OBJECTIVES: With the developing of new technology for genetic test, the accuracy of predicting the risk that a patient may diagnose with breast cancer in future was increased dramatically. But considering that after diagnosis with breast cancer, those women has doubled prevalence of diagnosed with depression compared with general female population, and the anxiety patient suffered after realized taking specific mutations, which high likely led to breast cancer, before really diagnosed with breast cancer. There is no doubt that depression is a serious issue for patient with high risk of developed breast cancer. Moreover, the drug interaction between antidepressants and tamoxifen reduces the effect of tamoxifen, and complicates the decision-making. This cost-effectiveness study tries to use Markov model to investigate the best strategy that gives to high-risk breast cancer patients after genetic test and diagnosed with breast cancer. METHODS: A cost-effectiveness study using Markov model will be conducted from a third payer perspective. Both time and different antidepressants from desipramine, fluoxetine, paroxetine, mianserin, melatonin to escitalopram will be included in this study as different exposure. Life-long quality of life will be calculated as outcome. In order to investigate the extent of accuracy, one way sensitivity analyses and probabilistic sensitivity analysis will be conducted. RESULTS: Mianserin, melatonin does not interfere with tamoxifen treatment, under that situation, these medication have the best outcome. The time period from diagnosed with breast cancer till 1 year is the best timing to give antidepressants, which may significantly change the outcome. CONCLUSIONS: Even though, sometimes patients with breast cancer may not realize they already threaten by depression, the antidepressant still significantly important to breast cancer population to prevent the progression of depression with better outcome.