Dataset Information

The strong focus on positive results in abstracts may cause bias in systematic reviews: a case study on abstract reporting bias.

ABSTRACT:

Background

Research articles tend to focus on positive findings in their abstract, especially if multiple outcomes have been studied. At the same time, search queries in databases are generally limited to the abstract, title and keywords fields of an article. Negative findings are therefore less likely to be detected by systematic searches and to appear in systematic reviews. We aim to assess the occurrence of this 'abstract reporting bias' and quantify its impact in the literature on the association between diesel exhaust exposure (DEE) and bladder cancer.

Methods

We set up a broad search query related to DEE and cancer in general. Full-texts of the articles identified in the search output were manually scanned. Articles were included if they reported, anywhere in the full-text, the association between DEE and bladder cancer. We assume that the use of a broad search query and manual full-text scanning allowed us to catch all the relevant articles, including those in which bladder cancer was not mentioned in the abstract, title or keywords.

Results

We identified 28 articles. Only 12 of these (43%) had mentioned bladder in their abstract, title or keywords. A meta-analysis based on these 12 detectable articles yielded a pooled risk estimate of 1.10 (95% confidence interval [CI] 0.97-1.25), whereas the meta-analysis based on all 28 articles yielded a pooled estimate of 1.03 (95% CI 0.96-1.11).

Conclusions

This case study on abstract reporting bias shows that (a) more than half of all relevant articles were missed by a conventional search query and (b) this led to an overestimation of the pooled effect. Detection of articles will be improved if all studied exposure and outcome variables are reported in the keywords. The restriction on the maximum number of keywords should be lifted.

SUBMITTER: Duyx B

PROVIDER: S-EPMC6637611 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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Publications

The strong focus on positive results in abstracts may cause bias in systematic reviews: a case study on abstract reporting bias.

Duyx Bram B Swaen Gerard M H GMH Urlings Miriam J E MJE Bouter Lex M LM Zeegers Maurice P MP

Systematic reviews 20190717 1

<h4>Background</h4>Research articles tend to focus on positive findings in their abstract, especially if multiple outcomes have been studied. At the same time, search queries in databases are generally limited to the abstract, title and keywords fields of an article. Negative findings are therefore less likely to be detected by systematic searches and to appear in systematic reviews. We aim to assess the occurrence of this 'abstract reporting bias' and quantify its impact in the literature on th ...[more]

PMID: 31315665

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Project description:BackgroundArticle summaries' information and structure may influence researchers/clinicians' decisions to conduct deeper full-text analyses. Specifically, abstracts of systematic reviews (SRs) and meta-analyses (MA) should provide structured summaries for quick assessment. This study explored a method for determining the methodological quality and bias risk of full-text reviews using abstract information alone.MethodsSystematic literature searches for SRs and/or MA about psoriasis were undertaken on MEDLINE, EMBASE, and Cochrane database. For each review, quality, abstract-reporting completeness, full-text methodological quality, and bias risk were evaluated using Preferred Reporting Items for Systematic Reviews and Meta-analyses for abstracts (PRISMA-A), Assessing the Methodological Quality of Systematic Reviews (AMSTAR), and ROBIS tools, respectively. Article-, author-, and journal-derived metadata were systematically extracted from eligible studies using a piloted template, and explanatory variables concerning abstract-reporting quality were assessed using univariate and multivariate-regression models. Two classification models concerning SRs' methodological quality and bias risk were developed based on per-item and total PRISMA-A scores and decision-tree algorithms. This work was supported, in part, by project ICI1400136 (JR). No funding was received from any pharmaceutical company.ResultsThis study analysed 139 SRs on psoriasis interventions. On average, they featured 56.7% of PRISMA-A items. The mean total PRISMA-A score was significantly higher for high-methodological-quality SRs than for moderate- and low-methodological-quality reviews. SRs with low-bias risk showed higher total PRISMA-A values than reviews with high-bias risk. In the final model, only 'authors per review > 6' (OR: 1.098; 95%CI: 1.012-1.194), 'academic source of funding' (OR: 3.630; 95%CI: 1.788-7.542), and 'PRISMA-endorsed journal' (OR: 4.370; 95%CI: 1.785-10.98) predicted PRISMA-A variability. Reviews with a total PRISMA-A score < 6, lacking identification as SR or MA in the title, and lacking explanation concerning bias risk assessment methods were classified as low-methodological quality. Abstracts with a total PRISMA-A score ≥ 9, including main outcomes results and explanation bias risk assessment method were classified as having low-bias risk.ConclusionsThe methodological quality and bias risk of SRs may be determined by abstract's quality and completeness analyses. Our proposal aimed to facilitate synthesis of evidence evaluation by clinical professionals lacking methodological skills. External validation is necessary.

