Increasing retractions of meta-analyses publications for methodological flaw.
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ABSTRACT:
SUBMITTER: Chen CY
PROVIDER: S-EPMC8499503 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ObjectivesThe growing rate of retraction of scientific publications has attracted much attention within the academic community, but there is little knowledge about the nature of such retractions in schizophrenia-related research. This study aimed to analyze the characteristics of retractions of schizophrenia-related publications.Materials and methodsThe Web of Science was searched for eligible studies. A bibliometric analysis was conducted to describe the characteristics of the retractions using R software and Excel 2019. Content analysis was conducted to examine the essential components of retraction notices.ResultsA total of 36 retracted publications with 415 citations were identified from 1997 to 2021, of which, 83.3% occurred in the last decade. The overall retraction rate was 0.19%, with most of them (29; 80.56%) from the United Kingdom. The retractions were published in 33 journals, and the 2020 IFs ranged between 0.17 and 49.96 (Median = 3.93). The retractions involved 21 research areas, particularly in Psychiatry (19; 52.78%), Neurosciences and Neurology (10; 27.78%), and Psychology (7; 19.44%). Data issues (17; 42.22%), administrative errors of the publishers (5; 13.89%), and study design (4; 11.11%) were the top three reasons for retractions.ConclusionThis study provides an insight into retractions of schizophrenia-related publications. Institutional governance should be further strengthened to improve the scrutiny of publications, prevent continuing citations, and erroneous propagation after retraction.
| S-EPMC9376617 | biostudies-literature
Project description:ObjectiveTo examine how the results of network meta-analyses are reported.DesignMethodological systematic review of published reports of network meta-analyses.Data sourcesCochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effects, Medline, and Embase, searched from inception to 12 July 2012.Study selectionAll network meta-analyses comparing the clinical efficacy of three or more interventions in randomised controlled trials were included, excluding meta-analyses with an open loop network of three interventions.Data extraction and synthesisThe reporting of the network and results was assessed. A composite outcome included the description of the network (number of interventions, direct comparisons, and randomised controlled trials and patients for each comparison) and the reporting of effect sizes derived from direct evidence, indirect evidence, and the network meta-analysis.Results121 network meta-analyses (55 published in general journals; 48 funded by at least one private source) were included. The network and its geometry (network graph) were not reported in 100 (83%) articles. The effect sizes derived from direct evidence, indirect evidence, and the network meta-analysis were not reported in 48 (40%), 108 (89%), and 43 (36%) articles, respectively. In 52 reports that ranked interventions, 43 did not report the uncertainty in ranking. Overall, 119 (98%) reports of network meta-analyses did not give a description of the network or effect sizes from direct evidence, indirect evidence, and the network meta-analysis. This finding did not differ by journal type or funding source.ConclusionsThe results of network meta-analyses are heterogeneously reported. Development of reporting guidelines to assist authors in writing and readers in critically appraising reports of network meta-analyses is timely.
| S-EPMC3949412 | biostudies-literature
Project description:PurposeTo assess the overall quality of published urological meta-analyses and identify predictive factors for high quality.Materials and methodsWe systematically searched PubMed to identify meta-analyses published from January 1st, 2011 to December 31st, 2015 in 10 predetermined major paper-based urology journals. The characteristics of the included meta-analyses were collected, and their reporting and methodological qualities were assessed by the PRISMA checklist (27 items) and AMSTAR tool (11 items), respectively. Descriptive statistics were used for individual items as a measure of overall compliance, and PRISMA and AMSTAR scores were calculated as the sum of adequately reported domains. Logistic regression was used to identify predictive factors for high qualities.ResultsA total of 183 meta-analyses were included. The mean PRISMA and AMSTAR scores were 22.74 ± 2.04 and 7.57 ± 1.41, respectively. PRISMA item 5, protocol and registration, items 15 and 22, risk of bias across studies, items 16 and 23, additional analysis had less than 50% adherence. AMSTAR item 1, "a priori" design, item 5, list of studies and item 10, publication bias had less than 50% adherence. Logistic regression analyses showed that funding support and "a priori" design were associated with superior reporting quality, following PRISMA guideline and "a priori" design were associated with superior methodological quality.ConclusionsReporting and methodological qualities of recently published meta-analyses in major paper-based urology journals are generally good. Further improvement could potentially be achieved by strictly adhering to PRISMA guideline and having "a priori" protocol.
