Most systematic reviews of adverse effects did not include unpublished data

Golder, Su; Loke, Yoon K.; Wright, Kath; Sterrantino, Carmelo

doi:10.1016/j.jclinepi.2016.05.003

Cited by 25 publications

(32 citation statements)

References 36 publications

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“…In the MUDS study, we used ABBYY FineReader software (version 11) to extract IPD and data about harms that were included as tables in appendices . Although CSRs provide the most complete aggregated data about harms, most systematic reviews of harms do not use them . This may be because, despite their advantages, obtaining CSRs can be challenging.…”

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

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“…Whilst the adverse effects of drug interventions are the most commonly researched in systematic reviews (237/348, 68%), the adverse effects of surgical interventions are the next most popular type of intervention evaluated (80/348, 23%) (Golder, Loke, Wright & Sterrantino, ; Golder, Loke & Zorzela, , ). Surgical interventions that are evaluated in systematic reviews include procedures that are very widely used such as caesarean section and breast reconstruction.…”

Section: Introductionmentioning

confidence: 99%

The development of search filters for adverse effects of surgical interventions in medline and Embase

Golder

Wright

Loke

2018

Health Info Libraries J

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BackgroundSearch filter development for adverse effects has tended to focus on retrieving studies of drug interventions. However, a different approach is required for surgical interventions.ObjectiveTo develop and validate search filters for medline and Embase for the adverse effects of surgical interventions.MethodsSystematic reviews of surgical interventions where the primary focus was to evaluate adverse effect(s) were sought. The included studies within these reviews were divided randomly into a development set, evaluation set and validation set. Using word frequency analysis we constructed a sensitivity maximising search strategy and this was tested in the evaluation and validation set.ResultsThree hundred and fifty eight papers were included from 19 surgical intervention reviews. Three hundred and fifty two papers were available on medline and 348 were available on Embase. Generic adverse effects search strategies in medline and Embase could achieve approximately 90% relative recall. Recall could be further improved with the addition of specific adverse effects terms to the search strategies.ConclusionWe have derived and validated a novel search filter that has reasonable performance for identifying adverse effects of surgical interventions in medline and Embase. However, we appreciate the limitations of our methods, and recommend further research on larger sample sizes and prospective systematic reviews.

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“…In a survey of 348 systematic reviews published in 2014, around three-quarters relied solely on data published in peer-reviewed journals 7. Of those that accessed other sources, data from trials registries (such as ClinicalTrials.gov), conference proceedings or contacting authors were the most used.…”

Section: Introductionmentioning

confidence: 99%

“…Of those that accessed other sources, data from trials registries (such as ClinicalTrials.gov), conference proceedings or contacting authors were the most used. No reviews reported using or attempting to obtain regulatory information even though the majority of the reviews evaluated drug interventions 7. A survey of 2184 Cochrane authors also found that contacting ‘trialists/investigators’ was one of the most common methods for accessing unpublished data and that data from manufacturers or from regulatory agencies were rarely obtained 8…”

Section: Introductionmentioning

confidence: 99%

When to include clinical study reports and regulatory documents in systematic reviews

Jefferson

Doshi

Boutron

et al. 2018

BMJ EBM

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Reporting bias is a major threat to the validity and credibility of systematic reviews. This article outlines the rationale for accessing clinical study reports and other regulatory documents (regulatory data) as a means of addressing reporting bias and identifies factors that may help decide whether (or not) to include regulatory data in systematic reviews. The article also describes the origins and current state of regulatory data access and summarises a survey of current systematic reviewers’ practices in considering regulatory data for inclusion in systematic reviews. How to access and extract regulatory data is not addressed. Organisations and other stakeholders such as Cochrane should encourage the use of data from clinical study reports as an important source of data in reviews of pharmaceutical interventions particularly when the intervention in question is of high importance and the risk of reporting bias is great.

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Most systematic reviews of adverse effects did not include unpublished data

Cited by 25 publications

References 36 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)

The development of search filters for adverse effects of surgical interventions in medline and Embase

When to include clinical study reports and regulatory documents in systematic reviews

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