OBJECTIVES: In deciding about coverage of new medical technology, multiple clinical outcomes are used to support reimbursement claims. Neither the real world value nor the relevance of these outcome measures for patients is systematically assessed. Hence, there is growing interest in the use of patient-reported outcome measures. Multi-criteria decision analysis, like the analytic hierarchy process (AHP), is a technique to elicit patient preferences. In the present study we used AHP to prioritize patient relevant endpoints related to the use of antidepressants in major depression.  METHODS: Patient relevant endpoints of treatment (remission of depression, response to treatment, no relapse, serious adverse events, adverse events, social function, anxiety, pain, cognitive function) were prioritized using pairwise comparisons of these outcomes. In two separate groups, twelve patients and seven experts judged on a 9 point scale the relative importance of pairs of two outcome measures. The geometric mean of these judgments was used to derive weighting factors for the outcome measures (scale 0-1). RESULTS: Of all outcome measures, patients rated response to treatment highest (0.32), while experts rated remission of depression highest (0.48). Adverse events were all rated lowest by patients as well as by experts, and disease-specific quality of life domains such as social function (0.11 & 0.09), anxiety (0.12 & 0.05) and cognitive function (0.13 & 0.06) were rated in between.  CONCLUSIONS: The most important outcome measures according to the patients are, in order of decreasing importance: response, cognitive function, no anxiety, social function, no relapse, no adverse events, and remission. The AHP appears to be suitable in gaining an overview of the importance of patient relevant outcome measures. An additional advantage of AHP is that the group discussions offer insight in the question why the endpoints are important.