Abstract
When there are no randomised clinical trials directly comparing all relevant treatment options, an indirect treatment comparison via meta-analysis of the available clinical evidence is an acceptable alternative. However, meta-analyses may be very misleading if not adequately performed. Here, we propose and validate a simple and effective approach to meta-analysis for exploring the effectiveness of long-acting β2-agonist (LABA)/long-acting muscarinic antagonist (LAMA) fixed-dose combinations in chronic obstructive pulmonary disease.
14 articles with 20 329 patients (combinations n=9292; monocomponents n=11 037) were included in this study. LABA/LAMA combinations were always more effective than the monocomponents in terms of the improvement in trough forced expiratory volume in 1 s, transition dyspnoea index and St George's Respiratory Questionnaire scores after 3, 6 and 12 months of treatment. No significant publication bias was identified. Significant discrepancies with previous network meta-analyses have been found, with overall differences ranging from 26.7% to 43.3%.
Results from previous network meta-analyses were misleading because no adequate attention was given to formulating the review question, specifying eligibility criteria, correctly identifying studies, collecting appropriate information and deciding what it would be pharmacologically relevant to analyse. The real gradient of effectiveness of LABA/LAMA fixed-dose combinations remains an unmet medical need; however, it can be investigated indirectly using a high-quality meta-analytic approach.
Abstract
We propose a simple and effective meta-analytic approach for exploring the impact of LABA/LAMA combinations in COPD http://ow.ly/8Zd9302154B
Footnotes
This article has supplementary material available from err.ersjournals.com
Support statement: This study was supported by institutional funds (University of Rome Tor Vergata).
Conflict of interest: Disclosures can be found alongside this article at err.ersjournals.com
Provenance: Submitted article, peer reviewed.
- Received April 27, 2016.
- Accepted June 24, 2016.
- Copyright ©ERS 2017.
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