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

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.

Ten years of meta-analyses on erythropoiesis-stimulating agents in cancer patients

Since erythropoiesis-stimulating agents (ESAs) were licensed in 1993, more than 70 randomized controlled trials and more than 20 meta-analyses and systematic reviews on their effectiveness were conducted. Here, we present a systematic review on the meta-analyses of trials evaluating ESAs in cancer patients.

Multiplicity of data in trial reports and the reliability of meta-analyses: empirical study

Objectives To examine the extent of multiplicity of data in trial reports and to assess the impact of multiplicity on meta-analysis results. Design Empirical study on a cohort of Cochrane systematic reviews. Data sources All Cochrane systematic reviews published from issue 3 in 2006 to issue 2 in 2007 that presented a result as a standardised mean difference (SMD). We retrieved trial reports contributing to the first SMD result in each review, and downloaded review protocols. We used these SMDs to identify a specific outcome for each meta-analysis from its protocol. Review methods Reviews were eligible if SMD results were based on two to ten randomised trials and if protocols described the outcome. We excluded reviews if they only presented results of subgroup analyses. Based on review protocols and index outcomes, two observers independently extracted the data necessary to calculate SMDs from the original trial reports for any intervention group, time point, or outcome measure compatible with the protocol. From the extracted data, we used Monte Carlo simulations to calculate all possible SMDs for every meta-analysis. Results We identified 19 eligible meta-analyses (including 83 trials). Published review protocols often lacked information about which data to choose. Twenty-four (29%) trials reported data for multiple intervention groups, 30 (36%) reported data for multiple time points, and 29 (35%) reported the index outcome measured on multiple scales. In 18 meta-analyses, we found multiplicity of data in at least one trial report; the median difference between the smallest and largest SMD results within a meta-analysis was 0.40 standard deviation units (range 0.04 to 0.91). Conclusions Multiplicity of data can affect the findings of systematic reviews and meta-analyses. To reduce the risk of bias, reviews and meta-analyses should comply with prespecified protocols that clearly identify time points, intervention groups, and scales of interest.

New methods can extend the use of minimal important difference units in meta-analyses of continuous outcome measures

For continuous outcomes measured using instruments with an established minimally important difference (MID), pooled estimates can be usefully reported in MID units. Approaches suggested thus far omit studies that used instruments without an established MID. We describe an approach that addresses this limitation.

Efficacy of psychological therapy in schizophrenia: conclusions from meta-analyses

Over the past years, evidence for the efficacy of psychological therapies in schizophrenia has been summarized in a series of meta-analyses. The present contribution aims to provide a descriptive survey of the evidence for the efficacy of psychological therapies as derived from these meta-analyses and to supplement them by selected findings from an own recent meta-analysis. Relevant meta-analyses and randomized controlled trials were identified by searching several electronic databases and by hand searching of reference lists. In order to compare the findings of the existing meta-analyses, the reported effect sizes were extracted and transformed into a uniform effect size measure where possible. For the own meta-analysis, weighted mean effect size differences between comparison groups regarding various types of outcomes were estimated. Their significance was tested by confidence intervals, and heterogeneity tests were applied to examine the consistency of the effects. From the available meta-analyses, social skills training, cognitive remediation, psychoeducational coping-oriented interventions with families and relatives, as well as cognitive behavioral therapy of persistent positive symptoms emerge as effective adjuncts to pharmacotherapy. Social skills training consistently effectuates the acquisition of social skills, cognitive remediation leads to short-term improvements in cognitive functioning, family interventions decrease relapse and hospitalization rates, and cognitive behavioral therapy results in a reduction of positive symptoms. These benefits seem to be accompanied by slight improvements in social functioning. However, open questions remain as to the specific therapeutic ingredients, to the synergistic effects, to the indication, as well as to the generalizability of the findings to routine care.

A modified test for small-study effects in meta-analyses of controlled trials with binary endpoints

Publication bias and related bias in meta-analysis is often examined by visually checking for asymmetry in funnel plots of treatment effect against its standard error. Formal statistical tests of funnel plot asymmetry have been proposed, but when applied to binary outcome data these can give false-positive rates that are higher than the nominal level in some situations (large treatment effects, or few events per trial, or all trials of similar sizes). We develop a modified linear regression test for funnel plot asymmetry based on the efficient score and its variance, Fisher's information. The performance of this test is compared to the other proposed tests in simulation analyses based on the characteristics of published controlled trials. When there is little or no between-trial heterogeneity, this modified test has a false-positive rate close to the nominal level while maintaining similar power to the original linear regression test ('Egger' test). When the degree of between-trial heterogeneity is large, none of the tests that have been proposed has uniformly good properties.

Bibliographic study showed improving methodology of meta-analyses published in leading journals 1993-2002

OBJECTIVE: To assess the methodology of meta-analyses published in leading general and specialist medical journals over a 10-year period. STUDY DESIGN AND SETTING: Volumes 1993-2002 of four general medicine journals and four specialist journals were searched by hand for meta-analyses including at least five controlled trials. Characteristics were assessed using a standardized questionnaire. RESULTS: A total of 272 meta-analyses, which included a median of 11 trials (range 5-195), were assessed. Most (81%) were published in general medicine journals. The median (range) number of databases searched increased from 1 (1-9) in 1993/1994 to 3.5 (1-21) in 2001/2002, P<0.0001. The proportion of meta-analyses including searches by hand (10% in 1993/1994, 25% in 2001/2002, P=0.005), searches of the grey literature (29%, 51%, P=0.010 by chi-square test), and of trial registers (10%, 32%, P=0.025) also increased. Assessments of the quality of trials also became more common (45%, 70%, P=0.008), including whether allocation of patients to treatment groups had been concealed (24%, 60%, P=0.001). The methodological and reporting quality was consistently higher in general medicine compared to specialist journals. CONCLUSION: Many meta-analyses published in leading journals have important methodological limitations. The situation has improved in recent years but considerable room for further improvements remains.

