Estimating effect sizes for health-related quality of life outcomes. (October 2014)

• Record Type: Journal Article
• Authors: Julious, Steven A; Walters, Stephen J
• Other Names: Kammerman Lisa A guest-editor.; Grosser Stella guest-editor.
• Is Part Of: Statistical methods in medical research. Volume 23:Number 5(2014:Oct.)
• Page Start: 430
• Page End: 439
• Publication Date: 2014-10
• Subjects: Sample size -- health-related quality of life -- patient-reported outcomes; Medicine -- Research -- Statistical methods -- Periodicals; Research -- Periodicals; Review Literature -- Periodicals; Statistics -- methods -- Periodicals; Médecine -- Recherche -- Méthodes statistiques -- Périodiques; 610.727
• DOI: 10.1177/0962280213476379
• Languages: English
• ISSNs: 0962-2802

Abstract

Summary: To enable an assessment of the costs and benefits of a new health technology one should use a range of outcome measures, including medical, psychosocial and economic. Therefore, unless a patient-reported outcome as well as clinical outcome is assessed in a study, the effect of a health technology on the patient will remain unknown as two therapies may have similar clinical consequences but different impacts upon the quality of the life of the patients. An important issue when designing a study with a new patient-reported outcome is the quantification of an effect size. Through a case study we highlight how simple calculations can enable the estimation of the effect sizes if there is information on established outcomes. This is done by mapping changes on the new scale to clinically relevant and important changes on established scales. We recommend the approaches described in this paper be considered for the quantification of important treatment effects when designing a clinical trial with a new patient-reported outcome measure.