A Decision Tree Model for Breast Reconstruction of Women with Breast Cancer: A Mixed Method Approach

Author:

Park Eun YoungORCID,Yi MyungsunORCID,Kim Hye SookORCID,Kim HaejinORCID

Abstract

The number of breast reconstructions following mastectomy has increased significantly during the last decades, but women are experiencing a number of conflicts with breast reconstruction decisions. The aim of this study was to develop a decision tree model of breast reconstruction and to examine its predictability. Mixed method design using ethnographic decision tree modeling was used. In the qualitative stage, data were collected using individual and focus group interviews and analyzed to construct a decision tree model. In the quantitative stage, the questionnaire was developed questions based on the criteria identified in the qualitative stage. A total of 61 women with breast cancer participated in 2017. Five major criteria: recovery of body image; impact on recurrence; recommendations from others; financial resources; and confirmation by physicians. The model also included nine predictive pathways. It turns out that the model predicted 90% of decisions concerning whether or not to have breast reconstruction. The findings indicate that the five criteria play a key role in decision-making about whether or not to have breast reconstruction. Thus, more comprehensive issues, including these five criteria, need to be integrated into an intervention for women with breast cancer to make their best decision on breast reconstruction.

Publisher

MDPI AG

Subject

Health, Toxicology and Mutagenesis,Public Health, Environmental and Occupational Health

Reference47 articles.

1. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries

2. 2020 Breast Cancer Facts and Figureshttp://www.kbcs.or.kr/journal/file/210107.pdf

3. Health Care Big Data Open System. National Interest Medical Practices (Examination and Procedure) Statisticshttp://opendata.hira.or.kr/op/opc/olapMfrnIntrsDiagBhvInfo.do

4. Nationwide Trends in Mastectomy for Early-Stage Breast Cancer

5. Patient-Reported Outcomes of Breast Reconstruction after Mastectomy: A Systematic Review

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