch's test, and Spearman's rank correlation analysis. The image regions that determine the neural network decision were localized using explainable AI techniques. Reference ranges were established from the characteristics of correctly classified photographs (true positive and true negative categories), defined as intervals of [mean − 2 std; mean + 2 std]. The effectiveness of parameter normalization was assessed by the improvement in accuracy, sensitivity, and specificity. Results. The proposed methodology was tested using the Derma Onko Check and Melanoma Check CVPs as an example. Its application allowed statistically significant intergroup differences in photometric and textural parameters to be identified (F=13.50–39.31, p<0.001 for the main metrics of the one-way ANOVA; F=5.41–72.29, p<0.001 for the conclusion category by the two-way ANOVA). The analysis confirmed that the observed patterns were independent of the specific CVP used (p=0.39–0.96 for the program factor; p=0.15–0.92 for the interaction effect). Multivariate analysis further demonstrated significant differences among classification outcome groups based on the combined set of image quality metrics (Wilks' lambda 0.639; F=10.37; p<0.001) and established key independent predictors of classification errors through logistic regression (Fast Fourier Transform blur: odds ratio (OR) 3.08; sharpness: OR 0.31; proportion of overexposed pixels: OR 1.64). Reference ranges were established for brightness (0.467–0.942), contrast (0.066–0.333), entropy (3.626–5.590), and high-frequency saturation (23.82–56.48), along with critical thresholds for image exclusion from inference (proportion of overexposed or darkened pixels greater than 55%). The use of a targeted preprocessing module for normalization of deviating parameters falling outside the reference ranges ensured an increase in diagnostic accuracy by +0.014–0.017 in absolute values across all studied CVP configurations, with a predominant increase in specificity (+0.015–0.019). Conclusion. The proposed methodology for analyzing the causes of erroneous classification of photographic images by AI-driven CVPs was tested on the example of Derma Onko Check and Melanoma Check using a limited dataset (460 photographic images representing two morphological subgroups of melanocytic skin tumors). The extension of the methodology to other areas of medical imaging (ophthalmology, histology, or ultrasound diagnostics), where image acquisition conditions differ substantially, will require validation on representative multicenter datasets with recalculation of parameter reference ranges to reflect the imaging specifics of each domain. The integration of modules for detecting and excluding images with abnormal metric values constitutes a natural practical implication of the proposed methodology and ensures a reproducible increase in the clinical accuracy of AI-driven CVP systems.
Objeсtive : To evaluate the direct medical costs of treating multiple myeloma (MM) patients with daratumumab and its Russian biosimilar using subcutaneous (SC) and intravenous (IV) administration routes, while considering the patients’ body weights. Material and methods. The targeted patient population and their weight characteristics were determined according to the MM patients registry at the Hematology Center of Moscow Botkin Multidisciplinary Scientific and Clinical Center. As of February 16, 2026, it included 329 patients treated with daratumumab or its combinations. The costs of a year-long course of therapy were calculated, including the following treatment strategies: daratumumab alone (both SC and IV), a biosimilar alone, or a combination of the two, depending on the patient's weight. Furthermore, cost-minimization and budget impact analyses were conducted within a 1-year timeframe for the considered treatment strategies. These analyses evaluated the direct medical costs of daratumumab therapy based on the dosing regimens outlined in the clinical guidelines and the summary of product characteristics. Results . The cost-minimization analysis revealed that treatment strategies for MM patients using daratumumab biosimilar alone or in combination (for patients weighing less than 88 kg) with the SC route of the original drug (for patients weighing 88 kg or more) are the most cost-effective. The estimated costs are 4.28 and 4.18 million rubles, respectively, in the first year of treatment and 2.43 and 2.37 million rubles in the second and subsequent years. Meanwhile, solely IV or solely SC administration of the original daratumumab results in a 14.2% and 19.1% increase in costs, respectively, reaching 5.10 and 4.89 million rubles in the first year of therapy and 2.90 and 2.78 million rubles in the second and subsequent years. Also, combining IV and SC forms of the original drug increases costs by 7.8%, reaching 4.62 million rubles in the first year of therapy and 2.62 million rubles in subsequent years. The budget impact analysis revealed that using a daratumumab biosimilar for all patients who received treatment in 2025 would result in total annual savings for the healthcare system of between 701.32 and 1,714.83 million rubles. Conclusion . Expanding the use of the daratumumab biosimilar is cost-effective, compared not only to the IV form of the original drug but also to the SC form, as well as their combination.
