Keyword: CIN

ABSTRACT: Introduction: Cervical cancer remains a significant problem in the structure of cancer morbidity and mortality among women in the Republic of Tajikistan. During the period from 2014 to 2025, the average age-standardized incidence rate (ASIR) was 11.68 per 100,000 female population, and the age-standardized mortality rate (ASMR) was 6.80 per 100,000. The highest average age-specific incidence rates were recorded in the 55–64 age group, at 32.16 per 100,000 women. To reduce this burden and in line with the World Health Organization's Global Strategy for the Elimination of Cervical Cancer, the Government of Tajikistan officially launched a mass human papillomavirus (HPV) vaccination campaign in October 2025. Objective: To evaluate the initial results of the implementation, coverage, safety profile, and public perception of the first national HPV immunization campaign targeting adolescent girls aged 10–14 years in the Republic of Tajikistan.
Materials and Methods: Following the vaccination campaign conducted in October 2025, a comprehensive assessment was carried out. The study analyzed official statistical data from the Republican Center for Immunoprophylaxis, covering a target population of 542,268 girls. In December 2025, a formal Post-Introduction Evaluation (PIE) was conducted at 16 immunization centers and 22 medical facilities to assess logistics, cold chain management, and healthcare worker preparedness. In addition, Rapid Convenience Monitoring (RCM) was implemented in 140 schools across 28 districts for operational decision-making, during which 8,834 girls were interviewed using structured teacher-administered questionnaires to identify behavioral and social factors influencing vaccination.
Results: The overall coverage of the national campaign reached 95.5%, with 507,114 girls vaccinated. Specifically, coverage was 91.1% among the cohort of 10-year-old girls (routine vaccination) and 96.7% among the cohort aged 11–14 years (catch-up vaccination). The vaccine safety profile was excellent, with 48 minor adverse events following immunization (AEFI) reported, accounting for 0.009%. The school-based RCM survey confirmed high coverage rates (91.5% in surveyed schools) and demonstrated strong public support, with 81% of parents endorsing the initiative. The main barriers among the unvaccinated minority were parental refusal (17.0%) and absence from school on the day of vaccination (16.3%). PIE results highlighted strong political leadership, a reliable cold chain infrastructure, and effective interaction between parents and educators, although minor local vaccine supply delays were also noted.
Conclusion: The rapid integration and exceptionally high vaccination coverage against HPV mark a critical public health achievement for Tajikistan. The first national campaign has successfully laid the foundation for achieving international cervical cancer elimination targets. To sustain the results achieved, future efforts should focus on local microplanning, continued community awareness initiatives to address vaccine hesitancy, and ensuring reliable supply chains for routine immunization.

