Quality of life and cost-effectiveness of different breast cancer surgery procedures: a Markov decision tree-based approach in the framework of Predictive, Preventive, and Personalized Medicine.

Purpose: Breast cancer is a complex disease with heterogeneous outcomes that may benefit from the implementation of Predictive, Preventive, and Personalized Medicine (PPPM/3PM) strategies. In this study, we aimed to explore the potential of PPPM approaches by investigating the 10-year trends in quality of life (QOL) and the cost-effectiveness of different types of surgeries for patients with breast cancer.

Methods: This prospective cohort study recruited 144 patients undergoing breast conserving surgery (BCS), 199 undergoing modified radical mastectomy (MRM), and 44 undergoing total mastectomy with transverse rectus abdominis myocutaneous flap (TRAMF) from three medical centers in Taiwan between June 2007 and June 2010.

Results: All patients exhibited a significant decrease in most QOL dimension scores from before surgery to 6 months postoperatively (p < 0.05); however, from postoperative year 1 to 2, improvement in most QOL dimension scores was significantly better in the TRAMF group than in the BCS and MRM groups (p < 0.05). At 2, 5, and 10 years after surgery, the patients' QOL remained stable. In the Markov decision tree model, the TRAMF group had higher total direct medical costs than the MRM and BCS groups (US$ 32,426, US$ 29,487, and US$ 28,561, respectively) and higher average QALYs gained (7.771, 6.773, and 7.385, respectively), with an incremental cost-utility ratio (ICUR) of US$ 2,944.39 and US$ 10,013.86 per QALY gained.

Conclusions: TRAMF appeared cost effective compared with BCS and MRM, and it has been proved with considerable QOL improvements in the framework of PPPM. Future studies should continue to explore the potential of PPPM approaches in breast cancer care. By incorporating predictive models, personalized treatment plans, and preventive strategies into routine clinical practice, we can further optimize patient outcomes and reduce healthcare costs associated with breast cancer treatment.

Supplementary information: The online version contains supplementary material available at 10.1007/s13167-023-00326-4.