Objective : To conduct a pharmacoeconomic evaluation of the triple beclomethasone/formoterol/glycopyrronium fixed-dose combination (FDC) for the treatment of patients with moderate and severe chronic obstructive pulmonary disease (COPD) in healthcare institutions of the Moscow Region, Russia. Material and methods . A pharmacoepidemiological analysis was conducted using data from multiple levels of medical care for patients with COPD in the Moscow Region, including records data from the Territorial Fund for Compulsory Health Insurance (TFCHI) and data on subsidized drug provision. To characterize the frequency and structure of inpatient and outpatient care for COPD, a frequency analysis was performed. Direct costs of COPD pharmacotherapy were assessed, including expenditures associated with triple FDCs. In addition, a budget impact analysis was carried out to evaluate the provision of triple FDCs in a single delivery device. Results . During the analyzed period, 23,583 COPD patients received inpatient care and 7,314 received outpatient care, with total expenditures of 703,329,560 and 251,189,103 rubles, respectively. Analysis of subsidized drug provision showed that 757 patients (4.2% of all patients receiving COPD therapy) were treated with one of three triple FDCs: beclomethasone/glycopyrronium bromide/ formoterol, budesonide/glycopyrronium bromide/formoterol, or vilanterol/umeclidinium bromide/fluticasone furoate. Budget impact analysis demonstrated that two triple FDCs (budesonide/glycopyrronium bromide/formoterol and beclomethasone/glycopyrronium bromide/formoterol) were associated with identical costs: 2,763.20 rubles per month and 33,158.40 rubles per year. Treatment with the vilanterol/umeclidinium bromide/fluticasone furoate combination was associated with higher costs. Conclusion . Use of triple FDC of beclomethasone/glycopyrronium bromide/formoterol may help improve compliance to therapy among patients with COPD and is associated with lower costs for the Moscow Region healthcare system. This treatment approach is clinically and economically feasible.
Vulvar cancer, a relatively rare gynecologic oncology condition, remains a pressing issue given its late diagnosis and the significant decline in quality of life following surgery and chemoradiation. A promising approach to improving the quality of medical care for patients with vulvar cancer is the implementation of prehabilitation and rehabilitation programs. Prehabilitation is a set of measures aimed at improving the patients’ physical function and mental state to mitigate the severity of deconditioning, improve treatment outcomes, and enhance their quality of life. Studies conducted to date show that multimodal prehabilitation programs have a positive effect on patients’ functional capacity and both short- and long-term treatment outcomes. The introduction of prehabilitation programs into clinical practice may be an important, undervalued resource for improving the quality of medical care for patients with gynecologic oncology. This review, based on evidence-based medicine, presents current approaches to prehabilitation for patients with vulvar cancer. Particular attention is paid to studies that are currently underway, as their results may advance our understanding of the role of prehabilitation in improving outcomes in gynecologic oncology in real-world clinical practice.
Background . Metastatic and unresectable cutaneous melanoma (MM/uRCM) is an aggressive malignancy associated with high mortality due to its pronounced metastatic potential. Immune checkpoint inhibitors are used to treat MM/uRCM in the Russian Federation. These inhibitors include nivolumab and prolgolimab, which block the programmed cell death 1 (PD-1) receptor. However, there are no direct comparative data on their clinical and economic efficacy and safety as monotherapy, which complicates optimal therapeutic decision-making. Objective : To evaluate the clinical efficacy and safety of prolgolimab versus nivolumab in MM/uRCM treatment and to conduct cost-effectiveness analysis based on data obtained. Material and methods. A systematic literature search was conducted in the Embase and PubMed/MEDLINE databases, which identified four clinical trials of prolgolimab and nivolumab in first-line therapy for MM/uRCM. The results were used to perform a matchingadjusted indirect comparison (MAIC) without an anchor. Cox regression and logistic regression were applied for the efficacy and safety analyses, respectively. A cost minimization analysis was carried out using the weight characteristics of 743 Russian patients with MM/uRCM. The analysis only considered the costs of drug therapy. Additionally, the costs of treatment with comparator drugs were evaluated in real-world clinical setting, taking into account therapy discontinuation due to disease progression or patient death. A budget impact analysis was performed for 10 patients with MM/uRCM. Results . In MAIC, the prolgolimab monotherapy showed no statistically significant differences in overall survival compared to nivolumab after population balancing: hazard ratio (HR) 0.84 (95% confidence interval (CI) 0.47–1.50; p=0.557) in CheckMate 067 trial population; HR 0.89 (95% CI 0.53–1.49; p=0.649) in RELATIVITY-047 trial population. Similarly, for progression-free survival: HR 1.14 (95% CI 0.77–1.70; p=0.511) for CheckMate 067; HR 1.07 (95% CI 0.77–1.48; p=0.683) for RELATIVITY-047. Based on cost minimization analysis results, weighted average annual drug therapy costs for the Russian patient population were 3.98 million rubles for prolgolimab, compared to 5.33 million rubles for nivolumab (34% higher). First-year therapy costs accounting for gradual discontinuation due to progression and death were 2.39 million rubles for prolgolimab versus 3.2 million rubles for nivolumab (difference: 809,559 rubles; 34%). On a five-year horizon, total drug therapy costs were 6.16 million rubles for prolgolimab and 8.25 million rubles for nivolumab. Budget impact analysis revealed a difference in therapy costs for 10 patients with MM/uRCM over a 1-year and 5-year horizons of 13.47 and 20.84 million rubles, respectively. Due to the cost difference, an additional three patients can be treated within the analyzed timeframe. Conclusion . Prolgolimab monotherapy demonstrated no statistically significant differences in overall survival or progression-free survival compared with nivolumab in MAIC. Given its comparable clinical efficacy and lower cost per treatment course, prolgolimab is cost-effective within the Russian healthcare system and allows for increased patient coverage without additional budget expenditures.
