OBJECTIVES: The clinical trial programme for Prucalopride, a selective and high affinity 5-HT4 receptor agonist, incorporated a constipation specific HRQoL measure (PAC-QOL) and SF-36 but not EQ-5D. A mapping relationship was developed to link EQ-5D to PAC-QOL using established algorithms linking EQ-5D and SF-36. METHODS: Trial responses (n=5488) on a common patient dataset enabled an empirical link to be established between the SF-36 and PAC-QOL which was extended to EQ-5D through the established algorithm. Having established this relationship a range of functional forms for mapping PAC-QOL onto EQ-5D were tested ranging from a simple linear relationship to more complex mapping structures incorporating quadratic and interactive terms. RESULTS: The relationship between PAC-QOL and EQ-5D was generally good. The estimated equation for deriving EQ-5D from PAC-QOL in its’ simplest linear functional form was:  EQ-5D = 97.7 – 9.8 (PAC-QOL). This implies that a one point change in PAC-QOL overall score would lead to a 9.8% change in EQ-5D. As expected, the mapping was largely limited to the upper health states of EQ-5D given that chronic constipation by itself is unlikely to lead to the severest forms of disability. This initial regression analysis displayed elements of non-linearity and hence a more complex analysis was undertaken which incorporated square and interaction terms. This new functional form facilitated a more accurate relationship to be established between PAC-QOL and EQ-5D. CONCLUSIONS: Mapping is required whenever a preference based generic HRQoL measure is not directly collected in clinical trials. Very limited theoretical guidance is available to structure such analyses and therefore empiricism largely rules. However by testing the robustness of the results to different assumptions and functional forms a robust mapping can be developed. This process was employed here to convert PAC-QOL into EQ-5D utility scores for incorporation into Cost Utility analyses.