Economic evaluations of chronic obstructive pulmonary disease (COPD) incorporate utilities through multi-attribute utility (MAU) measures, most commonly the EQ-5D, to report health-related quality-of-life (HR-QOL) changes or differences. Questions have been raised about the sensitivity of these measures in COPD. Limitations in detecting adequate patient-level changes in HR-QOL over time in stable and exacerbation states compared with disease-specific instruments could also result in underestimation of known treatment benefits. The purpose of this article was to present and discuss the empirical evidence on the validity of generic MAU measures within the COPD population. We built upon a previously conducted validation review for the period 1997-2007 that used 'respiratory disease' and 'EQ-5D' as keywords. For this discussion, PubMed and EMBASE databases were searched for articles in English from 1988 to August 2009, using similar search words. Based on the performance of MAU measures in COPD and exacerbations, they appear to have limited discriminatory ability, particularly between moderate and severe COPD, despite known differences in HR-QOL. Sensitivity to clinically relevant change in stable COPD over time due to treatment also appears limited. Current research suggests adequate sensitivity regarding detecting the onset and resolution of an exacerbation; however, sensitivity is limited in the short term, such as daily changes in health status. The evidence suggests responsiveness of MAU measures may be restricted to large within-patient change, which leads to difficulties in evaluating the subtle but important impact of exacerbations. Studies presenting alternative methods of deriving COPD-related utilities are also discussed. Overall, the insensitivities of generic MAU measures in COPD can lead to biased cost-effectiveness analyses and ill-informed economic decisions. Alternative measures such as condition-specific preference-based measures may be used in circumstances where more sensitivity is needed. The trade-off allows relevant and sensitive matters most important to patients to be evaluated; however inevitable gaps such as those related to adverse events are not considered.