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      Small study effects in meta-analyses of osteoarthritis trials: meta-epidemiological study

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Objective To examine the presence and extent of small study effects in clinical osteoarthritis research.

          Design Meta-epidemiological study.

          Data sources 13 meta-analyses including 153 randomised trials (41 605 patients) that compared therapeutic interventions with placebo or non-intervention control in patients with osteoarthritis of the hip or knee and used patients’ reported pain as an outcome.

          Methods We compared estimated benefits of treatment between large trials (at least 100 patients per arm) and small trials, explored funnel plots supplemented with lines of predicted effects and contours of significance, and used three approaches to estimate treatment effects: meta-analyses including all trials irrespective of sample size, meta-analyses restricted to large trials, and treatment effects predicted for large trials.

          Results On average, treatment effects were more beneficial in small than in large trials (difference in effect sizes −0.21, 95% confidence interval −0.34 to −0.08, P=0.001). Depending on criteria used, six to eight funnel plots indicated small study effects. In six of 13 meta-analyses, the overall pooled estimate suggested a clinically relevant, significant benefit of treatment, whereas analyses restricted to large trials and predicted effects in large trials yielded smaller non-significant estimates.

          Conclusions Small study effects can often distort results of meta-analyses. The influence of small trials on estimated treatment effects should be routinely assessed.

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          Most cited references 38

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          Empirical evidence of bias. Dimensions of methodological quality associated with estimates of treatment effects in controlled trials.

          To determine if inadequate approaches to randomized controlled trial design and execution are associated with evidence of bias in estimating treatment effects. An observational study in which we assessed the methodological quality of 250 controlled trials from 33 meta-analyses and then analyzed, using multiple logistic regression models, the associations between those assessments and estimated treatment effects. Meta-analyses from the Cochrane Pregnancy and Childbirth Database. The associations between estimates of treatment effects and inadequate allocation concealment, exclusions after randomization, and lack of double-blinding. Compared with trials in which authors reported adequately concealed treatment allocation, trials in which concealment was either inadequate or unclear (did not report or incompletely reported a concealment approach) yielded larger estimates of treatment effects (P < .001). Odds ratios were exaggerated by 41% for inadequately concealed trials and by 30% for unclearly concealed trials (adjusted for other aspects of quality). Trials in which participants had been excluded after randomization did not yield larger estimates of effects, but that lack of association may be due to incomplete reporting. Trials that were not double-blind also yielded larger estimates of effects (P = .01), with odds ratios being exaggerated by 17%. This study provides empirical evidence that inadequate methodological approaches in controlled trials, particularly those representing poor allocation concealment, are associated with bias. Readers of trial reports should be wary of these pitfalls, and investigators must improve their design, execution, and reporting of trials.
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            Systematic reviews in health care: Assessing the quality of controlled clinical trials.

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              Systematic reviews in health care: Investigating and dealing with publication and other biases in meta-analysis.

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                Author and article information

                Contributors
                Role: research fellow
                Role: associate director
                Role: senior research fellow
                Role: senior research fellow
                Role: research fellow
                Role: director and professor of statistics in medicine
                Role: head of department and professor of epidemiology and public health
                Role: head of division and professor of clinical epidemiology
                Journal
                BMJ
                bmj
                BMJ : British Medical Journal
                BMJ Publishing Group Ltd.
                0959-8138
                1468-5833
                2010
                2010
                16 July 2010
                : 341
                Affiliations
                [1 ]Institute of Social and Preventive Medicine (ISPM), University of Bern, Switzerland
                [2 ]CTU Bern, Bern University Hospital, Switzerland
                [3 ]Department of Rheumatology, Immunology and Allergology, Bern University Hospital, Switzerland
                [4 ]Laboratory of Clinical Epidemiology of Cardiovascular Disease, Department of Clinical Pharmacology and Epidemiology, Consorzio Mario Negri Sud, Santa Maria Imbaro, Italy.
                [5 ]Centre for Statistics in Medicine, University of Oxford, Oxford
                Author notes
                Correspondence to: P Jüni juni@ 123456ispm.unibe.ch
                Article
                nuee758011
                10.1136/bmj.c3515
                2905513
                20639294
                © Nüesch et al 2010

                This is an open-access article distributed under the terms of the Creative Commons Attribution Non-commercial License, which permits use, distribution, and reproduction in any medium, provided the original work is properly cited, the use is non commercial and is otherwise in compliance with the license. See: http://creativecommons.org/licenses/by-nc/2.0/ and http://creativecommons.org/licenses/by-nc/2.0/legalcode.

                Product
                Categories
                Research
                Pain (Neurology)
                Degenerative Joint Disease
                Musculoskeletal Syndromes
                Osteoarthritis

                Medicine

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