Using decision theory for precise choice of breast cancer treatment The precise choice of treatment for breast cancer depends upon the status of the hormone receptors (for estrogen and progesterone). Their conventional determination by means of immunohistochemistry (IHC) is associated with a certain error rate, which can be reduced by adding genomic data. Even conventional statistics can bring about a notable improvement but now it is possible to use decision theory to optimally combine diagnostic findings, particularly where they are contradictory. This is the finding of a recent study conducted by MedUni Vienna under the leadership of Wolfgang Schreiner from the Center for Medical Statistics, Informatics and Intelligent Systems (CeMSIIS).