{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T20:26:21Z","timestamp":1784838381797,"version":"3.55.0"},"reference-count":64,"publisher":"SAGE Publications","issue":"5","license":[{"start":{"date-parts":[[2013,2,19]],"date-time":"2013-02-19T00:00:00Z","timestamp":1361232000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Stat Methods Med Res"],"published-print":{"date-parts":[[2014,10]]},"abstract":"<jats:p>A patient-reported outcome is any report on the status of a patient\u2019s health condition that comes directly from the patient. Clear and meaningful interpretation of patient-reported outcome scores are fundamental to their use as they can be valuable in designing studies, evaluating interventions, educating consumers, and informing health policy makers involved with regulatory, reimbursement, and advisory agencies. Interpretation of patient-reported outcome scores, however, is often not well understood because of insufficient data or lack of experience or clinical understanding to draw from. This article provides an update review on two broad approaches \u2013 anchor-based and distributed-based \u2013 aimed at enhancing the understanding and meaning of patient-reported outcome scores. Anchor-based approaches include percentages based on thresholds, criterion-group interpretation, content-based interpretation, and clinical important difference. Distributed-based approaches include effect size, probability of relative benefit, and responder analysis and cumulative proportions. A third strategy called mediation analysis, which can elucidate a health condition measured by a patient-reported outcome in the context of an intervention\u2019s mechanism of action, is also highlighted and illustrated. Mediation analysis in the context of interpretation of patient-reported outcome scores is a relatively new development. The logic and rationale of the three methods are expressed generally. While the three approaches themselves are not new, some applications of them taken from their examples published in the past few years are original and coalesced in this article to add real-life implications of the different methodologies in one integrated report.<\/jats:p>","DOI":"10.1177\/0962280213476377","type":"journal-article","created":{"date-parts":[[2013,2,20]],"date-time":"2013-02-20T22:27:05Z","timestamp":1361399225000},"page":"460-483","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":71,"title":["Interpretation of patient-reported outcomes"],"prefix":"10.1177","volume":"23","author":[{"given":"Joseph C","family":"Cappelleri","sequence":"first","affiliation":[{"name":"Pfizer Inc, Groton, CT, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrew G","family":"Bushmakin","sequence":"additional","affiliation":[{"name":"Pfizer Inc, Groton, CT, 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