Statistical Analysis of Factors Influencing Survival of Women with Breast Cancer by Treatment Types - Motuziuk, I. M.; Dumenko, O. M. (Statistics of Ukraine, 2020)
This article investigates breast cancer incidence in Ukraine. The research is based on National cancer-registry data. It describes the problem of treatment choice complexity and ambiguity between surgical treatment and combined surgical treatment. The paper examines two types of combined surgical treatment: a combination of surgery with radiotherapy and a combination of surgery with radiotherapy and chemotherapy. In order to determine the positive and negative effects of each type of treatment, we conducted statistical analysis. The analysis was based on female patients’ data from the National Cancer Institute. Based on the results, the study proved the relevance of survival analysis from the perspective of overall survival and progression-free survival by treatment type. The article describes the analysis and its findings on 5-year survival rates. Specifics of research with censored data and methodology of evaluating factor weights in the Kaplan – Meier method are described. It also describes the distribution of patients treated in the National Cancer Institute, which made it possible to build a representative sample. The sample was used to conduct a comparative analysis of survival rates among breast cancer patients by treatment type. We built survival curves for comparative analysis by treatment type. This helped define relevant 5-year survival rates among patients. The study analyzed a number of factors that could be significant and could influence breast cancer patients’ survival. Furthermore, we applied stratified analysis by treatment type and checked the hypothesis that there is no difference between the population survival curves by using Log-rank and Wilcoxon tests. Based on the study results, new possibilities for further analysis were described. The results could be used for patients’ survival modeling and for determining the relationship between risk factors when they are influenced by another one. The results will be helpful in determining recommendations about treatment type.