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A study conducted by Amélie Yavchitz and colleagues examines the factors associated with “spin” (specific reporting strategies, intentional or unintentional, that emphasize the beneficial effect of treatments) in press releases of clinical trials.

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BackgroundMass media through the Internet is a powerful means of disseminating medical research. We aimed to determine whether and how the interpretation of research results is misrepresented by the use of “spin” in the health section of Google News. Spin was defined as specific way of reporting, from whatever motive (intentional or unintentional), to emphasize that the beneficial effect of the intervention is greater than that shown by the results.MethodsWe conducted a cross-sectional study of news highlighted in the health section of US, UK and Canada editions of Google News between July 2013 and January 2014. We searched for news items for 3 days a week (i.e., Monday, Wednesday, and Friday) during 6 months and selected a sample of 130 news items reporting a scientific article evaluating the effect of an intervention on human health.ResultsIn total, 78% of the news did not provide a full reference or electronic link to the scientific article. We found at least one spin in 114 (88%) news items and 18 different types of spin in news. These spin were mainly related to misleading reporting (59%) such as not reporting adverse events that were reported in the scientific article (25%), misleading interpretation (69%) such as claiming a causal effect despite non-randomized study design (49%) and overgeneralization/misleading extrapolation (41%) of the results such as extrapolating a beneficial effect from an animal study to humans (21%). We also identified some new types of spin such as highlighting a single patient experience for the success of a new treatment instead of focusing on the group results.ConclusionsInterpretation of research results was frequently misrepresented in the health section of Google News. However, we do not know whether these spin were from the scientific articles themselves or added in the news.

Objective To compare estimates of intervention effects between single centre and multicentre randomised controlled trials with continuous outcomes.Design Meta-epidemiological study.Data sources 26 meta-analyses totalling 292 randomised controlled trials (177 single centre, 115 multicentre) with continuous outcomes published between January 2007 and January 2010 in the Cochrane database of systematic reviews.Data extraction Data were extracted on characteristics of trials, single or multicentre status, risk of bias using the risk of bias tool of the Cochrane Collaboration, and results. Data synthesisThe intervention effects were estimated with standardised mean differences. For each meta-analysis, random effects meta-regression was used to estimate the difference in standardised mean differences between single centre and multicentre trials. Differences in standardised mean differences were then pooled across meta-analyses by a random-effects meta-analysis model. A combined difference in standardised mean differences of less than 0 indicated that single centre trials showed larger treatment effects, on average, than did multicentre trials. Because single centre trials may be more prone to publication bias and may have lower methodological quality than multicentre trials, sensitivity analyses were done with adjustment for sample size and domains of the risk of bias tool.Results Single centre trials showed larger intervention effects than did multicentre trials (combined difference in standardised mean differences −0.09, 95% confidence interval −0.17 to −0.01, P=0.04), with low heterogeneity across individual meta-analyses (I 2 =0%, between meta-analyses variance τ 2

BackgroundMultiple treatments are frequently available for a given condition, and clinicians and patients need a comprehensive, up-to-date synthesis of evidence for all competing treatments. We aimed to quantify the waste of research related to the failure of systematic reviews to provide a complete and up-to-date evidence synthesis over time.MethodsWe performed a series of systematic overviews and networks of randomized trials assessing the gap between evidence covered by systematic reviews and available trials of second-line treatments for advanced non-small cell lung cancer. We searched the Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effects, MEDLINE, EMBASE, and other resources sequentially by year from 2009 to March 2, 2015. We sequentially compared the amount of evidence missing from systematic reviews to the randomized evidence available for inclusion each year. We constructed cumulative networks of randomized evidence over time and evaluated the proportion of trials, patients, treatments, and treatment comparisons not covered by systematic reviews on December 31 each year from 2009 to 2015.ResultsWe identified 77 trials (28,636 patients) assessing 47 treatments with 54 comparisons and 29 systematic reviews (13 published after 2013). From 2009 to 2015, the evidence covered by existing systematic reviews was consistently incomplete: 45 % to 70 % of trials; 30 % to 58 % of patients; 40 % to 66 % of treatments; and 38 % to 71 % of comparisons were missing. In the cumulative networks of randomized evidence, 10 % to 17 % of treatment comparisons were partially covered by systematic reviews and 55 % to 85 % were partially or not covered.ConclusionsWe illustrate how systematic reviews of a given condition provide a fragmented, out-of-date panorama of the evidence for all treatments. This waste of research might be reduced by the development of live cumulative network meta-analyses.Electronic supplementary materialThe online version of this article (doi:10.1186/s12916-016-0555-0) contains supplementary material, which is available to authorized users.

Objective To evaluate the impact of searching clinical trial registries in systematic reviews. Design Methodological systematic review and reanalyses of meta-analyses. Data sources Medline was searched to identify systematic reviews of randomised controlled trials (RCTs) assessing pharmaceutical treatments published between June 2014 and January 2015. For all systematic reviews that did not report a trial registry search but reported the information to perform it, the World Health Organization International Trials Registry Platform (WHO ICTRP search portal) was searched for completed or terminated RCTs not originally included in the systematic review. Data extraction For each systematic review, two researchers independently extracted the outcomes analysed, the number of patients included, and the treatment effect estimated. For each RCT identified, two researchers independently determined whether the results were available (ie, posted, published, or available on the sponsor website) and extracted the data. When additional data were retrieved, we reanalysed meta-analyses and calculated the weight of the additional RCTs and the change in summary statistics by comparison with the original meta-analysis. Results Among 223 selected systematic reviews, 116 (52%) did not report a search of trial registries; 21 of these did not report the information to perform the search (key words, search date). A search was performed for 95 systematic reviews; for 54 (57%), no additional RCTs were found and for 41 (43%) 122 additional RCTs were identified. The search allowed for increasing the number of patients by more than 10% in 19 systematic reviews, 20% in 10, 30% in seven, and 50% in four. Moreover, 63 RCTs had results available; the results for 45 could be included in a meta-analysis. 14 systematic reviews including 45 RCTs were reanalysed. The weight of the additional RCTs in the recalculated meta-analyses ranged from 0% to 58% and was greater than 10% in five of 14 systematic reviews, 20% in three, and 50% in one. The change in summary statistics ranged from 0% to 29% and was greater than 10% for five of 14 systematic reviews and greater than 20% for two. However, none of the changes to summary effect estimates led to a qualitative change in the interpretation of the results once the new trials were added. Conclusions Trial registries are an important source for identifying additional RCTs. The additional number of RCTs and patients included if a search were performed varied across systematic reviews.

No specific funding.