The efficient evaluation of fusion algorithms becomes particularly important when different fusion schemes have to be compared with respect to an underlying performance metric. In this paper, we present explicit expressions for the global error probabilities of sensor fusion with side information for distributed detection applications. In the considered distributed detection problem, the sensors compress their observations independently and transmit local decisions to a fusion center that combines the received decisions with respect to available side information and computes the final detection result. In the special case of identical sensors, computationally efficient expressions are obtained by using the multinomial distribution. Numerical results reveal the influence of different qualities of side information on the overall detection performance.