Purpose: Breast cancer is a disease with high mortality and morbidity. The effectiveness and costs of the actual treatments for breast cancer depend strongly on the stage of the disease at which it is detected. A late detection is more expensive than an early detection, and it could provide less benefit to the patient’s health. This work develops a Discrete Event Simulation model programmed in Arena® to evaluate the appropriate moment to perform a biopsy to women who are at risk of developing breast cancer.
Method: The model simulates patient’s disease progression, based on her risk of developing breast cancer in order to decide if perform a biopsy at the year of the exam or wait until next year. When for a specific woman the model decides not to perform the biopsy, it estimates the remaining lifetime of the patient. The model also estimates the life years added by the treatment to a specific woman depending on the stage of the breast cancer when it is detected, and on the cost associated if waits next year or if begin the treatment in this moment. Finally, a cost-effectiveness analysis is performed to decide when to make the biopsy.
Result: For the first years of the estimation the alternative “wait next year” is more cost-effective for almost every case, but as the cancer progresses, the alternative “make the biopsy” is more effective but more expensive. In the latter, the model estimates the cost of another life year and the decision maker has to decide based on the result. Disease progression parameters were obtained from published data; only direct medical costs were considered and were based on local information.
Conclusion: The model helps the decision maker to konw when to perform the biopsy is cost-effective.
See more of: The 32nd Annual Meeting of the Society for Medical Decision Making