Literature DB >> 28435099

A meta-analysis but not a systematic review: an evaluation of the Global BMI Mortality Collaboration.

Katherine M Flegal1, John P A Ioannidis2.   

Abstract

Meta-analyses of individual participant data (MIPDs) offer many advantages and are considered the highest level of evidence. However, MIPDs can be seriously compromised when they are not solidly founded upon a systematic review. These data-intensive collaborative projects may be led by experts who already have deep knowledge of the literature in the field and of the results of published studies and how these results vary based on different analytical approaches. If investigators tailor the searches, eligibility criteria, and analysis plan of the MIPD, they run the risk of reaching foregone conclusions. We exemplify this potential bias in a MIPD on the association of body mass index with mortality conducted by a collaboration of outstanding and extremely knowledgeable investigators. Contrary to a previous meta-analysis of group data that used a systematic review approach, the MIPD did not seem to use a formal search: it considered 239 studies, of which the senior author was previously aware of at least 238, and it violated its own listed eligibility criteria to include those studies and exclude other studies. It also preferred an analysis plan that was also known to give a specific direction of effects in already published results of most of the included evidence. MIPDs where results of constituent studies are already largely known need safeguards to their validity. These may include careful systematic searches, adherence to the Preferred Reporting Items for Systematic Review and Meta-Analyses of individual participant data guidelines, and exploration of the robustness of results with different analyses. They should also avoid selective emphasis on foregone conclusions based on previously known results with specific analytical choices.
Copyright © 2017 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Bias; Body mass index; Epidemiologic methods; Global BMI Mortality Collaboration; Meta-analysis; Mortality

Mesh:

Year:  2017        PMID: 28435099     DOI: 10.1016/j.jclinepi.2017.04.007

Source DB:  PubMed          Journal:  J Clin Epidemiol        ISSN: 0895-4356            Impact factor:   6.437


  4 in total

1.  Comparative effects of the restriction method in two large observational studies of body mass index and mortality among adults.

Authors:  Katherine M Flegal; Barry I Graubard; Sang-Wook Yi
Journal:  Eur J Clin Invest       Date:  2017-05-08       Impact factor: 4.686

Review 2.  Systematic reviews: guidance relevant for studies of older people.

Authors:  Susan D Shenkin; Jennifer K Harrison; Tim Wilkinson; Richard M Dodds; John P A Ioannidis
Journal:  Age Ageing       Date:  2017-09-01       Impact factor: 10.668

3.  Predicted lean body mass, fat mass, and all cause and cause specific mortality in men: prospective US cohort study.

Authors:  Dong Hoon Lee; NaNa Keum; Frank B Hu; E John Orav; Eric B Rimm; Walter C Willett; Edward L Giovannucci
Journal:  BMJ       Date:  2018-07-03

Review 4.  Flawed methods and inappropriate conclusions for health policy on overweight and obesity: the Global BMI Mortality Collaboration meta-analysis.

Authors:  Katherine M Flegal; John P A Ioannidis; Wolfram Doehner
Journal:  J Cachexia Sarcopenia Muscle       Date:  2019-01-17       Impact factor: 12.910

  4 in total

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