OBJECTIVES: The purpose of meta-analysis is to derive pooled utility in different stages of breast cancer and to assess the relative impacts of study design characteristics in predicting utilities for breast cancer. METHODS:  We searched Medline, Embase, RISS, and KoreaMed to find out literatures reporting all publicly available utilities for breast cancer. Twenty six articles were identified reporting 124 unique utilities. We extracted 13 variables which were given in the articles: 1)mean utility weight 2) standard errors 3)assessment methods 4)disease stages 5)types of respondents, 6)number of respondents 7) countries of the respondents 8) age of the respondents 9)treatment methods 10)the lower bounds 11)the upper bounds of the scale 12)survey methods 13) survey origin. We performed a meta-regression with above variables being independent variables.  RESULTS: We found that the pooled utility was 0.6995 for the total breast cancer, 0.8254 for the early stage, 0.711 for the locally advanced stage, and 0.5569 for the recurrent and metastatic stage(P<0.0001). Assessment method, survey origin and respondent type show significant differences in the early stage(P<0.05), survey origin, survey method, and the lower and upper bound for the scale were significant in the recurrent and metastatic stage(P<0.05). The results of the regression analysis revealed that the severity of breast cancer, assessment method, and survey origin were significant predictors of quality of life while respondent type, age, survey method, and the lower and upper bound of the scale were not significant. Utility weight for recurrent and metastatic stage was lower than the values which was estimated for the early stage(P<0.0001). Utility weight estimated with scenario was lower than the results with own health status(P<0.05). CONCLUSIONS: Quality of life estimates for breast cancer show different values in the same health status by assessment method, survey origin, survey method, and respondent type.