A review of selected patient-generated outcome measures and their application in clinical trials
- PMID: 14627066
- DOI: 10.1046/j.1524-4733.2003.65236.x
A review of selected patient-generated outcome measures and their application in clinical trials
Abstract
Background: Patient-generated outcome measures have been developed in an effort to capture the individualistic nature of health-related quality of life (HRQoL). These measures differ from traditional HRQoL instruments in that they allow patients to individually define HRQoL domains or weights. Nevertheless, application of these measures may be challenging, particularly in a clinical trial setting.
Objective: The objective of this study was to provide a critical review of the following patient-generated outcome measures: Patient-Generated Index (PGI), Schedule for the Evaluation of Individual Quality of Life (SEIQoL), Repertory Grid, and Asthma Quality of Life Questionnaire (AQLQ).
Methods: We conducted a systematic literature review of the Medline and Olga databases and the journal Quality of Life Research and consulted experts. We abstracted data from eligible studies on the instruments' content, psychometric properties, and applicability in a clinical trial setting.
Results: The SEIQoL has shown to be reliable, valid, and responsive, but the PGI has not. Both instruments have poor practicality and have not been used in a clinical trial. The Repertory Grid's psychometric properties have not been well studied. The AQLQ is in part patient-generated and has been used in clinical trials. Nevertheless, the practicality of the individualized section is poor owing to the issue of missing data. All four instruments fail to provide a form of standardization needed for estimating population effects in a clinical trial.
Conclusion: The applicability of patient-generated outcome measures in a clinical trial setting remains questionable. Patient-generated outcome measures appear to be useful primarily in complementing traditional HRQoL measures, guiding individual patient treatment decisions, and assisting the design of new measures.
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