ABSTRACT: Introduction: Renal cell carcinoma brain metastases are a complication of oncological disease and are associated with an unfavorable prognosis. Stereotactic radiosurgery is one of the main methods of local treatment for intracranial metastases. Data on its outcomes in renal cell carcinoma brain metastases in Kazakhstan are limited.
Objective: To evaluate overall survival, intracranial progression-free survival, and local control after stereotactic radiosurgery.
Materials and Methods: A retrospective cohort study was conducted on patients with renal cell carcinoma brain metastases who underwent stereotactic radiosurgery using the Gamma Knife at the National Center for Neurosurgery between 05.10.2021 and 18.03.2026. The median age was 60 years (44–75), the median Karnofsky Performance Status score was 75 (50–90), and the median prognostic score was 1.5 (0–3.5). Extracranial metastases were present in 25 patients (78.1%), and 21 patients (65.6%) received systemic therapy prior to radiosurgery. Overall survival was assessed in 32 patients; intracranial progression-free survival and local control were assessed in 28 patients with available follow-up magnetic resonance imaging (MRI) studies. For local control assessment, 89 treated lesions were analyzed. Survival rates were calculated using the Kaplan–Meier method. The study was approved by the Bioethics Commission No. 1 of the "National Center for Neurosurgery" JSC (protocol extract No. 7 dated April 13, 2026) and conducted in accordance with the ethical principles of the Declaration of Helsinki.
Results: The median overall survival was 22.1 months. Overall survival rates at 6, 12, and 24 months were 71.4%, 60.8%, and 47.9%, respectively. Among the 28 patients with follow-up MRI studies, the median follow-up period was 4.5 months (1.23–36.13), and the median intracranial progression-free survival was 12.7 months. Intracranial progression was recorded in 11 patients: 9 developed new brain metastases, and 2 had leptomeningeal dissemination. Local control was analyzed in 89 treated metastatic lesions in 28 patients. One case of local progression of a treated lesion was recorded by MRI, detected 9.57 months after treatment. Local control at 6 and 12 months was 100% and 96.8%, respectively.
Conclusions:  Stereotactic radiosurgery using the Gamma Knife provides high local control of renal cell carcinoma brain metastases. Intracranial progression was predominantly due to the appearance of new metastatic lesions and leptomeningeal dissemination, rather than progression of previously treated lesions. The obtained results demonstrate the high efficacy of the Gamma Knife in achieving local control in patients with renal cell carcinoma brain metastases.

ABSTRACT: Objective: To evaluate the medical-organizational and clinical effectiveness of optimizing comprehensive diagnostics and follow-up care for patients with cervical intraepithelial neoplasia (CIN) through the introduction of a specialized digital module into the national Health Management Information System (HMIS/DHIS2) of the Republic of Tajikistan.
Materials and Methods: An analysis was conducted on the results of diagnosis, treatment, and dynamic follow-up of 542 patients with morphologically verified CIN1–3/Tis, aged 20 to 65 years, examined during 2023–2026. The main group using the digital system (n=82) was compared with a control group managed through paper-based documentation (n=460). The developed Digital Module for Early Diagnosis (DMED) of cervical cancer enabled the integration of 51 specialized cervical pathology units at district and city health centers, HPV diagnostics laboratories, cytology laboratories, and the State Institution "Republican Oncological Scientific Center" (ROSC). Time intervals for completing stages of medical care and the proportion of patients under follow-up care were assessed.
Results: The use of automatic tracking algorithms through the DMED for cervical cancer reduced the total diagnostic and treatment time interval (from abnormal visual screening through extended diagnostics to organ-preserving treatment with LEEP/cone biopsy) from 68.4 ± 5.2 to 21.2 ± 2.4 days (p < 0.001). The proportion of women lost to follow-up decreased from 34.2% to 6.1%. All 5 cases of invasive cervical cancer detected using the DMED were diagnosed at stage I of the disease.
Conclusion: The implementation of the DMED for cervical cancer optimizes the organization of gynecologic oncology care, eliminates lost links in patient referral pathways, and ensures a high level of monitoring of the health status of patients with precancerous pathology of the cervix.