Background. Standard error matrices systematically underestimate the clinical value of diagnostic artificial intelligence (AI) tools by misclassifying cautionary conclusions regarding histologically benign, yet clinically suspicious neoplasms with clinical signs of malignancy as false-positive outcomes. Objective: To develop and validate a methodology for assessing the clinical effectiveness and accuracy of diagnostic AI tools in dermato-oncology, incorporating clinical caution alertness as an independent metric. Material and methods. A total of 342 skin lesions were evaluated at the Burdenko Main Military Clinical Hospital (2025–2026). While a standard error matrix was used or the formal accuracy assessment, the clinical evaluation relied on two newly developed: a four-category clinical effectiveness system (complete concordance, concordance in clinical caution, discordance in clinical caution, complete discordance), and a clinical accuracy formula derived from a clinical case matrix (Justified Conclusion, Unjustified Conclusion, Missed Justified Conclusion and Not Missed Justified Conclusion). Wilson confidence intervals (CIs) were applied. Results. The formal evaluation yielded an accuracy was of 89.7% (100.0% sensitivity, 84.8% specificity). The analysis of clinical effectiveness revealed complete concordance in 82.2% of cases, concordance in clinical caution in 12.9%, discordance in clinical caution in 1.2%, and complete discordance in 3.8%. Clinical accuracy metrics were as follows: 98.5% sensitivity (95% CI 94.6–99.6), 88.1% specificity (95% CI 83.0–91.8), 92.1% accuracy (95% CI 88.8–94.5). Conclusion. Relying solely on the formal diagnostic accuracy of AI tools underestimates their clinical value. The proposed clinical accuracy and effectiveness metrics ensure an objective assessment of AI tools in relation to the real-world tasks in dermatooncological patient routing.
Background. In Russia, one of the key mechanisms for ensuring access to modern drug therapy for patients with severe chronic and rare diseases is the federal drug provision program for 14 High-Cost Nosologies (HCN). Objective: To evaluate the current performance of the 14 HCN program from the perspective of healthcare professionals directly involved in its implementation and to identify priority areas for program improvement. Material and methods. A survey was administered to specialists responsible for drug provision within the 14 HCN program. The questionnaire included nine questions using interval and ordinal response scales. Of 87 questionnaires received, 28 valid responses were included in the final analysis. Instrument reliability was assessed using Cronbach’s α coefficient, and agreement among expert judgments was evaluated using Kendall’s coefficient of concordance (W) and Pearson’s χ 2 test. Results. The questionnaire demonstrated satisfactory internal consistency (α=0.799). According to respondents, the most critical challenges of the program were insufficient funding (mean score 4.29), the need to improve the drug provision system (4.21), and the need to automate the submission and review of applications for medicinal products (4.18). Moderate agreement among experts was observed only in ranking nosologies by priority for implementing improvement measures (W=0.3089). Hemophilia, multiple sclerosis, and malignant neoplasms of lymphoid, hematopoietic, and related tissues were identified as the highest-priority conditions. Conclusion. The findings confirm need to strengthen the 14 HCN program and may inform the development of organizational and pharmacoeconomic optimization strategies.
Objective: To assess the attitudes of physicians, residents, and medical students toward artificial intelligence (AI) technologies, the prevalence and patterns of AI use in clinical practice and healthcare in Russia; and to characterize expectations and barriers to its implementation. Material and methods. A cross-sectional online survey was conducted from March 1 to July 15, 2026. The primary array consisted of 1169 returned questionnaires. After applying the exclusion criteria (age <18, technical data entry anomalies), 8 questionnaires were excluded. All subsequent calculations were performed on the final analytical sample of 1161 questionnaires. Statistical analysis involved Spearman's rank correlation, Kruskal–Wallis criterion, cluster analysis (k-means), principal component analysis (PCA). Results. The sample included 809 (69.7%) women, and 352 (30.3%) men, with the average age of 37.5±14.6 years (median 33 years, range 18–83 years). Among the respondents, 706 (60.8%) regularly or periodically use AI in medical activities, with the most common tool being large language model-based chatbots used by 620 (53.4%) participants. Thirty (2.6%) respondents fully trust the conclusions of AI systems, while 587 (50.6%) demonstrate insignificant trust. The perceived accuracy of AI diagnosis was 47.6% on average, while the perceived accuracy of diagnosis by physicians was 72.4% (a gap of 24.8%, stable in all age groups). Specialists <29 years old are more likely to use AI; the highest readiness was recorded in the group of 30–39 years. The use of AI outside of professional medical practice was the strongest predictor of its clinical use (ρ=0.65; p<0.001). Evaluation of diagnostic accuracy by physicians was not related to any indicator of AI acceptance (p<0.05). Cluster analysis (k=4) revealed four types of digital disposition: “Enthusiasts” (n=262), “Pragmatists” (n=310), “Observers” (n=269), and “Skeptics’ (n=320). The PCA confirmed a two-factor structure: acceptance of AI (PC1 39.4%) and trust in accuracy (PC2 15.0%). Conclusion. The gap between the declared acceptance of technology and actual behavioral engagement remains a persistent characteristic of the professional medical environment. A comparative analysis of age groups refutes the simplistic notion that “younger people are more supportive of AI, while older people more resistant to it”. Improving the overall digital literacy of medical professionals is a more effective and adaptable approach to reducing barriers to AI adoption than specialized medical AI training programs. At the same time, age predicts behavior rather than attitude: educational interventions aimed at changing attitudes towards technology are applicable to all age groups equally.
