Impact of searching clinical trial registries in systematic reviews of pharmaceutical treatments: methodological systematic review and reanalysis of meta-analyses

Baudard, Marie; Yavchitz, Amélie; Ravaud, Philippe; Perrodeau, Élodie; Boutron, Isabelle

doi:10.1136/bmj.j448

Cited by 92 publications

(82 citation statements)

References 38 publications

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“…Trial registries (eg, ClinicalTrials.gov) are useful for identifying trials, comparing published results with planned outcomes and methods and obtaining results not reported elsewhere . Registries may also include data about potential harms that cannot be obtained through other sources .…”

Section: Step 1 Specify Which Sources You Will Use For Your Review Amentioning

confidence: 99%

Practical guidance for using multiple data sources in systematic reviews and meta‐analyses (with examples from the MUDS study)

Mayo‐Wilson

Fusco

et al. 2017

Research Synthesis Methods

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Data for individual trials included in systematic reviews may be available in multiple sources. For example, a single trial might be reported in 2 journal articles and 3 conference abstracts. Because of differences across sources, source selection can influence the results of systematic reviews. We used our experience in the Multiple Data Sources in Systematic Reviews (MUDS) study, and evidence from previous studies, to develop practical guidance for using multiple data sources in systematic reviews.We recommend the following: (1) Specify which sources you will use. Before beginning a systematic review, consider which sources are likely to contain the most useful data. Try to identify all relevant reports and to extract information from the most reliable sources. (2) Link individual trials with multiple sources. Write to authors to determine which sources are likely related to the same trials. Use a modified Preferred Reporting Items for Systematic Reviews and Meta‐analyses (PRISMA) flowchart to document both the selection of trials and the selection of sources. (3) Follow a prespecified protocol for extracting trial characteristics from multiple sources. Identify differences among sources, and contact study authors to resolve differences if possible. (4) Prespecify outcomes and results to examine in the review and meta‐analysis. In your protocol, describe how you will handle multiple outcomes within each domain of interest. Look for outcomes using all eligible sources. (5) Identify which data sources were included in the review. Consider whether the results might have been influenced by data sources used. (6) To reduce bias, and to reduce research waste, share the data used in your review.

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Section: Step 1 Specify Which Sources You Will Use For Your Review Amentioning

confidence: 99%

Practical guidance for using multiple data sources in systematic reviews and meta‐analyses (with examples from the MUDS study)

Mayo‐Wilson

Fusco

et al. 2017

Research Synthesis Methods

View full text Add to dashboard Cite

show abstract

“…Although ignored during publication, negative studies assume just as much importance as published ones when the aim is to summarize evidence on a topic of interest. Importantly, including results from unpublished studies has been shown to alter the results of meta-analysis [12,13]. Thus, searching unpublished research is important for valid meta-analyses.…”

Section: Discussionmentioning

confidence: 99%

“…A systematic search for data from a diverse body of evidence is fundamental to serve that purpose. In addition to extracting data from published studies, it is important to search unpublished studies (also known as gray literature) as research shows that the latter have smaller treatment effects than published studies [10,11] and that inclusion of unpublished results can change conclusions of meta-analyses [12,13]. Conversely, failure to include unpublished data biases the results toward a positive treatment effect (also known as publication bias) [14,15].…”

Section: Introductionmentioning

confidence: 99%

Inadequate diversity of information resources searched in US-affiliated systematic reviews and meta-analyses: 2005–2016

Pradhan

Garnick

Barkondaj

et al. 2018

Journal of Clinical Epidemiology

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Objective: Systematic reviews and meta-analyses (SRMAs) rely upon comprehensive searches into diverse resources that catalog primary studies. However, since what constitutes a comprehensive search is unclear, we examined trends in databases searched from 2005–2016, surrounding the publication of search guidelines in 2013, and associations between resources searched and evidence of publication bias in SRMAs involving human subjects. Study Design: To ensure comparability of included SRMAs over the 12 years in the face of a near 100-fold increase of international SRMAs (mainly genetic studies from China) during this period, we focused on USA-affiliated SRMAs, manually reviewing 100 randomly selected SRMAs from those published in each year. After excluding articles (mainly for inadequate detail or out-of-scope methods), we identified factors associated with the databases searched, used network analysis to see which resources were simultaneously searched, and used logistic regression to link information sources searched with a lower chance of finding publication bias. Results: Among 817 SRMA articles studied, the common resources used were Medline (95%), EMBASE (44%), and Cochrane (41%). Methods journal SRMAs were most likely to use registries and grey literature resources. We found substantial co-searching of resources with only published materials, and not complemented by searches of registries and the grey literature. The 2013 guideline did not substantially increase searching of registries and grey literature resources to retrieve primary studies for the SRMAs. When used to augment Med-line, Scopus (in all SRMAs) and ClinicalTrials.gov (in SRMAs with safety outcomes) were negatively associated with publication bias. Conclusions: Even SRMAs that search multiple sources tend to search similar resources. Our study supports searching Scopus and CTG in addition to Medline to reduce the chance of publication bias.

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“…To evaluate the impact of searching trials registers, Baudard et al analysed 223 systematic reviews. One hundred and sixteen reviews (52%) did not report having searched trials registers.…”

Section: Discrepancies Between Unpublished Data and Trial Protocols mentioning

confidence: 99%

Challenges of identifying unpublished data from clinical trials: Getting the best out of clinical trials registers and other novel sources

Isojärvi

Wood

Lefebvre³

et al. 2018

Research Synthesis Methods

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Clinical trial data are essential for assessments of the effectiveness of health care interventions. Information about ongoing or completed, but not yet formally published, trials has been more difficult to identify until the development of clinical trials registers and portals. This paper summarises research evidence on identifying sources of trial data, how and when to search those sources, and which future developments may enhance access to and retrieval of unpublished trial evidence. We conducted a literature search for relevant studies and provide a narrative review of the evidence from these studies. Clinical trial data can be found in resources including clinical trials registers, regulatory agency sources, health technology assessment websites and manufacturers' websites, and submissions for regulatory approval. The challenges of searching these resources are described. Trials registers are relatively unsophisticated in terms of their search interfaces, and searchers need to adapt to each individual register. There is overlap across registers, but little research on the degree and nature of overlap and how best to search. Despite these challenges, trials registers and other resources can be rich sources of additional unique trial data, which may not be available from journal reports. New initiatives, such as OpenTrials, aim to consolidate and link all structured data and documentation related to clinical trials. No single resource gives access to all trials, and multiple registers should be searched as sensitively as possible. Searching is challenging and should be adequately resourced. Information specialists should monitor new developments which may reduce the challenges over the coming years.

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Impact of searching clinical trial registries in systematic reviews of pharmaceutical treatments: methodological systematic review and reanalysis of meta-analyses

Cited by 92 publications

References 38 publications

Practical guidance for using multiple data sources in systematic reviews and meta‐analyses (with examples from the MUDS study)

Practical guidance for using multiple data sources in systematic reviews and meta‐analyses (with examples from the MUDS study)

Inadequate diversity of information resources searched in US-affiliated systematic reviews and meta-analyses: 2005–2016

Challenges of identifying unpublished data from clinical trials: Getting the best out of clinical trials registers and other novel sources

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