We consider the 0-1 Knapsack Problem with Setups (KPS). Items are grouped into families and if any items of a family are packed, this induces a setup cost as well as a setup resource consumption. We introduce a new dynamic programming algorithm which performs much better than a previous dynamic program and turns out to be also a valid alternative to an exact approach based on the use of an ILP solver. Then we present a general inapproximability result. Furthermore, we investigate several relevant special cases which still permit fully polynomial time approximation schemes (FPTASs) and others where the problem remains hard to approximate.