Project description:ObjectiveTo assess the reporting quality of randomised controlled trial (RCT) abstracts on age-related macular degeneration (AMD) healthcare, to evaluate the adherence to the Consolidated Standards of Reporting Trials (CONSORT) statement's recommendations on minimum abstract information and to identify journal characteristics associated with abstract reporting quality.DesignCross-sectional evaluation of RCT abstracts on AMD healthcare.MethodsA PubMed search was implemented to identify RCT abstracts on AMD healthcare published in the English language between January 2004 and December 2013. Data extraction was performed by two parallel readers independently by means of a documentation format in accordance with the 16 items of the CONSORT checklist for abstracts. The total number of criteria fulfilled by an abstract was derived as primary endpoint of the investigation; incidence rate ratios (IRRs) with unadjusted 95% CI were estimated by means of multiple Poisson regression to identify journal and article characteristics (publication year, multicentre design, structured abstract recommendations, effective sample size, effective abstract word counts and journal impact factor) possibly associated with the total number of fulfilled items.Study characteristics136 of 673 identified abstracts (published in 36 different journals) fulfilled all eligibility criteria.ResultsThe median number of fulfilled items was 7 (95% CI 7 to 8). No abstract reported all 16 recommended items; the maximum total number was 14, the minimum 3 of 16 items. Multivariate analysis only demonstrated the abstracts' word counts as being significantly associated with a better reporting of abstracts (Poisson regression-based IRR 1.002, 95% CI 1.001 to 1.003).ConclusionsReporting quality of RCT abstracts on AMD investigations showed a considerable potential for improvement to meet the CONSORT abstract reporting recommendations. Furthermore, word counts of abstracts were identified as significantly associated with the overall abstract reporting quality.

Project description:Strategies to identify and mitigate publication bias and outcome reporting bias are frequently adopted in systematic reviews of clinical interventions but it is not clear how often these are applied in systematic reviews relating to quantitative health services and delivery research (HSDR). We examined whether these biases are mentioned and/or otherwise assessed in HSDR systematic reviews, and evaluated associating factors to inform future practice. We randomly selected 200 quantitative HSDR systematic reviews published in the English language from 2007-2017 from the Health Systems Evidence database (www.healthsystemsevidence.org). We extracted data on factors that may influence whether or not authors mention and/or assess publication bias or outcome reporting bias. We found that 43% (n = 85) of the reviews mentioned publication bias and 10% (n = 19) formally assessed it. Outcome reporting bias was mentioned and assessed in 17% (n = 34) of all the systematic reviews. Insufficient number of studies, heterogeneity and lack of pre-registered protocols were the most commonly reported impediments to assessing the biases. In multivariable logistic regression models, both mentioning and formal assessment of publication bias were associated with: inclusion of a meta-analysis; being a review of intervention rather than association studies; higher journal impact factor, and; reporting the use of systematic review guidelines. Assessment of outcome reporting bias was associated with: being an intervention review; authors reporting the use of Grading of Recommendations, Assessment, Development and Evaluations (GRADE), and; inclusion of only controlled trials. Publication bias and outcome reporting bias are infrequently assessed in HSDR systematic reviews. This may reflect the inherent heterogeneity of HSDR evidence and different methodological approaches to synthesising the evidence, lack of awareness of such biases, limits of current tools and lack of pre-registered study protocols for assessing such biases. Strategies to help raise awareness of the biases, and methods to minimise their occurrence and mitigate their impacts on HSDR systematic reviews, are needed.

Dataset Information

The strong focus on positive results in abstracts may cause bias in systematic reviews: a case study on abstract reporting bias.

Background

Methods

Results

Conclusions

Publications

The strong focus on positive results in abstracts may cause bias in systematic reviews: a case study on abstract reporting bias.

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