| S-EPMC5399869 | biostudies-literature
Project description:OBJECTIVES:Meta-analyses (MAs) are often used because they are lauded to provide robust evidence that synthesises information from multiple studies. However, the validity of MA conclusions relies on the procedural rigour applied by the authors. Therefore, this meta-research study aims to characterise the methodological quality and meta-analytic practices of MAs indexed in PsycINFO. DESIGN:A meta-epidemiological study. PARTICIPANTS:We evaluated a random sample of 206 MAs indexed in the PsycINFO database in 2016. PRIMARY AND SECONDARY OUTCOMES:Two authors independently extracted the methodological characteristics of all MAs and checked their quality according to the 16 items of the A MeaSurement Tool to Assess systematic Reviews (AMSTAR2) tool for MA critical appraisal. Moreover, we investigated the effect of mentioning Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) on the methodological quality of MAs. RESULTS:According to AMSTAR2 criteria, 95% of the 206 MAs were rated as critically low quality. Statistical methods were appropriate and publication bias was well evaluated in 87% and 70% of the MAs, respectively. However, much improvement is needed in data collection and analysis: only 11% of MAs published a research protocol, 44% had a comprehensive literature search strategy, 37% assessed and 29% interpreted the risk of bias in the individual included studies, and 11% presented a list of excluded studies. Interestingly, the explicit mentioning of PRISMA suggested a positive influence on the methodological quality of MAs. CONCLUSION:The methodological quality of MAs in our sample was critically low according to the AMSTAR2 criteria. Some efforts to tremendously improve the methodological quality of MAs could increase their robustness and reliability.
| S-EPMC7402002 | biostudies-literature
Project description:Rationale, aims, and objectivesCOVID-19 has caused an ongoing public health crisis. Many systematic reviews and meta-analyses have been performed to synthesize evidence for better understanding this new disease. However, some concerns have been raised about rapid COVID-19 research. This meta-epidemiological study aims to methodologically assess the current systematic reviews and meta-analyses on COVID-19.MethodsWe searched in various databases for systematic reviews with meta-analyses published between 1 January 2020 and 31 October 2020. We extracted their basic characteristics, data analyses, evidence appraisal, and assessment of publication bias and heterogeneity.ResultsWe identified 295 systematic reviews on COVID-19. The median time from submission to acceptance was 33 days. Among these systematic reviews, 73.9% evaluated clinical manifestations or comorbidities of COVID-19. Stata was the most used software programme (43.39%). The odds ratio was the most used effect measure (34.24%). Moreover, 28.14% of the systematic reviews did not present evidence appraisal. Among those reporting the risk of bias results, 14.64% of studies had a high risk of bias. Egger's test was the most used method for assessing publication bias (38.31%), while 38.66% of the systematic reviews did not assess publication bias. The I2 statistic was widely used for assessing heterogeneity (92.20%); many meta-analyses had high values of I2 . Among the meta-analyses using the random-effects model, 75.82% did not report the methods for model implementation; among those meta-analyses reporting implementation methods, the DerSimonian-Laird method was the most used one.ConclusionsThe current systematic reviews and meta-analyses on COVID-19 might suffer from low transparency, high heterogeneity, and suboptimal statistical methods. It is recommended that future systematic reviews on COVID-19 strictly follow well-developed guidelines. Sensitivity analyses may be performed to examine how the synthesized evidence might depend on different methods for appraising evidence, assessing publication bias, and implementing meta-analysis models.
