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10.1038/npjpcrm.2014.102

http://scihub22266oqcxt.onion/10.1038/npjpcrm.2014.102
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C4498191!4498191!25569783
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suck abstract from ncbi


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pmid25569783      NPJ+Prim+Care+Respir+Med 2015 ; 25 (�): 14102-
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  • Methodological quality of meta-analyses on treatments for chronic obstructive pulmonary disease: a cross-sectional study using the AMSTAR (Assessing the Methodological Quality of Systematic Reviews) tool #MMPMID25569783
  • Ho RS; Wu X; Yuan J; Liu S; Lai X; Wong SY; Chung VC
  • NPJ Prim Care Respir Med 2015[]; 25 (�): 14102- PMID25569783show ga
  • Background:: Meta-analysis (MA) of randomised trials is considered to be one of the best approaches for summarising high-quality evidence on the efficacy and safety of treatments. However, methodological flaws in MAs can reduce the validity of conclusions, subsequently impairing the quality of decision making. Aims:: To assess the methodological quality of MAs on COPD treatments. Methods:: A cross-sectional study on MAs of COPD trials. MAs published during 2000?2013 were sampled from the Cochrane Database of Systematic Reviews and Database of Abstracts of Reviews of Effect. Methodological quality was assessed using the validated AMSTAR (Assessing the Methodological Quality of Systematic Reviews) tool. Results:: Seventy-nine MAs were sampled. Only 18% considered the scientific quality of primary studies when formulating conclusions and 49% used appropriate meta-analytic methods to combine findings. The problems were particularly acute among MAs on pharmacological treatments. In 48% of MAs the authors did not report conflict of interest. Fifty-eight percent reported harmful effects of treatment. Publication bias was not assessed in 65% of MAs, and only 10% had searched non-English databases. Conclusions:: The methodological quality of the included MAs was disappointing. Consideration of scientific quality when formulating conclusions should be made explicit. Future MAs should improve on reporting conflict of interest and harm, assessment of publication bias, prevention of language bias and use of appropriate meta-analytic methods.



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