Socio-economic quality of life differences among the breast cancer patients

Aim of the study: To evaluate the socio-economic differences among the breast cancer patients. Methods: The MSc work was performed in analyzing the quality of life data obtained from EORTC QLQ-C30 and EQ-5D questionnaires, in such a way entering to the Breast cancer economic evaluation study performed in The Department of Prophylactic Medicine. After calculating the EQ-5D utilities and other EORTC quality of life indexes the analysis of investigating how the quality of life is influenced by different socio-economic conditions was performed. The main comparative criteria were: the stage of breast cancer, the year of diagnosis, marital status, age, education, monthly income and the rural/urban surrounding. The total sample size of the study consisted of 284 respondents. The mathematical/statistical analysis was performed using Microsoft Excel 2003 and SPSS 12.0. The main statistical criteria used in the data analysis were: Student (t), Chi Square, Mann-Whitney U, One way ANOVA, post hock LZD tests, and Spearman’s correlation coefficient. The statistical significance level was set at p<0.05. Results: The global quality of life measures such as the EQ-5D utilities, EQ VAS, and the EORTC global health status scale were relatively similar; however, they were significantly smaller when comparing to the results published in the scientific literature. When comparing the indexes of the entire sample, such criteria as EQ-5D “mobility” and “self care” dimensions, and EORTC cognitive and physical functioning were valued relatively better than the others. Alternatively, EQ-5D “anxiety/depression”, EORTC emotional functioning, insomnia, fatigue, and especially – financial difficulties scale, were valued as the criteria representing the worst quality of life points. Living with partner, having a higher or high education and higher income (more than 1000 lt/month), being younger than 70 years old, and having the lower stage of breast cancer were the significant predictors of overall better quality of life (p