Investigation of Risk Of Bias due to Unreported and SelecTively included results in meta-analyses of nutrition research: the ROBUST study protocol

The Perils of Misinterpreting and Misusing "Publication Bias" in Meta-analyses: An Education Review on Funnel Plot-Based Methods

Publication bias refers to a systematic deviation from the truth in the results of a meta-analysis due to the higher likelihood for published studies to be included in meta-analyses than unpublished studies. Publication bias can lead to misleading recommendations for decision and policy making. In this education review, we introduce, explain, and provide solutions to the pervasive misuses and misinterpretations of publication bias that afflict evidence syntheses in sport and exercise medicine, with a focus on the commonly used funnel-plot based methods. Publication bias is more routinely assessed by visually inspecting funnel plot asymmetry, although it has been consistently deemed unreliable, leading to the development of statistical tests to assess publication bias. However, most statistical tests of publication bias (i) cannot rule out alternative explanations for funnel plot asymmetry (e.g., between-study heterogeneity, choice of metric, chance) and (ii) are grossly underpowered, even when using an arbitrary minimum threshold of ten or more studies. We performed a cross-sectional meta-research investigation of how publication bias was assessed in systematic reviews with meta-analyses published in the top two sport and exercise medicine journals throughout 2021. This analysis highlights that publication bias is frequently misused and misinterpreted, even in top tier journals. Because of conceptual and methodological problems when assessing and interpreting publication bias, preventive strategies (e.g., pre-registration, registered reports, disclosing protocol deviations, and reporting all study findings regardless of direction or magnitude) offer the best and most efficient solution to mitigate the misuse and misinterpretation of publication bias. Because true publication bias is very difficult to determine, we recommend that future publications use the term "risk of publication bias".

Credibility at stake: only two-thirds of randomized trials of nutrition interventions are registered and lack transparency in outcome and treatment effect definitions

OBJECTIVES

This study aimed to investigate the adherence of randomized controlled trials of nutrition interventions to transparency practices informing assessments of selective reporting biases, including the availability of a trial registration entry, protocol and statistical analysis plan (SAP).

STUDY DESIGN AND SETTING

Retrospective observational study with cross-sectional design. We systematically searched for trials published from 1 July 2019, to 30 June 2020, and included a randomly selected sample of 400 studies. We searched for registry entries, protocols, and SAPs for all included studies. We extracted data to characterize the disclosure of sufficient information in the available materials to inform assessments of selective reporting biases, considering the definition of outcome domain, measure, metric, method of aggregation, time point, analysis population, methods to handle missing data and method of adjustment.

RESULTS

Most trials (69%) were registered, but these often lacked sufficient specification of outcomes and intended treatment effects. Protocols and SAPs provided more details but were less often available (14% and 3%, respectively), and even then, almost all studies presented limited information to inform the assessments of risk of bias due to the selection of the reported result.

CONCLUSION

Lack of full specification of outcomes and intended treatment effects hinder a full adherence of randomized controlled trials of nutrition interventions to transparency practices and may affect their credibility.

Development of a checklist to detect errors in meta-analyses in systematic reviews of interventions: study protocol

Background : Systematic reviews underpin clinical practice and policies that guide healthcare decisions. A core component of many systematic reviews is meta-analysis, which is a statistical synthesis of results across studies. Errors in the conduct and interpretation of meta-analysis can lead to incorrect conclusions regarding the benefits and harms of interventions; and studies have shown that these errors are common. Enabling peer reviewers to better detect errors in meta-analysis through the use of a checklist provides an opportunity for these errors to be rectified before publication. To our knowledge, no such checklist exists. Objective : To develop and evaluate a checklist to detect errors in pairwise meta-analyses in systematic reviews of interventions. Methods : We will undertake a four-step process to develop the checklist. First, we will undertake a systematic review of studies that have evaluated errors in the conduct and interpretation of meta-analysis to generate a bank of items to consider for the checklist. Second, we will undertake a survey of systematic review methodologists and statisticians to seek their views on which items, of the bank of items generated in step 1, are most important to include in the checklist. Third, we will hold a virtual meeting to agree upon which items to include in the checklist. Fourth, before finalising the checklist, we will pilot with editors and peer reviewers of journals. Conclusion : The developed checklist is intended to help journal editors and peer reviewers identify errors in the application and interpretation of meta-analyses in systematic reviews. Fewer errors in the conduct and improved interpretation will lead to more accurate review findings and conclusions to inform clinical practice.