Background. Artificial intelligence (AI)-based computer vision software is becoming an increasingly important tool in dermato-oncological practice. Deep learning models have demonstrated the ability to classify skin neoplasms with accuracy comparable to that of experienced dermatologists. However, their implementation in real clinical practice has revealed several significant challenges. Objective: To analyze and systematize the major challenges arising in the AI-assisted diagnosis of malignant skin neoplasms and to propose solutions to each identified challenge using the Derma Onko Melanoma Check software as an example. Material and methods. The clinical experience of applying AI software for the diagnosis of malignant skin neoplasms was analyzed, and six major categories of challenges were identified. Specific solutions to each of these challenges are proposed on the example of the Derma Onko Melanoma Check clinical decision support system (a multimodel AI-based computer vision system) for the preliminary diagnosis and triage of patients with skin neoplasms. Results. Six major challenges were identified and systematized: (1) imbalanced training datasets, with an overrepresentation of dermoscopic images and an insufficient number of clinical photographs; (2) poor quality of images acquired by physicians (e.g., overexposure, blur, and underexposure), limiting diagnostic reliability; (3) submission of images in which the lesion occupies an insufficient area of the frame for reliable analysis; (4) the single-model architecture of most AI systems and the resulting lack of adequate oncological alertness; (5) the absence of explainable artificial intelligence (XAI) in AI-generated reports; and (6) the inability of physicians to modify or refine the AI-generated conclusion using information obtained from the patient’s medical history and clinical examination. For each challenge, a specific solution implemented in Derma Onko Melanoma Check is proposed, including automated image quality assessment, lesion size verification, a multimodel ensemble of neural networks, XAI-based visualization of high-risk regions, interactive entry of clinical history data, and support for multimodal analysis. Conclusion. The implementation of AI systems incorporating the proposed solutions into routine clinical practice, particularly in primary care settings involving general practitioners, may significantly improve the early detection of malignant skin neoplasms by raising oncological vigilance for suspicious lesions and increasing the clinical interpretability and reliability of AI-generated diagnostic conclusions.
Background. For magnesium–pyridoxine therapy (original drug Magne B6®), the systems-level proteomic synergy of magnesium and pyridoxine-dependent proteins remains to be not sufficiently characterized in the nervous systems of pregnant women and diverse age groups.Objective: To establish the mechanisms of action of magnesium-dependent proteins on human neurophysiology and to characterize the proteomic synergy of original product components (a fixed combination of magnesium lactate and pyridoxine).Material and methods. In order to compile the most comprehensive list of magnesium- and pyridoxine-dependent proteins, the study applied algorithms for genome/proteome annotation and heterogeneous feature analysis, developed within the topological recognition theory. Subsequent analyses were conducted using data such as annotation keywords, protein tissue distribution, other protein cofactors, roles in the reactom, functional categories, protein interactions with various pharmaceuticals (including other micronutrients and nutraceuticals), and diseases associated with impaired magnesium-dependent protein activity.Results. The study identified a comprehensive set of magnesium- (n=1020) and pyridoxine-dependent (n=99) proteins, with a specific focus on those involved in nervous system function. Among various tissues, the brain exhibits the greatest diversity of magnesiumdependent (n=244) proteins. The synergy between magnesium and pyridoxine is manifested across many levels: cofactor interactions, protein functional categories, interactions with various pharmaceuticals, and associations with diseases. Notably, many pyridoxinedependent proteins interact with the same cofactors as magnesium-dependent proteins. Pyridoxine-dependent proteins generally fall into the same most common functional categories as magnesium-dependent ones, indicating a clear synergism between magnesium and pyridoxine in supporting fundamental physiological processes. At least 172 magnesium-dependent proteins and 20 pyridoxinedependent proteins in the human proteome are involved in the neuroprotective, neurotrophic, and other neurotropic effects of magnesium. These proteins play an important role in maintaining neurotransmitter homeostasis, neuroplasticity, and neuronal survival. Furthermore, a total of 143 drugs (including a number of micronutrients and/or nutraceuticals) are associated with the function/activity of magnesium-dependent proteins; these encompass anesthetics, anxiolytics, hypnotics and sedatives, antidementia drugs, calcium channel blockers, cardiac glycosides, antiarrhythmic agents and other cardiac drugs, antidepressants, antipsychotics, antibiotics, etc. The interaction of magnesium-dependent proteins with these groups of drugs is multidirectional. Analysis of diseases associated with dysfunction of magnesium-dependent proteins in the human proteome revealed at least 80 different diseases associated with magnesium deficiency (seizures; impaired fetal neurological development; myelination of nerves; impaired vision, hearing, and adaptive behavior; cognitive disorders; intellectual deficit). The majority of these pathologies linked to the dysfunction of magnesium-dependent proteins are also associated with the dysfunction of pyridoxine-dependent proteins. An extensive clinical evidence base has been established for the use of Magne B6® in neurology and neuropediatrics.Conclusion. The combination of organic magnesium salts (citrate, lactate, or pyroglutamate) with vitamin B6 in the Magne B6® product line (Magne B6® Forte, Magne B6® tablets, and Magne B6® oral solution) provides synergistic neuroprotective and mood-stabilizing effects. Evidence-based data confirm the pharmacological efficacy of the original drug Magne B6®.
