Dissemination and publication of research findings: an updated review of related biases

To identify and appraise empirical studies on publication and related biases published since 1998; to assess methods to deal with publication and related biases; and to examine, in a random sample of published systematic reviews, measures taken to prevent, reduce and detect dissemination bias. DATA SOURCES: The main literature search, in August 2008, covered the Cochrane Methodology Register Database, MEDLINE, EMBASE, AMED and CINAHL. In May 2009, PubMed, PsycINFO and OpenSIGLE were also searched. Reference lists of retrieved studies were also examined. REVIEW METHODS: In Part I, studies were classified as evidence or method studies and data were extracted according to types of dissemination bias or methods for dealing with it. Evidence from empirical studies was summarised narratively. In Part II, 300 systematic reviews were randomly selected from MEDLINE and the methods used to deal with publication and related biases were assessed.

Studies with significant or positive results were more likely to be published than those with non-significant or negative results, thereby confirming findings from a previous HTA report. There was convincing evidence that outcome reporting bias exists and has an impact on the pooled summary in systematic reviews. Studies with significant results tended to be published earlier than studies with non-significant results, and empirical evidence suggests that published studies tended to report a greater treatment effect than those from the grey literature. Exclusion of non-English-language studies appeared to result in a high risk of bias in some areas of research such as complementary and alternative medicine. In a few cases, publication and related biases had a potentially detrimental impact on patients or resource use. Publication bias can be prevented before a literature review (e.g. by prospective registration of trials), or detected during a literature review (e.g. by locating unpublished studies, funnel plot and related tests, sensitivity analysis modelling), or its impact can be minimised after a literature review (e.g. by confirmatory large-scale trials, updating the systematic review). The interpretation of funnel plot and related statistical tests, often used to assess publication bias, was often too simplistic and likely misleading. More sophisticated modelling methods have not been widely used. Compared with systematic reviews published in 1996, recent reviews of health-care interventions were more likely to locate and include non-English-language studies and grey literature or unpublished studies, and to test for publication bias.