PROGNOSTIC RISK SCALE FOR MORTALITY IN BREAST CANCER
Abstract
Relevance: Breast cancer is the most common malignancy in women and one of the leading causes of cancer-related mortality. Despite the availability of clinical and biological prognostic factors, developing simple, clinically applicable risk stratification tools remains an important challenge. The study aimed to identify factors associated with mortality in patients with breast cancer and to develop a prognostic model for individual risk assessment. Materials and Methods: We conducted a retrospective cohort analysis of 729 patients with primary breast cancer (registry data from 2018-2022). The study endpoint was mortality. At the time of analysis (January 2026), 185 deaths (25%) had been recorded. We used binary logistic regression to assess the independent contribution of variables to mortality risk. The model included functional status (Eastern Cooperative Oncology Group [ECOG] scale), disease stage (TNM classification), and molecular tumor phenotype. Model performance was evaluated using the chi-square test, Nagelkerke’s coefficient of determination, and the Hosmer–Lemeshow goodnessof-fit test. Results: The logistic regression model was statistically significant (χ² = 138.292; p < 0.001) and demonstrated satisfactory calibration (p = 0.505). All included variables remained independently associated with mortality. Functional limitations according to the ECOG scale increased the odds of mortality more than fourfold (odds ratio (OR) = 4.20; 95% CI 2.41-7.31; p < 0.001). Higher TNM stage was associated with increased mortality risk (OR = 1.51; 95% CI 1.35-1.69; p < 0.001). Molecular tumor phenotype was also identified as an independent prognostic factor (OR = 1.26; 95% CI 1.11-1.43; p < 0.001). Based on the regression coefficients, we developed a point-based prognostic scale to quantify individual mortality risk and stratify patients into risk groups. Conclusion: ECOG functional status, TNM stage, and molecular tumor phenotype independently predict mortality. The developed prognostic scale enables individualized risk assessment and may be used for clinical risk stratification of breast cancer patients.