Background. Beta-adrenergic blockers, or beta-blockers (BBs), are a crucial class of medications. Given their extensive use in the management of cardiovascular diseases, regular analysis of BB availability and range in the pharmaceutical market is essential.Objective: To analyze the range of BBs available on the pharmaceutical market of the Republic of Uzbekistan, taking their quantitative composition, countries of origin, and dosage forms into account.Material and methods. The study utilized data from the State Register of medicines, medical devices and medical equipment approved for use in medical practice in the Republic of Uzbekistan. Methods employed included systematization, statistical and comparative analysis, and graphical representation of the results.Results. The Uzbek pharmaceutical market is dominated by metoprolol, bisoprolol, and nebivolol, with the majority of products manufactured in the countries of the near and far abroad such as India, Russia, and Germany. Solid dosage forms, specifically tablets and capsules, are prevalent in this sector, which is consistent with the therapeutic use of this drug class.Conclusion. The range of BBs in the pharmaceutical market of Uzbekistan is extensive in terms of international nonproprietary names, trade names, and manufacturing origins. This reflects consistent demand and the clinical importance of this drug group in the management of cardiovascular conditions. The findings can be used to further improve the pharmaceutical supply system.
Objective: To evaluate the impact of administering tyrosyl-D-arginyl-phenylalanyl-glycine amide postoperatively to relieve pain in patients with type 2 diabetes mellitus (T2DM) and obesity on the compulsory health insurance system of Moscow Region.Material and methods. A pharmacoeconomic budget impact analysis covering a period of one year was conducted. The target population included T2DM and obesity patients aged over 18 years who received postoperative analgesic therapy (tyrosyl-D-arginyl-phenylalanylglycine amide, trimeperidine, or morphine). The regional budget impact analysis of drug therapy took into account the duration of analgesia, the incidence of complications and their treatment. A mathematical model was developed to calculate the direct medical costs of various postoperative analgesic regimens. The cost of pharmacotherapy and treatment of complications per patient during a course of medication was calculated. A sensitivity analysis of the obtained results was conducted.Results. A total of 1501 patients with T2DM and obesity underwent surgical treatment at the medical facilities of Moscow Region. The total sample of patients in the study was divided into three groups depending on the analgesic used. With the use of tyrosyl-D-arginylphenylalanyl-glycine amide, the incidence of complications in the analyzed patient population was almost four times lower compared to trimeperidine and morphine, and the cost of treating complications was almost three times lower. The total cost of treating one surgical patient experiencing a complication after the use of tyrosyl-D-arginyl-phenylalanyl-glycine amide amounted to 18,732.25 rubles, which is almost 1.3 times lower compared to other analgesic strategies. The budget impact analysis revealed the pharmacoeconomic feasibility of using tyrosyl-D-arginyl-phenylalanyl-glycine amide in postoperative analgesic therapy. Sensitivity analysis showed that the results were robust to changes in the initial parameters.Conclusion. Administration of tyrosyl-D-arginyl-phenylalanyl-glycine amide in the postoperative period leads to a proven reduction in the incidence of complications. This is a cost-effective approach to providing medical care to adult patients with T2DM and obesity.
