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Quality of meta-analyses for randomized trials in the field of hypertension

a systematic review

Roush, George C.; Amante, Brigani; Singh, Tanveer; Ayele, Hiwot; Araoye, Morakinyo; Yang, Danwen; Kostis, William J.; Elliott, William J.; Kostis, John B.; Berlin, Jesse A.

doi: 10.1097/HJH.0000000000001094
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Objectives: Doubling on average every 6 years, hypertension-related meta-analyses are now published twice weekly and are often considered the highest level of evidence for clinical practice. However, some hypertension specialists and guideline authors view meta-analyses with skepticism. This article evaluates the quality of hypertension-related meta-analyses of clinical trials.

Methods: A systematic search was conducted for meta-analyses of clinical trials recently published over 3.3 years. Specific criteria reproducibly assessed 26 features in the four domains of meta-analysis quality, domains justified by fundamental analytics and extensive research: analyzing trial quality, analyzing heterogeneity, analyzing publication bias, and providing transparency.

Results: A total of 143 meta-analyses were identified. A total of 44% had 8+ deficient features with no relation to journal impact factor: odds ratio relating 8+ deficient features to the upper third versus lower third of impact factor = 1.3 (95% confidence limit 0.6–2.9). A total of 56% had all four domains deficient. Quality did not improve over time. Thirty articles (21%) reported statistically significant results (P < 0.05) from inappropriate DerSimonian–Laird models, whereas unreported, appropriate, Knapp–Hartung models gave statistical nonsignificance; 88% of these 30 articles reported the incorrect results in their abstracts. A total of 60% of all meta-analyses failed to conduct analyses in subgroups of quality when indicated, 63% failed to report Tau and Tau2, 57% omitted testing for publication bias, none conducted a cumulative analysis for publication bias, and 71–77% omitted mentioning in their abstracts problems of trial quality, heterogeneity, and publication bias.

Conclusion: Although widespread, deficiencies in hypertension-related meta-analyses are readily corrected and do not represent flaws inherent in the meta-analytic method.

aUCONN School of Medicine, Bridgeport, Connecticut

bUniversity of Colorado Hospital, Aurora, Colorado

cRutgers Robert Wood Johnson Medical School, Brunswick, New Jersey

dPacific Northwest University of Health Sciences, Yakima, Washington

eJohnson & Johnson, Titusville, New Jersey, USA

Correspondence to George C. Roush, 217 East 70th Street, #708, New York, NY 10021, USA. E-mail: groush@gcr0.com

Abbreviation: MA, meta-analysis

Received 27 May, 2016

Revised 5 July, 2016

Accepted 28 July, 2016

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