ABSTRACT: Background: The introduction of targeted therapy and immune checkpoint inhibitors has significantly improved treatment outcomes in patients with locally advanced and metastatic renal cell carcinoma (mRCC). However, tumor heterogeneity and the development of alternative signaling pathways may contribute to treatment resistance, emphasizing the need for effective combination strategies.
Objective: To evaluate the efficacy of contemporary immunotherapy-based combinations in the first-line treatment of metastatic renal cell carcinoma and identify clinical factors relevant to treatment selection.
Materials and Methods: Published data from randomized phase III studies of first-line systemic therapy for advanced and metastatic renal cell carcinoma were analyzed. Particular attention was given to nivolumab plus ipilimumab and lenvatinib plus pembrolizumab compared with sunitinib. Treatment efficacy was assessed using progression-free survival (PFS), overall survival (OS), objective response rate (ORR), and outcomes according to International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) risk groups.
Results: In the CLEAR trial, lenvatinib plus pembrolizumab significantly prolonged median PFS compared with sunitinib (23.9 vs 9.2 months) and improved overall survival. In patients with intermediate/poor IMDC risk, median PFS was 22.1 months with lenvatinib plus pembrolizumab versus 5.9 months with sunitinib, while ORR was 72.4% versus 28.8%, respectively. Long-term results of the CheckMate 214 trial demonstrated a sustained survival benefit with nivolumab plus ipilimumab compared with sunitinib. The final analysis after a median follow-up of 9.3 years showed an OS hazard ratio of 0.71 in the intention-to-treat population and 0.69 in patients with intermediate/poor IMDC risk. Durable responses were maintained across long-term follow-up.
Conclusions: Immunotherapy-based combinations have substantially improved the treatment of metastatic renal cell carcinoma. Lenvatinib plus pembrolizumab provides significant improvements in PFS and objective response compared with sunitinib, while nivolumab plus ipilimumab demonstrates durable long-term survival benefits. Selection of first-line therapy should consider IMDC risk group, tumor burden, metastatic sites, clinical condition, histological characteristics, and individual patient factors.

ABSTRACT: Introduction: Despite the relatively low mutational burden of most pediatric tumors, molecular genetic studies are increasingly being used in pediatric oncology. They enable confirmation of diagnosis, assessment of prognosis, and identification of potential targets for molecularly targeted therapy. Analysis of molecular diagnostic results in real-world clinical practice allows us to assess the capabilities and limitations of molecular diagnostics across different pediatric tumors.
Materials and Methods: Targeted sequencing of tumor DNA using a customized QIAseq panel (Qiagen, Germany) was performed in 334 patients with extracranial solid tumors treated at the Dmitry Rogachev National Medical Research Center of Pediatric Hematology, Oncology and Immunology between 2018 and 2023.
Results: The highest diagnostic yield was observed in malignant rhabdoid tumors (n=23): diagnostically significant alterations were identified in 91.3% of patients.
In most cases, these alterations were highly specific to this tumor type and could be used to confirm the diagnosis alongside morphological and immunohistochemical data.
Prognostically significant molecular alterations were most frequently detected in neuroblastoma – in 66.7% of patients (112/168). The majority of these consisted of mutations in genes of the RAS/p53 signaling pathways, allowing further characterization of tumor biology and identification of patients with molecular features potentially associated with disease course and response to therapy.
Potentially therapeutically significant alterations were identified in 36% of patients (120/334). However, the presence of a molecular target did not always lead to the administration of the corresponding drug, as evidence for the efficacy of targeted therapy in children remains limited for a significant proportion of these alterations.
Targeted therapy based on molecular genetic testing results was administered in 6.3% of cases (21/334), predominantly in neuroblastoma (n=13).
It was used in the first-line setting or at first relapse in 66.7% of cases (14/21). In 61.9% (13/21) of patients, targeted agents were used in combination with standard antitumor therapy.
An objective response or disease stabilization lasting more than 6 months was observed in 66.7% (14/21) of patients. The median time to best response or stabilization was 6 months (range 0.8–12.3). The median duration of targeted therapy as monotherapy was 10.9 months (range 0.8–43.5), and in combination with chemotherapy – 12.3 months (range 0.3–61.5). In 42.8% (9/21) of patients, the response was maintained at the time of last follow-up.
Conclusion: Thus, molecular genetic plays an important role in improving the diagnosis and treatment of pediatric tumors. Futher accumulation of clinical and molecular data will provide a deeper understanding of tumor biology and expand opportunities of personalized treatment.