Objective: To evaluate the efficacy of gamma interferon (IFN-γ) injections for patients with multidrug-resistant tuberculosis (MDR-TB) undergoing antituberculosis chemotherapy according to current clinical guidelines through a clinical and economic analysis.Material and methods. A clinical-economic model of the two strategies for managing MDR-TB patients was developed. The costeffectiveness of these strategies was determined taking into account only the direct costs of inpatient care. Time-based costs for patient management were calculated, focusing on the period from the start of therapy to the end of the study drug administration (3 months). This included: Period 0 – the start of therapy, days 1–14 plus 3 days for testing to confirm the absence of bacterial excretion; Period 1 – days 18–30 + 3 days for testing; Period 2 – days 34–60 + 3 days for testing; Period 3 – days 64–90 + 3 days for testing. For budget impact analysis we used the difference in costs between the two treatment strategies: antituberculosis chemotherapy with IFN-γ injections (the main group) and antituberculosis chemotherapy without IFN-γ (the control group). Efficiency parameters included sputum conversion rates based on microscopy and the median time to clinical response. Cost-effectiveness ratios were calculated using the clinical efficiency of the compared therapies, taking into account sputum smear conversion rates based on microscopy. The results were verified using a one-factor sensitivity analysis based on the cost-effectiveness ratio within a range of ±30%.Results. Pharmacotherapy costs during the first 14 days of hospitalization were higher in the group treated with IFN-γ (12,347,287.00 rubles) compared with the control group (10,723,532.00 rubles). Due to the clinical response achieved, a significantly larger number of patients in the main group are transferred to outpatient care, and costs in Period 1 for this group tend to decrease (1,394,517.12 rubles), while in the control group they are three times higher (4,138,021.76 rubles). Costs in the control group were 3.8 times higher than in the main group in Period 2, and 3.3 times higher in Period 3. Total costs for inpatient care over the 3-month treatment period with the study drug (the main group) were 1.5 times lower than those in the control group. Furthermore, the results were supported by calculations using the time to clinical response, as determined by microscopic examination. These calculations showed that the treatment in the main group was 25.64% more cost-effective than in the control group. The lower cost-effectiveness ratio in the main group compared to the control group (1,401.51 and 1,802.27, respectively) and the higher clinical efficacy in terms of the main criterion indicate that including IFN-γ in the treatment of MDR-TB patients is more cost-effective and preferable. A one-factor sensitivity analysis based on the cost-effectiveness metric confirmed the robustness of the findings to uncertainties and variations in the input data.Conclusion. The results obtained indicate the economic feasibility of adding IFN-γ as a pathogenetic therapy for MDR-TB in combination with antituberculosis chemotherapy.
Background. A previous analysis of the causes of misclassification of melanocytic and non-melanocytic skin lesions by computer vision programs (CVPs) based on the artificial intelligence (AI) models Derma Onko Check and Melanoma Check revealed systematic deviations in image quality metrics within groups of false-positive and false-negative results. Elimination of these deviations through targeted correction of photo image parameters is a logical step toward improving the diagnostic accuracy of AI-based systems.Objective: To develop a module for correcting photo image parameters, which is capable of normalizing quality metrics to the reference ranges of correctly classified cases, as well as to conduct a quantitative assessment of its impact on the performance of CVPs.Material and methods. Photographic images from an anonymized skin lesion database were subjected to parameter correction. A set of 13 photometric and texture metrics was calculated for each image; the characteristics of correctly classified photo images (true positive and true negative cases) were used as normal ranges. A Python module was developed that implements sequential, independent correction of the following deviating parameters: white balance, gamma correction, adaptive contrast processing, and an unsharp mask. Re-inference of the processed photo images was performed using Tensor Flow Lite (TFLite) models with routing to the corresponding programs Derma Onko Check and Melanoma Check. Performance was assessed by accuracy, sensitivity, and specificity.Results. The developed correction module improved the diagnostic accuracy of AI-based CVPs. During validation of the AI program Derma Onko Check on the dataset of melanocytic neoplasms (n=230), the accuracy increased from 0.909 to 0.926 (+0.017), sensitivity – from 0.949 to 0.961 (+0.012), specificity – from 0.901 to 0.919 (+0.019). During validation of the AI program Melanoma Check on the dataset of melanocytic neoplasms, the accuracy increased from 0.844 to 0.857 (+0.014). During validation of the AI program Derma Onko Check on the dataset of non-melanocytic neoplasms (n=230), the accuracy increased from 0.868 to 0.882 (+0.015). Images with critical defects (overexposed pixels exceeding 55%) were excluded from the inference: seven images for the Derma Onko Check AI program and five images for the Melanoma Check AI program in the melanocytic dataset. No critically defective images were identified in the non-melanocytic tumor dataset.Conclusion. The developed module for correcting image parameters ensures a stable and reproducible improvement in the diagnostic accuracy (sensitivity and specificity) of CVPs. The obtained results confirm the feasibility of integrating such a module into CVPs.
Background. Alloferon is a naturally occurring peptide that exhibits pronounced antiviral and anti-inflammatory properties. By inducing interferon biosynthesis, alloferon activates lymphocyte immunity.Objective: To systematize all available scientific data on the pharmacology of alloferon.Material and methods. A set of all currently available publications on alloferon from both fundamental and clinical studies (122 publications in PubMed/MEDLINE and eLibrary) was examined. After downloading this sample, it was systematically analyzed using the topological and metric approaches to heterogeneous feature descriptions developed by Yu.I. Zhuravlev and K.V. Rudakov.Results. A metric analysis of the terms most informative for describing the pharmacology of alloferon revealed its complex antiviral action, involving the suppression of the replication of human papillomavirus virus (HPV), herpes simplex virus (HSV), and hepatitis B and C viruses. HPV and HSV infections stimulate the development of dysplasia and other cervical tissue lesions, endometritis, and recurrent miscarriage. Thus, the use of alloferon in treating these gynecological pathologies has proven highly effective. Additionally, alloferon successfully treats mixed viral and bacterial-viral infections in prostatitis, eye diseases (e.g., viral iridocyclitis, anterior/ posterior uveitis), erysipelas, which is a streptococcal infection of the soft tissues, and others. Possible molecular mechanisms of alloferon's action include regulating the gene expression of antiviral and humoral immunity, as well as the body's inflammatory response. Notably, alloferon stimulates the immune system while preventing excessive inflammation, which can lead to tissue degradation, multiorgan pathology, and aggravated viral infections. Furthermore, research results from fundamental and clinical studies suggest using alloferon in complex antitumor therapy.Conclusion. Alloferon is an immune and inflammatory modulator that has demonstrated high efficacy against viral and mixed infections with a good safety profile.
