Dataset Information

Selective reporting bias in randomised controlled trials from two network meta-analyses: comparison of clinical trial registrations and their respective publications.

ABSTRACT: OBJECTIVE:To determine (i) the difference in the frequency of serious adverse events (SAEs) reported in trial registrations and their respective primary publications and (ii) the effect of adding SAE data from registries to a network meta-analysis (NMA) in changing the surface under the cumulative ranking (SUCRA) curve values of interventions. DESIGN:Secondary analysis of primary publications from two NMAs. ELIGIBILITY CRITERIA FOR SELECTING STUDIES:We included randomised trials published in English after 2005 that were included in two NMAs of pharmacological interventions for Alzheimer's disease and chronic obstructive pulmonary disease. DATA EXTRACTION:Two reviewers independently searched multiple international trial registries for registration status and abstracted data from the included study publications and ClinicalTrials.gov. RESULTS:Of the 203 randomised trials included, 140 (69.0%) were registered with a trial registry and 72 (35.5%) posted results in the registry. The proportion of registered trials increased over time (38.5% in 2005 vs 78.6% in 2014). Of the publications with results posted in a trial registry, 14 (19.4%) had inconsistent reporting of overall SAEs; 7 (10.4%) studies did not report SAEs in the publication but did in the registry. In the 134 randomised trials with a prespecified primary outcome in the registry, 19 studies (9.4%) had a change in the primary outcome in the publication. Adding SAEs reported in registries to the NMAs did not affect the ranking of interventions. CONCLUSION:We identified inconsistent reporting of SAEs in randomised trials that were included in two NMAs. Findings highlight the importance of including trial registries in the grey literature search and verifying safety data before incorporating it into NMAs. STUDY REGISTRATION:osf.io/mk6dr.

SUBMITTER: Wong EK

PROVIDER: S-EPMC6731894 | biostudies-other | 2019 Sep

REPOSITORIES: biostudies-other

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Selective reporting bias in randomised controlled trials from two network meta-analyses: comparison of clinical trial registrations and their respective publications.

Wong Eric Kc EK Lachance Chantelle C CC Page Matthew J MJ Watt Jennifer J Veroniki Areti A Straus Sharon E SE Tricco Andrea C AC

BMJ open 20190905 9

<h4>Objective</h4>To determine (i) the difference in the frequency of serious adverse events (SAEs) reported in trial registrations and their respective primary publications and (ii) the effect of adding SAE data from registries to a network meta-analysis (NMA) in changing the surface under the cumulative ranking (SUCRA) curve values of interventions.<h4>Design</h4>Secondary analysis of primary publications from two NMAs.<h4>Eligibility criteria for selecting studies</h4>We included randomised t ...[more]

PMID: 31492792

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Project description:Objectives: We aimed to study the prevalence of selective reporting of primary and secondary outcomes in tinnitus trials and to examine if selective reporting of outcome measures is influenced by the nature and direction of its results. Background: Selective reporting of outcome measures has been reported in several biomedical fields and can influence the clinical usefulness and implementation of outcomes of clinical trials. It is reported as one of the obstacles in finding an effective intervention for tinnitus. Methods: ClinicalTrials.gov (CT.gov) was used to identify all registered interventional tinnitus trials up to December 2015. A standardized search was used to find corresponding publications up to March 2018. The prespecified outcomes in CT.gov were compared with the outcomes reported in corresponding publication(s). The effects of the (lack of) statistical significance of trial results and the effects of funding source on record adherence were evaluated. Changes in registration elements were assessed with the Archive site of CT.gov. Results: We found corresponding publications for 60 (64.5%) of 93 eligible tinnitus trials registered in CT.gov. Of all the publications, five (7.5%) fully reported outcome measures entirely in line with the prespecified outcome measures. Discrepancies between the prespecified and reported outcomes were found in a total of 51 (76.1%) of the studies for primary outcomes, whereas 62 (92.5%) of the studies had discrepancies in secondary outcomes. In secondary outcomes, statistical significance of trial results influenced CT.gov record adherence. In addition, there was a statistically significant difference in the rate of discrepancy in industry-funded [n = 98 (87.5%) discrepant outcomes] and non-industry funded trials [n = 172 (74.5%) discrepant outcomes] (p = 0.01). Finally, 15 (25.9%) trialists made modifications in registered outcome measures during or after the trial period. Conclusion: Tinnitus trials suffer from substantial outcome reporting bias. Awareness of its presence must be raised to limit the obstacles of finding an effective intervention for tinnitus.

Project description:ObjectiveTo investigate the planning of subgroup analyses in protocols of randomised controlled trials and the agreement with corresponding full journal publications.DesignCohort of protocols of randomised controlled trial and subsequent full journal publications.SettingSix research ethics committees in Switzerland, Germany, and Canada.Data sources894 protocols of randomised controlled trial involving patients approved by participating research ethics committees between 2000 and 2003 and 515 subsequent full journal publications.ResultsOf 894 protocols of randomised controlled trials, 252 (28.2%) included one or more planned subgroup analyses. Of those, 17 (6.7%) provided a clear hypothesis for at least one subgroup analysis, 10 (4.0%) anticipated the direction of a subgroup effect, and 87 (34.5%) planned a statistical test for interaction. Industry sponsored trials more often planned subgroup analyses compared with investigator sponsored trials (195/551 (35.4%) v 57/343 (16.6%), P<0.001). Of 515 identified journal publications, 246 (47.8%) reported at least one subgroup analysis. In 81 (32.9%) of the 246 publications reporting subgroup analyses, authors stated that subgroup analyses were prespecified, but this was not supported by 28 (34.6%) corresponding protocols. In 86 publications, authors claimed a subgroup effect, but only 36 (41.9%) corresponding protocols reported a planned subgroup analysis.ConclusionsSubgroup analyses are insufficiently described in the protocols of randomised controlled trials submitted to research ethics committees, and investigators rarely specify the anticipated direction of subgroup effects. More than one third of statements in publications of randomised controlled trials about subgroup prespecification had no documentation in the corresponding protocols. Definitive judgments regarding credibility of claimed subgroup effects are not possible without access to protocols and analysis plans of randomised controlled trials.