| S-EPMC8242754 | biostudies-literature
Project description:BackgroundStudies have shown that industry-sponsored meta-analyses of drugs lack scientific rigour and have biased conclusions. However, these studies have been restricted to certain medical specialities. We compared all industry-supported meta-analyses of drug-drug comparisons with those without industry support.MethodsWe searched PubMed for all meta-analyses that compared different drugs or classes of drugs published in 2004. Two authors assessed the meta-analyses and independently extracted data. We used a validated scale for judging the methodological quality and a binary scale for judging conclusions. We divided the meta-analyses according to the type of support in 3 categories: industry-supported, non-profit support or no support, and undeclared support.ResultsWe included 39 meta-analyses. Ten had industry support, 18 non-profit or no support, and 11 undeclared support. On a 0-7 scale, the median quality score was 6 for meta-analyses with non-profit or no support and 2.5 for the industry-supported meta-analyses (P < 0.01). Compared with industry-supported meta-analyses, more meta-analyses with non-profit or no support avoided bias in the selection of studies (P = 0.01), more often stated the search methods used to find studies (P = 0.02), searched comprehensively (P < 0.01), reported criteria for assessing the validity of the studies (P = 0.02), used appropriate criteria (P = 0.04), described methods of allocation concealment (P = 0.05), described methods of blinding (P = 0.05), and described excluded patients (P = 0.08) and studies (P = 0.15). Forty percent of the industry-supported meta-analyses recommended the experimental drug without reservations, compared with 22% of the meta-analyses with non-profit or no support (P = 0.57).In a sensitivity analysis, we contacted the authors of the meta-analyses with undeclared support. Eight who replied that they had not received industry funding were added to those with non-profit or no support, and 3 who did not reply were added to those with industry support. This analysis did not change the results much.ConclusionTransparency is essential for readers to make their own judgment about medical interventions guided by the results of meta-analyses. We found that industry-supported meta-analyses are less transparent than meta-analyses with non-profit support or no support.
| S-EPMC2553412 | biostudies-literature
Project description:BackgroundDue to clinical and methodological diversity, clinical studies included in meta-analyses often differ in ways that lead to differences in treatment effects across studies. Meta-regression analysis is generally recommended to explore associations between study-level characteristics and treatment effect, however, three key pitfalls of meta-regression may lead to invalid conclusions. Our aims were to determine the frequency of these three pitfalls of meta-regression analyses, examine characteristics associated with the occurrence of these pitfalls, and explore changes between 2002 and 2012.MethodsA meta-epidemiological study of studies including aggregate data meta-regression analysis in the years 2002 and 2012. We assessed the prevalence of meta-regression analyses with at least 1 of 3 pitfalls: ecological fallacy, overfitting, and inappropriate methods to regress treatment effects against the risk of the analysed outcome. We used logistic regression to investigate study characteristics associated with pitfalls and examined differences between 2002 and 2012.ResultsOur search yielded 580 studies with meta-analyses, of which 81 included meta-regression analyses with aggregated data. 57 meta-regression analyses were found to contain at least one pitfall (70%): 53 were susceptible to ecological fallacy (65%), 14 had a risk of overfitting (17%), and 5 inappropriately regressed treatment effects against the risk of the analysed outcome (6%). We found no difference in the prevalence of meta-regression analyses with methodological pitfalls between 2002 and 2012, nor any study-level characteristic that was clearly associated with the occurrence of any of the pitfalls.ConclusionThe majority of meta-regression analyses based on aggregate data contain methodological pitfalls that may result in misleading findings.