ABSTRACT: Introduction: Germline mutations in the BRCA1 and BRCA2 genes are an important hereditary risk factor for the development of breast cancer. The spectrum of pathogenic variants of these genes is characterized by pronounced ethnic and population specificity, including the presence of founder mutations. Data on the spectrum of germline BRCA1/BRCA2 variants in the Kazakh population remain limited, which hinders their application in clinical practice and genetic counseling.
Objective: To study the spectrum of germline mutations in the BRCA1 and BRCA2 genes in patients with breast cancer and women with a family history in the Kazakh population and to identify the founder mutation.
Materials and Methods: The study included 544 women of Kazakh ethnicity with breast cancer or a family history of cancer. DNA was isolated from peripheral blood lymphocytes according to the manufacturer's protocol. Exons and adjacent intronic regions of the BRCA1 and BRCA2 genes were sequenced by NGS. Variants were classified by clinical significance, and their spectrum and distribution by gene, type, and localization were analyzed.
Results: Of the 544 examined patients, 178 (32.7%) were found to have mutations in the BRCA genes. Mutations in the BRCA1 gene were detected in 35 patients (19.7%), in the BRCA2 gene — in 119 patients (66.8%), and mutations in both genes — in 24 patients (13.5%).
The study identified a total of 125 BRCA gene variants. Sequence analysis revealed 37 pathogenic variants in 81 patients, 83 likely pathogenic variants in 104 patients, 1 likely benign variant in 6 patients, 2 benign variants in 6 patients, and 2 variants of uncertain clinical significance in 2 patients.
Among BRCA1 gene variants, the most common was a deletion of exon 6, detected in 11 patients (6.1%). Deletions of exons 2, 13, and 20 were found in 7 patients each (3.9%), while deletions of exons 8 and 23, as well as variants BRCA1 c.3214delC and BRCA1 c.1044_1045insC, were found in 3 patients each (1.7%).
Among the identified BRCA2 gene variants, the most common was a deletion of exon 16, detected in 37 patients. The variant c.24_27delGCCAinsCG was identified in 15 patients, c.2600_2601insA in 12 patients, and c.9241_9242insA in 11 patients.
Conclusions: The spectrum of germline BRCA1/BRCA2 mutations in the Kazakh population is characterized by a predominance of BRCA2 gene variants. Deletion of exon 16 of the BRCA2 gene was identified as a founder mutation.

ABSTRACT: ABSTRACT
Background: Diethylnitrosamine (DEN) is a nitrosamine derivative with alkylating, carcinogenic, and mutagenic properties that causes major liver damage and acts as a hepatocarcinogen in rodents. Acacia nilotica and Kigelia africana are plants used in local communities to treat wounds and ulcers.
Objective: This study investigated the effect of aqueous extracts of Kigelia africana and Acacia nilotica on alpha-fetoprotein (AFP), carcinoembryonic antigen (CEA), and cancer antigen 125 (CA-125) levels in DEN-induced liver cell dysplasia in Wistar rats.
Methods: Forty (40) male Wistar rats, aged 6–8 weeks, were divided into eight (8) groups of five (5) animals each. Liver cell dysplasia was induced with a single intraperitoneal dose of DEN (100 mg/kg) and promoted with oral phenobarbitone (0.25 mg/kg) twice weekly, beginning one week after induction. Group I received clean drinking water; group II received DEN only; group III received DEN + phenobarbitone; groups IV and V received DEN + phenobarbitone + 250 mg/kg and 500 mg/kg of Acacia nilotica respectively; groups VI and VII received DEN + phenobarbitone + 250 mg/kg and 500 mg/kg of Kigelia africana respectively; and group VIII received DEN + phenobarbitone + 10 mg/kg of sorafenib. Blood samples were collected on day 120 for biomarker evaluation, and liver tissue was processed for histopathology.
Results: CEA and CA-125 differed significantly among groups (p < 0.001), although group means largely remained within the physiological reference range; AFP showed no significant difference (p = 0.580). The highest CEA values occurred in the DEN-only and DEN + phenobarbitone groups, while CA-125 was highest in the DEN-only and sorafenib-treated groups. Animals treated with the plant extracts, particularly at the higher dose (500 mg/kg), maintained CEA and CA-125 values close to those of the negative control. Histopathology showed dose-dependent attenuation of DEN-induced changes by both extracts, with the higher dose of Kigelia africana producing near-normal liver architecture.
Conclusion: Both extracts, especially at higher doses, appeared chemoprotective against DEN-induced hepatic changes, supporting further investigation of their underlying mechanisms.

