There are many options for breast cancer (lat. Carcinoma) treatment, with the optimal choice depending on stage, grade, type, and prognosis. Early and accurate detection and classification can greatly increase the chances of treatment success, but current prognostic tests for breast cancer are limited to certain types and stages of cancer and their accuracy is limited. However, scientists, led by Professor Dimitris Anastassiou at Columbia University developed an algorithm (called BCAM) that uses a set of metagenes (linear combinations of individual genes that are biomarkers for underlying biological mechanisms) to provide prognostic information for any stage and type of cancer in a single test. This technology could be utilized as an integrated breast cancer test for individualized prognosis to determine optimal treatment for breast cancer patients.