| S-EPMC8207572 | biostudies-literature
Project description:ObjectivesProspectively registering study plans in a permanent time-stamped and publicly accessible document is becoming more common across disciplines and aims to reduce risk of bias and make risk of bias transparent. Selective reporting persists, however, when researchers deviate from their registered plans without disclosure. This systematic review aimed to estimate the prevalence of undisclosed discrepancies between prospectively registered study plans and their associated publication. We further aimed to identify the research disciplines where these discrepancies have been observed, whether interventions to reduce discrepancies have been conducted, and gaps in the literature.DesignSystematic review and meta-analyses.Data sourcesScopus and Web of Knowledge, published up to 15 December 2019.Eligibility criteriaArticles that included quantitative data about discrepancies between registrations or study protocols and their associated publications.Data extraction and synthesisEach included article was independently coded by two reviewers using a coding form designed for this review (osf.io/728ys). We used random-effects meta-analyses to synthesise the results.ResultsWe reviewed k=89 articles, which included k=70 that reported on primary outcome discrepancies from n=6314 studies and, k=22 that reported on secondary outcome discrepancies from n=1436 studies. Meta-analyses indicated that between 29% and 37% (95% CI) of studies contained at least one primary outcome discrepancy and between 50% and 75% (95% CI) contained at least one secondary outcome discrepancy. Almost all articles assessed clinical literature, and there was considerable heterogeneity. We identified only one article that attempted to correct discrepancies.ConclusionsMany articles did not include information on whether discrepancies were disclosed, which version of a registration they compared publications to and whether the registration was prospective. Thus, our estimates represent discrepancies broadly, rather than our target of undisclosed discrepancies between prospectively registered study plans and their associated publications. Discrepancies are common and reduce the trustworthiness of medical research. Interventions to reduce discrepancies could prove valuable.Registrationosf.io/ktmdg. Protocol amendments are listed in online supplemental material A.
| S-EPMC10551944 | biostudies-literature
Project description:Background Well-conducted meta-analyses are considered to be at the top of the evidence-based hierarchy pyramid, with an expansion of these publications within the cardiovascular research arena. There are limited data evaluating the trends and quality of such publications. The objective of this study was to evaluate the methodological rigor and temporal trends of cardiovascular medicine-related meta-analyses published in the highest impact journals. Methods and Results Using the Medline database, we retrieved cardiovascular medicine-related systematic reviews and meta-analyses published in The New England Journal of Medicine, The Lancet, Journal of the American Medical Association, The British Medical Journal, Annals of Internal Medicine, Circulation, European Heart Journal, and Journal of American College of Cardiology between January 1, 2012 and December 31, 2018. Among 6406 original investigations published during the study period, meta-analyses represented 422 (6.6%) articles, with an annual decline in the proportion of published meta-analyses (8.7% in 2012 versus 4.6% in 2018, Ptrend=0.002). A substantial number of studies failed to incorporate elements of Preferred Reporting Items for Systematic Reviews and Meta-Analyses or Meta-Analysis of Observational Studies in Epidemiology guidelines (51.9%) and only a minority of studies (10.4%) were registered in PROSPERO (International Prospective Register of Systematic Reviews). Fewer manuscripts failed to incorporate the Preferred Reporting Items for Systematic Reviews and Meta-Analyses or Meta-Analysis of Observational Studies in Epidemiology elements over time (60.2% in 2012 versus 40.0% in 2018, Ptrend<0.001) whereas the number of meta-analyses registered at PROSPERO has increased (2.4% in 2013 versus 17.5% in 2018, Ptrend<0.001). Conclusions The proportion of cardiovascular medicine-related meta-analyses published in the highest impact journals has declined over time. Although there is an increasing trend in compliance with quality-based guidelines, the overall compliance remains low.
| S-EPMC8649500 | biostudies-literature
Project description:Methodological quality of meta-analyses on hypertension treatments can affect treatment decision-making. The authors conducted a cross-sectional study to investigate the methodological quality of meta-analyses on hypertension treatments. One hundred and fifty-eight meta-analyses were identified. Overall, methodological quality was unsatisfactory in the following aspects: comprehensive reporting of financial support (1.9%), provision of included and excluded lists of studies (22.8%), inclusion of grey literature (27.2%), and inclusion of protocols (32.9%). The 126 non-Cochrane meta-analyses had poor performance on almost all the methodological items. Non-Cochrane meta-analyses focused on nonpharmacologic treatments were more likely to consider scientific quality of included studies when making conclusions. The 32 Cochrane meta-analyses generally had good methodological quality except for comprehensive reporting of the sources of support. These results highlight the need for cautious interpretation of these meta-analyses, especially among physicians and policy makers when guidelines are formulated. Future meta-analyses should pay attention to improving these methodological aspects.
| S-EPMC8030759 | biostudies-literature