ABSTRACT: Prostate cancer still remains one of the most common cancers in men worldwide, and it is a great therapeutic challenge, especially in the field of immunotherapeutics. The tumour microenvironment (TME) is immunologically “cold” in prostate cancer, and influenced by intrinsic molecular characteristics of the disease such as androgen receptor (AR) signalling, PTEN loss, and lineage plasticity towards neuroendocrine prostate cancer (NEPC). Together, these aspects inhibit antigen presentation, block the entry of cytotoxic T cells and help to establish spatially organised immunosuppressive niches, providing a rational explanation for the clinical variability and partial efficacy of immune-based therapies.
Traditional bulk genomic approaches have provided important insights into tumour biology but are unable to capture the cellular and spatial complexity of tumour–immune interactions. These developments have been spurred by recent advancements in single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics, which allow to detect individual cell subpopulations within intact tumour tissues, such as exhausted T cells co-expressing PD-1, TIM-3, LAG-3 and TIGIT, immunosuppressive SPP1+ macrophages and various cancer-associated fibroblast subpopulations. These technologies have identified specific immune exclusion sites, stromal–epithelial immune silencing barriers, and therapeutic resistance and immune evasion regulatory programs in the context of prostate cancer specifically.
However, there are still many technical challenges that need to be overcome, such as the lack of patient samples and their demographic diversity, data integration, lack of spatial characterisation of bone metastases and difficulties in clinical translation. Comprehensive multi-omics atlases, AI-driven spatial pattern recognition, functional validation of potential targets and prospective clinical trials based on biomarkers are all important areas for future research. They show significant potential for the creation of better, personalized immunotherapeutic treatment for prostate cancer.

ABSTRACT: Hepatocellular adenomas (HCA) are rare benign liver tumors associated with metabolic risk factors and carry a risk of malignant transformation. We present a case of a 50-year-old woman with a liver lesion initially diagnosed as a hepatocellular adenoma that showed progressive growth on follow-up imaging. Contrast-enhanced MRI (Magnetic Resonance Imaging) and CT (Computed Tomography) showed enlargement of the lesion in segments S6–S7. Initial biopsy findings were consistent with hepatocellular adenoma. Because of continued tumor growth, right liver resection was performed. Histopathological examination revealed foci of well-differentiated hepatocellular carcinoma arising within a dysplastic adenoma with areas of necrosis. This case highlights the diagnostic challenges in distinguishing hepatocellular adenoma from early hepatocellular carcinoma, particularly in patients with metabolic risk factors and progressive tumor enlargement. It emphasizes the importance of careful imaging surveillance and timely surgical management.

