Use of statistical analysis, data mining, decision analysis and cost effectiveness analysis to analyze medical data: Application to comparative effectiveness of lumpectomy and mastectomy for breast cancer

TL;DR: Data mining, decision analysis and cost effectiveness analysis methods were used to supplement statistical models in comparing lumpectomy to mastectomy for surgical treatment of breast cancer.

Abstract: USE OF STATISTICAL ANALYSIS, DATA MINING, DECISION ANALYSIS AND COST EFFECTIVENESS ANALYSIS TO ANALYZE MEDICAL DATA: APPLICATION TO COMPARATIVE EFFECTIVENESS OF LUMPECTOMY AND MASTECTOMY FOR BREAST CANCER Beatrice Ugiliweneza November 4t\ 2011 Statistical models have been the first choice for comparative effectiveness in clinical research. Though effective, these models are limited when the data to be analyzed do not fit the assumed distributions; which is mostly the case when the study is not a clinical trial. In this project, data mining, decision analysis and cost effectiveness analysis methods were used to supplement statistical models in comparing lumpectomy to mastectomy for surgical treatment of breast cancer. Mastectomy has been the gold standard for breast cancer treatment for since the 1800s. In the 20 century, an equivalence of mastectomy and lumpectomy was established in terms of long-term survival and disease free survival. However, short term comparative effectiveness in post-operative outcomes has not been fully explored. Studies using administrative data are lacking and no study has used new technologies of self-expression, particularly the internet discussion board. In this study, data used were from the Nationwide Inpatient