Predicting oncological outcomes in early-stage cervical cancer: follow-up analysis using medical informatics methods

Chronic psycho-emotional stress under active combat conditions correlates with a sharp increase in the incidence of oncological pathologies, particularly cervical cancer (CC). Concurrently, the forced delay of specialized treatment significantly worsens disease-free survival rates, which is most critical for young patients. Objective: to perform a mathematical analysis of follow-up data from patients with early-stage cervical cancer (stages IB–IIA) to identify and refine the values of marker indicators for predicting long-term oncological outcomes in the future. Materials and methods. Using mathematical statistics and modern information technologies, a digital array of follow-up data from 108 patients with early-stage CC was analyzed. A systematic analysis of large datasets allowed, with minimal involvement of human resources, to establish correlations between baseline clinical characteristics, treatment features, and the occurrence of long-term cancer-specific outcomes, as well as to identify a number of potential prognostic markers. Results. It was determined that the majority of marker features are formed based on baseline clinical indicators prior to the initiation of treatment. However, their reference values for early-stage CC differ from the universally accepted standards in the literature for the general patient population. It was established that the specificity of these markers directly depends on the type of the first treatment modality (primary surgery or chemoradiotherapy). Conclusion. The identified patterns and highlighted prognostic markers can serve as a foundation for developing clinical guidelines on personalized adjustment of antineoplastic therapy under conditions of forced intensification of the treatment process.