DUGi

Cost-effectiveness evaluation of the DIEP flap and the expander implant for immediate breast reconstruction after mastectomy a multicentred 10 year-retrospective cohort study

http://dugi.udg.edu/item/http:@@@@hdl.handle.net@@10256@@19933

BACKGROUND: Breast cancer is the most common cancer in women in Western countries. One of the surgical treatments for most breast cancer stages still is the mastectomy yet its functional, psychological and aesthetical consequences require immediate breast reconstruction. Between the two most currently used reconstruction techniques -the expander-implant and the DIEP flap-, greater aesthetical outcomes and best quality of life have been achieved using the DIEP flap although expander-implant is still highly routinely performed. In the context of a public healthcare system and taking into account that both techniques are accepted for breast reconstruction, analysing their economic impact would help optimizing resources and could be decisive when choosing the best breast reconstruction technique. OBJECTIVE: the aim of this cost-effectiveness analysis is to determine the most cost- effective technique as well as to provide useful information when deciding to perform a breast reconstruction, in order to optimize financial resources. DESIGN AND METHODS: this study is a multicentred 10-year retrospective cohort and will be performed in 4 hospitals in Catalunya, detailed in chapters below. PARTICIPANTS: 150 women over 18 years that were submitted to total mastectomy and immediate breast reconstruction using expander-implant or DIEP flap between 2001 and 2011 in any hospitals participating, organized in two cohort of 75 person each. METHODS: data related to patients will be collected through clinical history and financial data will be obtained from Hospital’s Budget for 2020. Data will be analysed and represented into a statistical analysis plan in order to compare cost-effectiveness between both techniques. Statistical representation of variables will also be performed through a univariate, bivariate and multivariate analysis