DETERMINATION OF POOR OUTCOME PROGNOSIS IN PATIENT WITH ACUTE LEUCEMIA WHICH WAS COMPLICATED BY PNEUMONIA

Abstract

Introduction: At the present stage, the medicine development is based on the principles of evidence-based medicine, which requires using of statistical methods and forecasting. Using statistical analysis and possibilities and mathematical forecasting emphasizes the probability of obtained data in scientific medical research. Identifying the factors that determine the survival of patients with acute leukemia and pneumonia causes the conduct of this study. The aim: To create a mathematical model of poor outcome prognosis in patients with acute leukemia, which was complicated by pneumonia, to determine the treatment place and timely optimize the treatment. Materials and methods: An electronic database of formalized disease history of 360 patients with acute leukemia and pneumonia was created. The data base contained data of objective survey and additional research methods. In our study we used non-parametric dispersion analysis of Kraskele-Wallis, correlation analysis with the calculation of Spierman’s rank correlation coefficients, simple and multiple logistic regression analysis with the calculation of the odds ratio; ROC analysis. The significance level p <0,05 was considered statistically significant. Results: It was determined that with the onset of the lethal outcome of patients with pneumonia, developed on the background of acute leukemia, the indicators of leukocytes, lymphocytes, neutrophils, platelets, erythrocytes, hemoglobin and immunity indexes (B(CD19+), T(CD4+), CD4+/CD8+, IgG). According to the results of our study, a mathematical model of prediction poor outcome in patients with acute leukemia, which was complicated by pneumonia, was created: PPO=exp(-10,317+0,410* В(CD19+) -2,149* IgG)/ [1+exp(-10,317+0,410* В(CD19+) -2,149* IgG)]. Conclusion: Using in clinical practice the proposed mathematical model of prediction poor outcome in patients with acute leukemia, which was complicated by pneumonia, will allow determining the treatment place and timely optimizing the treatment program.