Grey literature in meta-analyses of randomized trials of health care interventions

BACKGROUND: The inclusion of grey literature (i.e. literature that has not been formally published) in systematic reviews may help to overcome some of the problems of publication bias, which can arise due to the selective availability of data. OBJECTIVES: To review systematically research studies, which have investigated the impact of grey literature in meta-analyses of randomized trials of health care interventions. SEARCH STRATEGY: We searched the Cochrane Methodology Register (The Cochrane Library Issue 3, 2005), MEDLINE (1966 to 20 May 2005), the Science Citation Index (June 2005) and contacted researchers who may have carried out relevant studies. SELECTION CRITERIA: A study was considered eligible for this review if it compared the effect of the inclusion and exclusion of grey literature on the results of a cohort of meta-analyses of randomized trials. DATA COLLECTION AND ANALYSIS: Data were extracted from each report independently by two reviewers. The main outcome measure was an estimate of the impact of trials from the grey literature on the pooled effect estimates of the meta-analyses. Information was also collected on the area of health care, the number of meta-analyses, the number of trials, the number of trial participants, the year of publication of the trials, the language and country of publication of the trials, the number and type of grey and published literature, and methodological quality. MAIN RESULTS: Five studies met the inclusion criteria. All five studies showed that published trials showed an overall greater treatment effect than grey trials. This difference was statistically significant in one of the five studies. Data could be combined for three of the five studies. This showed that, on average, published trials showed a 9% greater treatment effect than grey trials (ratio of odds ratios for grey versus published trials 1.09; 95% CI 1.03-1.16). Overall there were more published trials included in the meta-analyses than grey trials (median 224 (IQR 108-365) versus 45(IQR 40-102)). Published trials had more participants on average. The most common types of grey literature were abstracts (55%) and unpublished data (30%). There is limited evidence to show whether grey trials are of poorer methodological quality than published trials. AUTHORS' CONCLUSIONS: This review shows that published trials tend to be larger and show an overall greater treatment effect than grey trials. This has important implications for reviewers who need to ensure they identify grey trials, in order to minimise the risk of introducing bias into their review.

Disagreements in meta-analyses using outcomes measured on continuous or rating scales: observer agreement study

OBJECTIVE: To study the inter-observer variation related to extraction of continuous and numerical rating scale data from trial reports for use in meta-analyses. DESIGN: Observer agreement study. DATA SOURCES: A random sample of 10 Cochrane reviews that presented a result as a standardised mean difference (SMD), the protocols for the reviews and the trial reports (n=45) were retrieved. DATA EXTRACTION: Five experienced methodologists and five PhD students independently extracted data from the trial reports for calculation of the first SMD result in each review. The observers did not have access to the reviews but to the protocols, where the relevant outcome was highlighted. The agreement was analysed at both trial and meta-analysis level, pairing the observers in all possible ways (45 pairs, yielding 2025 pairs of trials and 450 pairs of meta-analyses). Agreement was defined as SMDs that differed less than 0.1 in their point estimates or confidence intervals. RESULTS: The agreement was 53% at trial level and 31% at meta-analysis level. Including all pairs, the median disagreement was SMD=0.22 (interquartile range 0.07-0.61). The experts agreed somewhat more than the PhD students at trial level (61% v 46%), but not at meta-analysis level. Important reasons for disagreement were differences in selection of time points, scales, control groups, and type of calculations; whether to include a trial in the meta-analysis; and data extraction errors made by the observers. In 14 out of the 100 SMDs calculated at the meta-analysis level, individual observers reached different conclusions than the originally published review. CONCLUSIONS: Disagreements were common and often larger than the effect of commonly used treatments. Meta-analyses using SMDs are prone to observer variation and should be interpreted with caution. The reliability of meta-analyses might be improved by having more detailed review protocols, more than one observer, and statistical expertise.

Critical appraisal of meta-analyses: an introductory guide for the practicing surgeon

ABSTRACT: Meta-analyses are an essential tool of clinical research. Meta-analyses of individual randomized controlled trials frequently constitute the highest possible level of scientific evidence for a given research question and allow surgeons to rapidly gain a comprehensive understanding of an important clinical issue. Moreover, meta-analyses often serve as cornerstones for evidence-based surgery, treatment guidelines, and knowledge transfer. Given the importance of meta-analyses to the medical (and surgical) knowledge base, it is of cardinal importance that surgeons have a basic grasp of the principles that guide a high-quality meta-analysis, and be able to weigh objectively the advantages and potential pitfalls of this clinical research tool. Unfortunately, surgeons are often ill-prepared to successfully conduct, critically appraise, and correctly interpret meta-analyses. The objective of this educational review is to provide surgeons with a brief introductory overview of the knowledge and skills required for understanding and critically appraising surgical meta-analyses as well as assessing their implications for their own surgical practice.