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Title: Evidence-based interpretation guidelines for quality of life measures
Author: Cocks, Kim
ISNI:       0000 0004 2724 3387
Awarding Body: University of Leeds
Current Institution: University of Leeds
Date of Award: 2011
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Aim: To use published literature to obtain estimates of large, medium and small differences in quality of life (QOL) data for the European Organisation for the Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (EORTC QLQ-C30). Methods: An innovative method combining systematic review of published studies, expert opinions and meta-analysis was used to obtain estimates of large, medium and small differences for QLQ-C30 scores. Published mean data were identified from the literature. Differences between groups of patients and over time within patients were reviewed by 34 experts in QOL measurement and cancer treatment. The experts, blinded to QOL results, were asked to predict these differences. Differences were combined using meta-analytic techniques to obtain estimates of small, medium and large effects. Qualitative interviews with patients and experts were used to assess the new methodology. Results: 911 articles were identified, with 211 relevant articles (3444 contrasts) for the analysis. Our systematic reviewof the randomised controlled trials (RCTs) showed that the clinical relevance of QOL differences was rarely discussed. Our meta-analysis estimates varied depending on the subscale and on whether QOL was improving or deteriorating. Thus, the recommended minimum to detect medium differences between groups ranges from 7 (diarrhoea) to 19 points (role functioning). When interpreting differences over time a minimum of 7 points represents a medium difference but for most subscales a larger difference is required for a medium deterioration compared with a medium improvement. Conclusion: Guidelines for interpreting the size of effects are provided for the QLQ- C30 subscales. These guidelines can be used for sample size calculations for clinical trials and to interpret differences in QLQ-C30 scores. The novel methodology was shown to be robust in sensitivity analyses but benefitted from a thorough quality assessment and using only the best quality evidence to derive the guidelines.
Supervisor: Brown, Julia ; King, Madelaine ; Fayers, Peter Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available