David Moher and colleagues introduce PRISMA, an update of the QUOROM guidelines for reporting systematic reviews and meta-analyses

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Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement

Systematic reviews and meta-analyses have become increasingly important in health care. Clinicians read them to keep up to date with their field,1,2 and they are often used as a starting point for developing clinical practice guidelines. Granting agencies may require a systematic review to ensure there is justification for further research,3 and some health care journals are moving in this direction.4 As with all research, the value of a systematic review depends on what was done, what was found, and the clarity of reporting. As with other publications, the reporting quality of systematic reviews varies, limiting readers' ability to assess the strengths and weaknesses of those reviews.

Several early studies evaluated the quality of review reports. In 1987, Mulrow examined 50 review articles published in 4 leading medical journals in 1985 and 1986 and found that none met all 8 explicit scientific criteria, such as a quality assessment of included studies.5 In 1987, Sacks and colleagues6 evaluated the adequacy of reporting of 83 meta-analyses on 23 characteristics in 6 domains. Reporting was generally poor; between 1 and 14 characteristics were adequately reported (mean = 7.7; standard deviation = 2.7). A 1996 update of this study found little improvement.7

In 1996, to address the suboptimal reporting of meta-analyses, an international group developed a guidance called the QUOROM Statement (QUality Of Reporting Of Meta-analyses), which focused on the reporting of meta-analyses of randomized controlled trials.8 In this article, we summarize a revision of these guidelines, renamed PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses), which have been updated to address several conceptual and practical advances in the science of systematic reviews (Box 1).



Box 1

Conceptual issues in the evolution from QUOROM to PRISMA

Preferred reporting items for systematic reviews and meta-analyses: the PRISMA Statement.

Objective: Funnel plots (plots of effect estimates against sample size) may be useful to detect bias in meta-analyses that were later contradicted by large trials. We examined whether a simple test of asymmetry of funnel plots predicts discordance of results when meta-analyses are compared to large trials, and we assessed the prevalence of bias in published meta-analyses. Design: Medline search to identify pairs consisting of a meta-analysis and a single large trial (concordance of results was assumed if effects were in the same direction and the meta-analytic estimate was within 30% of the trial); analysis of funnel plots from 37 meta-analyses identified from a hand search of four leading general medicine journals 1993-6 and 38 meta-analyses from the second 1996 issue of the Cochrane Database of Systematic Reviews . Main outcome measure: Degree of funnel plot asymmetry as measured by the intercept from regression of standard normal deviates against precision. Results: In the eight pairs of meta-analysis and large trial that were identified (five from cardiovascular medicine, one from diabetic medicine, one from geriatric medicine, one from perinatal medicine) there were four concordant and four discordant pairs. In all cases discordance was due to meta-analyses showing larger effects. Funnel plot asymmetry was present in three out of four discordant pairs but in none of concordant pairs. In 14 (38%) journal meta-analyses and 5 (13%) Cochrane reviews, funnel plot asymmetry indicated that there was bias. Conclusions: A simple analysis of funnel plots provides a useful test for the likely presence of bias in meta-analyses, but as the capacity to detect bias will be limited when meta-analyses are based on a limited number of small trials the results from such analyses should be treated with considerable caution. Key messages Systematic reviews of randomised trials are the best strategy for appraising evidence; however, the findings of some meta-analyses were later contradicted by large trials Funnel plots, plots of the trials9 effect estimates against sample size, are skewed and asymmetrical in the presence of publication bias and other biases Funnel plot asymmetry, measured by regression analysis, predicts discordance of results when meta-analyses are compared with single large trials Funnel plot asymmetry was found in 38% of meta-analyses published in leading general medicine journals and in 13% of reviews from the Cochrane Database of Systematic Reviews Critical examination of systematic reviews for publication and related biases should be considered a routine procedure

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Bias in meta-analysis detected by a simple, graphical test

Systematic review and meta-analysis

Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement

Anonymous sources are used by journalists when it is important to protect whistleblowers from repercussions. Healthcare is heavily influenced by vested interests which are often financial, but academic prestige and protection of guild interests also play a major role. If anonymous authorship is not allowed, many potential whistleblowers would prefer to keep quiet, even though their stepping forward would serve the public interest and might save many lives, particularly by reducing prescription drug deaths. This is especially important since drugs are the third leading cause of death in the Western world.

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Anonymous authorship may reduce prescription drug deaths.

[Honest information about mammography screening, please!].

25 patients with AIDS or serious HIV infection were asked to specify the minimum time zidovudine should prolong life before they would be willing to take the drug for the rest of their lives. Most patients were unable to state a least acceptable survival benefit. Hence, the clinical relevance of sample size calculations in AIDS trials may be questioned since a survival benefit of zero would lead to an infinite sample size. Alternatively, one could aim first at a fixed number of deaths. Thereafter, it could be calculated how many more years the study should continue to secure that a mortality difference of some universally adopted magnitude would not be overlooked. This approach would not solve the sample size dilemma but would convert it into a pragmatic question: are we willing to continue the study for another x number of years?

Patients' views on the least acceptable increase in survival with zidovudine treatment.

Re: restoring invisible and abandoned trials: a call for people to publish the findings

Evidence-based medicine is based on the best results from clinical and epidemiological research, which is combined with clinical experience and patient preferences. Questions of prognosis and harm are often best elucidated in large cohort studies. For other clinical questions the best evidence is usually found by systematic review of randomised trials, if possible in the form of meta-analyses. To make a diagnosis is, for example, not an aim in itself but a way to arrive at a prognosis and to suggest a treatment, provided this leads to a better prognosis. The most relevant, albeit rarely seen, test of a diagnostic method is a randomised trial. Evidence-based medicine will provide the best basis for evaluations of which interventions should be abandoned and which are effective and economically feasible. The use of evidence-based clinical guidelines will lead to more cost-effective treatments. It should be a national strategy that health care should be evidence-based.

Peter C Gøtzsche

Papers

Anonymous authorship may reduce prescription drug deaths.

[Honest information about mammography screening, please!].

Patients' views on the least acceptable increase in survival with zidovudine treatment.

Re: restoring invisible and abandoned trials: a call for people to publish the findings

[What is evidence-based medicine?].