EQ-5D Based Utility Values for Adults with Chronic Obstructive Pulmonary Disease: A Systematic Review, Meta-Analysis, and Meta-Regression.

Chronic obstructive pulmonary disease (COPD) is a common lung disease that negatively affects health-related quality of life (QoL). Utility values, which measure QoL by weighting health states with societal preferences, are required for the cost-utility models that drive economic evaluations and policy decisions. Moayeri et al. published a systematic review and meta-analysis of utilities (EQ-5D) in COPD in June 2016. The current study investigated changes in mean utilities in more recent studies thereafter, exploring heterogeneity in utilities across diverse clinical and study characteristics. Systematic searches of databases, such as MEDLINE and Embase were undertaken from 1 July 2015 until 20 May 2024. A random-effects meta-analysis of utilities (EQ-5D) was performed which addressed inter-study heterogeneity and subgroup analyses. The pooled general mean (95% CI) utility value was 0.761 (0.726-0.795) from 43 studies, whereas Moayeri et al. reported 0.673 (0.653-0.693) from 32 studies. This improvement in mean utilities could be due to increased awareness, early detection, and better medical interventions over the past decade, but demonstrates that a general utility value should be approached with caution given significant heterogeneity. Four meta-regressions were performed on each subgroup: region, method of elicitation, reported comorbidities, and disease stage; of which, method of elicitation, disease stage, and region were found to be significant moderators of utilities. It is, therefore, important to use meta-analysed utilities for cost-utility analyses that reflect the context and patient population of the model. Moreover, these results provide additional evidence for the precision and sensitivity of EQ-5D-5L over EQ-5D-3L.

The INVEST project: investigating the use of evidence synthesis in the design and analysis of clinical trials.

BACKGROUND: When designing and analysing clinical trials, using previous relevant information, perhaps in the form of evidence syntheses, can reduce research waste. We conducted the INVEST (INVestigating the use of Evidence Synthesis in the design and analysis of clinical Trials) survey to summarise the current use of evidence synthesis in trial design and analysis, to capture opinions of trialists and methodologists on such use, and to understand any barriers. METHODS: Our sampling frame was all delegates attending the International Clinical Trials Methodology Conference in November 2015. Respondents were asked to indicate (1) their views on the use of evidence synthesis in trial design and analysis, (2) their own use during the past 10 years and (3) the three greatest barriers to use in practice. RESULTS: Of approximately 638 attendees of the conference, 106 (17%) completed the survey, half of whom were statisticians. Support was generally high for using a description of previous evidence, a systematic review or a meta-analysis in trial design. Generally, respondents did not seem to be using evidence syntheses as often as they felt they should. For example, only 50% (42/84 relevant respondents) had used a meta-analysis to inform whether a trial is needed compared with 74% (62/84) indicating that this is desirable. Only 6% (5/81 relevant respondents) had used a value of information analysis to inform sample size calculations versus 22% (18/81) indicating support for this. Surprisingly large numbers of participants indicated support for, and previous use of, evidence syntheses in trial analysis. For example, 79% (79/100) of respondents indicated that external information about the treatment effect should be used to inform aspects of the analysis. The greatest perceived barrier to using evidence synthesis methods in trial design or analysis was time constraints, followed by a belief that the new trial was the first in the area. CONCLUSIONS: Evidence syntheses can be resource-intensive, but their use in informing the design, conduct and analysis of clinical trials is widely considered desirable. We advocate additional research, training and investment in resources dedicated to ways in which evidence syntheses can be undertaken more efficiently, offering the potential for cost savings in the long term.