Background. Spiramycin is a macrolide antibiotic characterized by minimal resistance to various strains of pathogenic bacteria and a good safety profile. Although the pharmacology of spiramycin has been the subject of many publications, these data are yet to be systematized.Objective: To systematize all available scientific publications on spiramycin pharmacology.Material and methods. All currently available publications on basic and clinical studies of spiramycin were analyzed. The query “spiramycin OR rovamycine OR RP 5337” returned 1,755 reports in the PubMed/MEDLINE biomedical database. This sample of publications was then systematically analyzed using the topological and metric approaches to the analysis of heterogeneous feature descriptions that are adopted by the scientific school of Yu.I. Zhuravlev and K.V. Rudakov (Academicians of the RAS). Results. A cluster analysis of the most informative terms describing the pharmacological properties of spiramycin revealed that it is a unique macrolide characterized by targeted tissue accumulation and significantly higher safety than other antibiotics. This safety of spiramycin underlies its successful use to treat toxoplasmosis in pregnant women and prevent maternal-to-fetal transmission of the parasite Toxoplasma gondii. Spiramycin also holds promise for the treatment of other urogenital infections (chlamydia and non-gonococcal urethritis), as well as against oral pathogens that cause caries, gingivitis, and periodontitis. Spiramycin's targeted accumulation in lung tissue allows it to be used against respiratory pathogens, including upper and lower respiratory tract infections. Spiramycin was shown to have anti-inflammatory, anti-tumor, and other additional effects (e.g., anti-obesity).Conclusion. Spiramycin is characterized by targeted tissue accumulation; it exhibits no significant concomitant toxicity, causes no micronutrient loss (including magnesium, whose deficiency results in QT interval prolongation on the electrocardiogram), and, unlike some other macrolides, has no stimulating effect on resistance development in bacterial pathogens. These properties of the spiramycin molecule indicate promising potential for its use in the inhibition and eradication of bacterial strains resistant to other antibiotics.
Objective: To evaluate the budget impact of a fixed-duration combination (FC) “acalabrutinib + venetoclax” regimen for treatmentnaive adults with chronic lymphocytic leukemia (CLL), unmutated IGHV, and absence of del(17p) or mutations in TP53 in the Russian Federation.Material and methods. A deterministic, payer-perspective model was developed over one- and three-year horizons. The analysis focused on drug acquisition costs (national price registry, +10% value added tax), with label-based dosing. The standard therapy included Bruton’s tyrosine kinase inhibitors (acalabrutinib, ibrutinib, or zanubrutinib), or FCs “venetoclax + obinutuzumab” and “ibrutinib + venetoclax”. The simulated scenario assumed a 50% substitution of “ibrutinib + venetoclax” by “acalabrutinib + venetoclax” over three years. A one way sensitivity analysis was performed to evaluate the impact of variations in drug prices (±20%), population size (±20%), and uptake of “acalabrutinib + venetoclax” (–20% to complete substitution).Results. The target population included 697 patients. Per-patient costs of FCs were as follows: 9,124,560 rubles for “acalabrutinib + venetoclax”; 10,375,643 rubles for “ibrutinib + venetoclax”. For the total cohort, total three-year expenditures amounted to 8,404.5 million rubles in the current practice versus 8,322.0 million rubles with FC “acalabrutinib + venetoclax”, i.e., budget savings came to 82.5 million rubles. These savings are driven by the lower cost for a course of “acalabrutinib + venetoclax” compared to “ibrutinib + venetoclax”. Sensitivity analyses confirmed robustness: although results were most sensitive to the prices of acalabrutinib and ibrutinib, savings persisted across tested ranges; higher uptake of “acalabrutinib + venetoclax” further increased budget savings.Conclusions. Implementing the FC “acalabrutinib + venetoclax” for the first-line treatment of CLL patients with unmutated IGHV and no TP53 aberrations reduces the healthcare budget burden compared to “ibrutinib + venetoclax”, yielding approximately 82.5 million rubles in savings over three years based on drug acquisition costs.
