OBJECTIVES To explore the impact of different utility measurement strategies on the results of a cost-effectiveness analysis, funding decisions, decision uncertainty and value of information. METHODS Data from a UK trial of two cancer therapies (active versus standard care) were analysed using NICE reference case methods. Within-trial, cost-utility analyses were conducted with utility based on a number of strategies: A) Observed EQ-5D; cancer-specific utility based on the EORTC QLQ-C30 B) the EORTC-8D and C) the QLQ_U; Mapping from QLQ-C30 to EQ-5D using an algorithm generated in D) the same cancer patient group and E) a different cancer group. Incremental cost-effectiveness ratios (ICERS) were calculated. Bootstrapped net benefit estimates allowed generation of cost-effectiveness acceptability curves (CEACs) and population expected value of perfect information (EVPI) was calculated using incremental cost scenarios. Results were compared across utility strategies. RESULTS There were small but important differences observed in the incremental QALYs which ranged from 0.067 (EQ-5D) to 0.036 (EORTC-8D). Large differences were observed in the ICERs generated; for strategies A to E these were: £57,513; £106,264; £102,785; £90,049; £78,885. Using an incremental cost scenario of £3,000 only strategy A yielded an ICER <£30,000. At a QALY willingness to pay threshold (WTPT) of £20,000 there was little decision uncertainty. However, assuming WTPT=£50,000, the probability the active treatment was cost-effective ranged 0.34 (EQ-5D) to 0.025 (EORTC-8D). Using this threshold, the population EVPI for the strategies were: £3,597,844; £120,621; £155,858; £354,094; £805,847.  CONCLUSIONS Different utility sources can lead to very different estimates of cost-effectiveness and value of further research and change funding decisions. Estimates of cost-effectiveness based on mapping (even when the algorithm appears to perform well) can differ substantively from those based on observed scores. The lowest ICERs were obtained with the EQ-5D but this may not capture side-effects picked up by the cancer-specific utility measures.