ABSTRACT: Precision medicine aims to deliver the right treatment to the right patient at the right time, yet its widespread clinical adoption remains limited by challenges in accurate diagnosis, slow drug development processes and the difficulty of translating complex biological data into actionable clinical decisions. Conventional diagnostic and therapeutic approaches often rely on population averages, which can overlook individual genetic, molecular and clinical differences, leading to variable treatment responses and high drug development failure rates. In recent years, Artificial Intelligence (AI) and Machine Learning (ML) have gained increasing attention as clinical support tools capable of analyzing complex and large-scale biomedical data, improving diagnostic accuracy, accelerating drug development and enabling more personalized approaches to patient care. This study presents a systematic literature review conducted in accordance with the PRISMA guidelines, examining recent evidence on how AI and ML act as catalysts for precision medicine, particularly in diagnosis and drug development. Peer-reviewed studies published between 2019 and 2025 were systematically identified from major academic databases and screened using predefined inclusion and exclusion criteria. The selected studies were analyzed to assess clinical applications, AI techniques employed and their implications for personalized healthcare and pharmaceutical innovation. The findings indicate that AI and ML significantly enhance diagnostic accuracy through applications in medical imaging, genomics and electronic health record analysis, supporting earlier and more precise disease detection. In drug development, AI-driven methods improve target identification, lead optimization, toxicity prediction and clinical trial design, contributing to reduced development time and cost. Furthermore, the integration of multi-omics and clinical data through AI enables more personalized treatment strategies, improving therapeutic selection and dosing. This study concludes that AI and ML are powerful catalysts for precision medicine and capable of bridging the gap between complex biomedical data and clinical decision-making. With appropriate validation, explainable models and robust ethical and regulatory frameworks, these technologies have the potential to accelerate drug development and support clinicians in delivering more accurate diagnoses, more effective treatments and safer patient-centered, precision-based healthcare.

ABSTRACT: Artificial intelligence (AI) has become increasingly integrated into radiology and nuclear medicine, particularly in oncology, where imaging plays a central role in diagnosis, staging, treatment planning, and response assessment. To date, evaluation of AI-enabled radiology has been dominated by diagnostic accuracy metrics derived from retrospective validation studies. While such measures are essential for technical assessment, they provide limited insight into real-world clinical value. High algorithmic performance does not necessarily translate into improved decision-making, workflow efficiency, patient outcomes, or health system performance. This narrative review critically examines AI-enabled radiology as a digital health intervention in oncology and nuclear medicine, emphasizing the need to move beyond accuracy-centric evaluation paradigms. We analyze the translational gap between controlled validation and routine clinical deployment, highlighting challenges related to dataset bias, generalizability, and human–AI interaction. Key domains of real-world impact are explored, including clinical decision-making, multidisciplinary integration, workflow and operational performance, patient-centered outcomes, and system-level implications. Methodological considerations for outcome-focused evaluation are discussed, alongside regulatory, ethical, and governance frameworks necessary for responsible implementation. We propose a clinical-impact–centered evaluation framework that links AI-assisted imaging to patient, clinician, and system-level outcomes within a continuous monitoring model. Reframing AI-enabled radiology as a clinical intervention rather than a standalone algorithm is essential for ensuring meaningful, equitable, and sustainable adoption in oncology and nuclear medicine practice.

ABSTRACT: Minimal residual disease (MRD) has become a significant predictor of relapse and survival in acute myeloid leukemia (AML), indicating the extent of remission beyond traditional morphological evaluation. Although multicolor flow cytometry and quantitative PCR are essential methodologies in minimal residual disease identification, both are constrained by immunophenotypic variability, the necessity for stable molecular targets, and limited sensitivity. Advancements in next-generation sequencing (NGS) have revolutionized the minimal residual disease (MRD) field by enabling highly sensitive, mutation-driven identification of leukemic clones across a broad genomic landscape. Contemporary error-suppressed next-generation sequencing techniques—such as unique molecular identifiers, duplex sequencing, and single-molecule molecular inversion probes—have enhanced analytical sensitivity to the 10⁻⁵ to 10⁻⁶ range, enabling the detection of ultra-low-frequency variations with greater specificity. These techniques improve clinical risk classification, refine prognostication within genetically defined AML subtypes, and guide therapeutic options, including post-remission therapy, targeted inhibition, and the timing and intensity of allogeneic stem cell transplantation. Innovative applications, such as single-cell sequencing, cell-free DNA studies, and integrative multi-omic MRD evaluation, enhance the capabilities of genomics-based monitoring. Nonetheless, obstacles remain, such as differentiating cancer mutations from clonal hematopoiesis, standardizing analytical pipelines, establishing clinically relevant thresholds, and incorporating NGS MRD into standardized treatment protocols. This review encapsulates contemporary NGS methods for AML MRD diagnosis, assesses their clinical ramifications and constraints, and suggests future pathways necessary for comprehensive clinical integration. With advancements in the area, NGS-based MRD is set to become a pivotal element of precision-guided AML control.

