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  5. Efficacy and safety profile of xanthines in COPD: a network meta-analysis

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Article
en
2018

Efficacy and safety profile of xanthines in COPD: a network meta-analysis

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en
2018
Vol 27 (148)
Vol. 27
DOI: 10.1183/16000617.0010-2018

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Peter J Barnes
Peter J Barnes

Imperial College London

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Mario Cazzola
Luigino Calzetta
Peter J Barnes
+4 more

Abstract

Theophylline can still have a role in the management of stable chronic obstructive pulmonary disease (COPD), but its use remains controversial, mainly due to its narrow therapeutic window. Doxofylline, another xanthine, is an effective bronchodilator and displays a better safety profile than theophylline. Therefore, we performed a quantitative synthesis to compare the efficacy and safety profile of different xanthines in COPD. The primary end-point of this meta-analysis was the impact of xanthines on lung function. In addition, we assessed the risk of adverse events by normalising data on safety as a function of person-weeks. Data obtained from 998 COPD patients were selected from 14 studies and meta-analysed using a network approach. The combined surface under the cumulative ranking curve (SUCRA) analysis of efficacy (change from baseline in forced expiratory volume in 1 s) and safety (risk of adverse events) showed that doxofylline was superior to aminophylline (comparable efficacy and significantly better safety), bamiphylline (significantly better efficacy and comparable safety), and theophylline (comparable efficacy and significantly better safety). Considering the overall efficacy/safety profile of the investigated agents, the results of this quantitative synthesis suggest that doxofylline seems to be the best xanthine for the treatment of COPD.

How to cite this publication

Mario Cazzola, Luigino Calzetta, Peter J Barnes, Gerard J. Criner, Fernando J. Martínez, Alberto Papi, Maria Gabriella Matera (2018). Efficacy and safety profile of xanthines in COPD: a network meta-analysis. , 27(148), DOI: https://doi.org/10.1183/16000617.0010-2018.

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Publication Details

Type

Article

Year

2018

Authors

7

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1183/16000617.0010-2018

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