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Peter C Gøtzsche

Bio: Peter C Gøtzsche is an academic researcher from Cochrane Collaboration. The author has contributed to research in topics: Systematic review & Placebo. The author has an hindex of 90, co-authored 413 publications receiving 147009 citations. Previous affiliations of Peter C Gøtzsche include University of Copenhagen & Copenhagen University Hospital.


Papers
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Journal ArticleDOI
TL;DR: The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Initiative developed recommendations on what should be included in an accurate and complete report of an observational study, resulting in a checklist of 22 items that relate to the title, abstract, introduction, methods, results, and discussion sections of articles.

9,603 citations

Journal ArticleDOI
TL;DR: The STROBE Statement is a checklist of items that should be addressed in articles reporting on the 3 main study designs of analytical epidemiology: cohort, casecontrol, and cross-sectional studies; these recommendations are not prescriptions for designing or conducting studies.
Abstract: Much biomedical research is observational. The reporting of such research is often inadequate, which hampers the assessment of its strengths and weaknesses and of a study's generalizability. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Initiative developed recommendations on what should be included in an accurate and complete report of an observational study. We defined the scope of the recommendations to cover 3 main study designs: cohort, case-control, and cross-sectional studies. We convened a 2-day workshop in September 2004, with methodologists, researchers, and journal editors, to draft a checklist of items. This list was subsequently revised during several meetings of the coordinating group and in e-mail discussions with the larger group of STROBE contributors, taking into account empirical evidence and methodological considerations. The workshop and the subsequent iterative process of consultation and revision resulted in a checklist of 22 items (the STROBE Statement) that relate to the title, abstract, introduction, methods, results, and discussion sections of articles. Eighteen items are common to all 3 study designs and 4 are specific for cohort, case-control, or cross-sectional studies. A detailed Explanation and Elaboration document is published separately and is freely available at http://www.annals.org and on the Web sites of PLoS Medicine and Epidemiology. We hope that the STROBE Statement will contribute to improving the quality of reporting of observational studies.

9,000 citations

Journal ArticleDOI
TL;DR: This Explanation and Elaboration document explains the meaning and rationale for each checklist item and includes an example of good reporting and, where possible, references to relevant empirical studies and methodological literature.

8,021 citations

Journal ArticleDOI
24 Mar 2010-BMJ
TL;DR: This update of the CONSORT statement improves the wording and clarity of the previous checklist and incorporates recommendations related to topics that have only recently received recognition, such as selective outcome reporting bias.
Abstract: Overwhelming evidence shows the quality of reporting of randomised controlled trials (RCTs) is not optimal. Without transparent reporting, readers cannot judge the reliability and validity of trial findings nor extract information for systematic reviews. Recent methodological analyses indicate that inadequate reporting and design are associated with biased estimates of treatment effects. Such systematic error is seriously damaging to RCTs, which are considered the gold standard for evaluating interventions because of their ability to minimise or avoid bias. A group of scientists and editors developed the CONSORT (Consolidated Standards of Reporting Trials) statement to improve the quality of reporting of RCTs. It was first published in 1996 and updated in 2001. The statement consists of a checklist and flow diagram that authors can use for reporting an RCT. Many leading medical journals and major international editorial groups have endorsed the CONSORT statement. The statement facilitates critical appraisal and interpretation of RCTs. During the 2001 CONSORT revision, it became clear that explanation and elaboration of the principles underlying the CONSORT statement would help investigators and others to write or appraise trial reports. A CONSORT explanation and elaboration article was published in 2001 alongside the 2001 version of the CONSORT statement. After an expert meeting in January 2007, the CONSORT statement has been further revised and is published as the CONSORT 2010 Statement. This update improves the wording and clarity of the previous checklist and incorporates recommendations related to topics that have only recently received recognition, such as selective outcome reporting bias. This explanatory and elaboration document-intended to enhance the use, understanding, and dissemination of the CONSORT statement-has also been extensively revised. It presents the meaning and rationale for each new and updated checklist item providing examples of good reporting and, where possible, references to relevant empirical studies. Several examples of flow diagrams are included. The CONSORT 2010 Statement, this revised explanatory and elaboration document, and the associated website (www.consort-statement.org) should be helpful resources to improve reporting of randomised trials.

5,957 citations

Journal ArticleDOI
18 Oct 2007-BMJ
TL;DR: In this article, a group of methodologists, researchers, and journal editors sets out guidelines to improve reports of observational studies, which hampers assessment and makes it less useful.
Abstract: Poor reporting of research hampers assessment and makes it less useful. An international group of methodologists, researchers, and journal editors sets out guidelines to improve reports of observational studies

4,179 citations


Cited by
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Journal ArticleDOI
TL;DR: Moher et al. as mentioned in this paper introduce PRISMA, an update of the QUOROM guidelines for reporting systematic reviews and meta-analyses, which is used in this paper.
Abstract: David Moher and colleagues introduce PRISMA, an update of the QUOROM guidelines for reporting systematic reviews and meta-analyses

62,157 citations

Journal Article
TL;DR: The QUOROM Statement (QUality Of Reporting Of Meta-analyses) as mentioned in this paper was developed to address the suboptimal reporting of systematic reviews and meta-analysis of randomized controlled trials.
Abstract: 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

46,935 citations

Journal ArticleDOI
13 Sep 1997-BMJ
TL;DR: Funnel plots, plots of the trials' 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.
Abstract: 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

37,989 citations

Journal ArticleDOI
TL;DR: In this review the usual methods applied in systematic reviews and meta-analyses are outlined, and the most common procedures for combining studies with binary outcomes are described, illustrating how they can be done using Stata commands.

31,656 citations

Journal ArticleDOI
TL;DR: A structured summary is provided including, as applicable, background, objectives, data sources, study eligibility criteria, participants, interventions, study appraisal and synthesis methods, results, limitations, conclusions and implications of key findings.

31,379 citations