ABSTRACT: Spatial tumour heterogeneity, which denotes the changes in cellular and molecular attributes across distinct locations within a tumour, significantly influences cancer diagnosis and treatment resistance. The heterogeneity of tumour cells inside a singular mass facilitates tumour development, metastasis, and the ineffectiveness of standard therapy. Comprehending the geographical distribution of tumour cells is crucial for formulating more efficient treatment regimens. Diverse methodologies are employed to investigate spatial heterogeneity, encompassing modern imaging techniques such as MRI, PET, and multiplexed imaging, alongside omics approaches including genomes, transcriptomics, and proteomics. These instruments offer insights into the tumour microenvironment and facilitate the identification of resistant subpopulations. The amalgamation of imaging and genomic data via radiogenomics has emerged as a viable methodology, providing an extensive perspective on the spatial and molecular intricacies of tumours. Principal findings reveal that spatial heterogeneity fosters medication resistance by establishing microenvironments characterised by varying oxygen levels, immunological infiltration, and genetic alterations, hence complicating the efficacy of monotherapy strategies. Hypoxic environments and immunological evasion significantly contribute to treatment resistance. Addressing geographical heterogeneity has the potential to enhance cancer treatments. By analysing the molecular and geographical characteristics of tumours, physicians can customise therapies more efficiently, minimising resistance and improving therapeutic results. This methodology signifies a vital advancement in precision medicine, providing more individualised and efficacious cancer therapies in the future.

ABSTRACT: This inaugural editorial introduces the new journal, "Oncology, Nuclear Medicine and Transplantology," launched by the National Research Oncology Center (NROC) in Kazakhstan. It outlines the journal's mission to serve as a pivotal interdisciplinary platform integrating these three rapidly evolving and interconnected fields. The editorial emphasizes the journal's commitment to addressing significant healthcare challenges at the national level in Kazakhstan, stimulating regional collaboration across Central Asia, and contributing to the global scientific discourse. The goal is to foster the exchange of original research, clinical experiences, and innovative practices to ultimately improve patient care and advance medical science in these critical specialties.

ABSTRACT: Introduction: This study is aimed at assessing the operational efficiency of the admission department of the National Research Oncological Center (NROC) for the period from 2020 to 2024 with an emphasis on the impact of digitalization on patient management and workflow optimization. Telemedicine is a key tool for improving the availability and quality of medical care, especially for patients living in remote regions. In oncology, its importance is increasing due to the need for interdisciplinary interaction and quick routing of patients.
Methods: A retrospective analysis was conducted using internal hospital records, admission logs, and national healthcare regulations. Key performance indicators were assessed, including patient intake volume, processing time, and rejection rates. The impact of digital tools such as automated registration, routing algorithms, and remote clinical validation was examined.
Results: Patient visits increased from 5,664 in 2020 to 11,851 in 2024, while cancer-related hospitalizations rose from 1,477 to 6,102. The average waiting time for reception was reduced from 12 to 7 hours, and the processing time for documentation was reduced from 45 to 15 minutes. The introduction of digital solutions improved the accuracy of admission and reduced the number of inappropriate hospitalizations. Improvements in identifying clinical contraindications and infectious risks through remote screening technologies were also noted. The number of telemedicine consultations increased 3 times, especially in surgery and transplantology.
Conclusion: Digital transformation has significantly improved admissions efficiency, improving patient flow, reducing processing time and improving decision-making. Further development of digital infrastructure and staff competencies is recommended to ensure sustainable growth and quality of care in cancer care. The comprehensive implementation of telemedicine and interaction with air ambulance contribute to increasing the availability of cancer care, optimizing resources and reducing costs.