Background. The introduction of immune checkpoint inhibitors (ICIs) and targeted therapies (TTs) has fundamentally changed the clinical management of melanoma, significantly improving survival outcomes both in unresectable disease and in the adjuvant setting. At the same time, these therapeutic innovations have substantially increased healthcare expenditures, which raises the importance of pharmacoeconomic evaluation in clinical and policy decision-making.Objective: To analyze current methods for assessing the cost-effectiveness of pharmacotherapy using real-world data (RWD), to summarize international experience in their application, and to evaluate the prospects for implementing RWD-oriented pharmacoeconomic approaches in the healthcare system of the Russian Federation.Material and methods. Pharmacoeconomic studies published between 2010 and 2025 were analyzed using data from randomized clinical trials and RWD. Key outcomes assessed included costs, effectiveness, and utility, such as quality-adjusted life years and incremental cost-effectiveness ratios.Results. In most international models, ICIs – particularly anti-рrogrammed cell death protein 1 monotherapy – have more favorable costeffectiveness profiles in the treatment of unresectable melanoma compared with TTs, whereas combination regimens are characterized by a substantially higher budget impact. The cost-effectiveness of adjuvant therapy largely depends on the risk of recurrence and the cost of subsequent treatment for disease progression. Several studies show the high economic value of preventive and screening interventions aimed at early melanoma detection. The review highlights the need for cautious extrapolation of international pharmacoeconomic data to the Russian setting, taking into account national pricing policies, reimbursement mechanisms, and the absence of a formally established willingness-to-pay threshold.Conclusion. The performed analysis of published studies shows that the use of RWD in pharmacoeconomic evaluations of pharmacotherapy allows refinement of model parameters and improves the robustness of economic conclusions; however, the applied approaches vary substantially in study design and data quality. The applicability of these approaches within the Russian healthcare system requires consideration of limitations related to the availability and structure of domestic RWD.
Objective: To conduct a comparative analysis of concepts aimed at improving pharmaceutical care for patients with socially significant diseases in both Russia and other countries with the purpose of identifying priority development directions for the Russian system.Material and methods. A systematic search of scientific literature, regulatory documents, and statistical data for 2016–2025 was conducted using the PubMed/MEDLINE, CyberLeninka, and eLibrary databases. A comparative method was applied to analyze European, North American, and Russian pharmaceutical provision models. Their effectiveness was evaluated based on accessibility, financial sustainability, quality of care, and innovation criteria.Results. The European model is characterized by a high level of government funding (70–80%) and effective cost control mechanisms through health technology assessment institutions. The North American system demonstrates trends toward universal coverage with multiple funding sources. The Russian model provides 100% coverage for high-cost nosologies, however, the overall share of government funding reaches 40% with a significant regional differentiation in accessibility. Current trends include implementation of personalized medicine, targeted therapy, telemedicine, and risk-sharing agreements with pharmaceutical companies.Conclusion. Priority directions for improving the Russian system include unification of regional approaches, implementation of clinical and economic effectiveness assessment mechanisms, development of personalized medicine and digital technologies for pharmaceutical care management.
Background. Low-sodium salt substitutes (LSSS) are widely used in the dietary management of patients with arterial hypertension.Objective: To investigate the effects of LSSS in white rats using a model of accelerated “dietary-related” aging induced by D-galactose combined with palm oil, dietary L-methionine, sodium chloride in drinking water, and ferrous sulfate.Material and methods. The study included 30 male Wistar rats weighing 300–500 g. Model induction was performed until Day 13; after that, all animals with reproduced pathology were switched to a standard diet, and a subset of these animals received LSSS therapy until Day 54 of the experiment. On Days 0, 13, and 54, sixty parameters were assessed, including the results of complete blood count, serum biochemistry, and neurological testing.Results. The model reproduced a complex of disorders, including altered biomarkers of multiple organ pathology, hematopoietic dysfunction, and deterioration of neurological status. The use of LSSS from Day 13 to Day 54 mitigated the progression of accelerated multiple organ aging. In particular, model induction increased serum creatinine (intact: 35.67±1.21 μmol/l; model, Day 54: 39.17±1.47 μmol/l; p=0.000628) with a significant reduction in glomerular filtration rate (GFR) (intact: 167.41±7.26 ml/min/1.73 m2 ; model, Day 54: 153.4±6.32 ml/min/1.73 m2 , p=0.002646). The LSSS promoted the normalization of serum creatinine (model, Day 54: 39.17±1.47 μmol/l; LSSS: 33.33±1.86 μmol/l; p=0.000628) and GFR (model, Day 54: 153.4±6.32 ml/min/1.73 m2 ; LSSS: 181.1±12.27 mL/min/1.73 m2 ; p=0.002646), bringing these parameters toward values typical of intact animals. Furthermore, LSSS contributed to the normalization of iron and electrolyte metabolism. It restored transferrin saturation (model, Day 54: 69.88±11.79%; LSSS: 46.7±10.8%; p=0.053335), with levels comparable to those of intact animals. Improvements were also noted in the levels of magnesium (model, Day 54: 1.12±0.01 mmol/l; LSSS: 1.22±0.14 mmol/l; p=0.004019), sodium (model, Day 54: 141.42±1.3 mmol/l; LSSS: 138.13±1.61 mmol/l; p=0.069579), and potassium (model, Day 54: 7.29±0.05 mmol/l; LSSS: 8.06±1.72 mmol/l). LSSS also reduced liver damage induced by the model, alleviated chronic inflammation, and normalized hematopoiesis (restoration of immature reticulocyte fractions, medium- and high-fluorescence fractions). Neurological evaluation using the open field and Porsolt tests demonstrated that model-induced neurological impairments were effectively mitigated by LSSS therapy.Conclusion. Standardized LSSS administration promotes attenuation of aging-related pathophysiology in the studied experimental model.
