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

Area of Science:

• Oncology
• Plastic Surgery
• Decision Science

Background:

• Breast reconstruction post-mastectomy is increasingly common.
• Many women experience decision-making conflicts regarding breast reconstruction.
• Existing decision support may not fully address patient concerns.

Purpose of the Study:

• To develop and validate a decision tree model for breast reconstruction choices.
• To identify key factors influencing women's decisions on breast reconstruction.
• To assess the predictive accuracy of the developed model.

Main Methods:

• A mixed-methods approach using ethnographic decision tree modeling.
• Qualitative stage: Individual and focus group interviews to construct the model.
• Quantitative stage: Questionnaire development and validation with 61 breast cancer patients.

Main Results:

• Five major criteria emerged: body image recovery, recurrence impact, social recommendations, finances, and physician confirmation.
• The decision tree model included nine predictive pathways.
• The model accurately predicted 90% of decisions regarding breast reconstruction.

Conclusions:

• The five identified criteria are crucial for breast reconstruction decision-making.
• The developed decision tree model demonstrates high predictability.
• Interventions should integrate these key criteria to support women's optimal breast reconstruction choices.