Project description:BACKGROUND: Previous reviews show that reporting guidelines have improved the quality of trial reports in medicine, yet existing guidelines may not be fully suited for social and psychological intervention trials. OBJECTIVE/DESIGN: We conducted a two-part study that reviewed (1) reporting guidelines for and (2) the reporting quality of social and psychological intervention trials. DATA SOURCES: (1) To identify reporting guidelines, we systematically searched multiple electronic databases and reporting guideline registries. (2) To identify trials, we hand-searched 40 journals with the 10 highest impact factors in clinical psychology, criminology, education, and social work. ELIGIBILITY: (1) Reporting guidelines consisted of articles introducing a checklist of reporting standards relevant to social and psychological intervention trials. (2) Trials reported randomised experiments of complex interventions with psychological, social, or health outcomes. RESULTS: (1) We identified 19 reporting guidelines that yielded 147 reporting standards relevant to social and psychological interventions. Social and behavioural science guidelines included 89 standards not found in CONSORT guidelines. However, CONSORT guidelines used more recommended techniques for development and dissemination compared to other guidelines. (2) Our review of trials (n?=?239) revealed that many standards were poorly reported, such as identification as a randomised trial in titles (20% reported the information) and abstracts (55%); information about blinding (15%), sequence generation (23%), and allocation concealment (17%); and details about actual delivery of experimental (43%) and control interventions (34%), participant uptake (25%), and service environment (28%). Only 11 of 40 journals referenced reporting guidelines in "Instructions to Authors." CONCLUSION: Existing reporting guidelines have important limitations in content, development, and/or dissemination. Important details are routinely missing from trial publications; most leading journals in social and behavioural sciences do not ask authors to follow reporting standards. Findings demonstrate a need to develop a CONSORT extension with updated standards for social and psychological intervention trials.

Project description:BackgroundNetwork meta-analysis (NMA), a generalization of conventional MA, allows for assessing the relative effectiveness of multiple interventions. Reporting bias is a major threat to the validity of MA and NMA. Numerous methods are available to assess the robustness of MA results to reporting bias. We aimed to extend such methods to NMA.MethodsWe introduced 2 adjustment models for Bayesian NMA. First, we extended a meta-regression model that allows the effect size to depend on its standard error. Second, we used a selection model that estimates the propensity of trial results being published and in which trials with lower propensity are weighted up in the NMA model. Both models rely on the assumption that biases are exchangeable across the network. We applied the models to 2 networks of placebo-controlled trials of 12 antidepressants, with 74 trials in the US Food and Drug Administration (FDA) database but only 51 with published results. NMA and adjustment models were used to estimate the effects of the 12 drugs relative to placebo, the 66 effect sizes for all possible pair-wise comparisons between drugs, probabilities of being the best drug and ranking of drugs. We compared the results from the 2 adjustment models applied to published data and NMAs of published data and NMAs of FDA data, considered as representing the totality of the data.ResultsBoth adjustment models showed reduced estimated effects for the 12 drugs relative to the placebo as compared with NMA of published data. Pair-wise effect sizes between drugs, probabilities of being the best drug and ranking of drugs were modified. Estimated drug effects relative to the placebo from both adjustment models were corrected (i.e., similar to those from NMA of FDA data) for some drugs but not others, which resulted in differences in pair-wise effect sizes between drugs and ranking.ConclusionsIn this case study, adjustment models showed that NMA of published data was not robust to reporting bias and provided estimates closer to that of NMA of FDA data, although not optimal. The validity of such methods depends on the number of trials in the network and the assumption that conventional MAs in the network share a common mean bias mechanism.

Project description:BackgroundClinical trials on Traditional Chinese Medicine (TCM) should be registered in a publicly accessible international trial register and report on all outcomes. We systematically assessed and evaluated TCM trials in registries with their subsequent publications.ObjectiveTo describe the characteristics of TCM trials, estimate bias risk and outcome-reporting bias in clinical trials.Data sources and study selectionFifteen trial registries were searched from their inception to July 2012 to identify randomised trials on TCM including Chinese herbs, acupuncture and/or moxibustion, cupping, tuina, qigong, etc.Data extractionWe extracted data including TCM specialty and treated disease/conditions from the registries and searched for subsequent publications in PubMed and Chinese databases. We compared information in the registries of completed trials with any publications focusing on study design, sample size, randomisation, bias risk including reporting bias from the register protocol.Results1096 registered randomised trials were identified evaluating TCM, of which 505 were completed studies (46.1%). The most frequent conditions were pain (13.3%), musculoskeletal (11.7%), nervous (8.7%), digestive (7.1%), circulatory (6.5%), respiratory (6.3%), mental and behavioural disorders (6.2%) and cancer (6.0%). The trial register data identified parallel, phase II/III randomised trials with sample size estimations and blinding, but limited information about randomisation (sequence generation and allocation concealment). Comparing trial registration data of 115 completed trials (22.8%) with their subsequent 136 publications, inconsistencies were identified in one or more of the following: sample size (11%), outcome assessor blinding (37.5%), primary outcomes (29%) and safety (28%) reporting.ConclusionsIncreasing numbers of clinical trials investigating a variety of TCM interventions have been registered in international trial registries. The study design of registered TCM trials has improved in estimating sample size, use of blinding and placebos. However, selective outcome reporting is widespread and similar to conventional medicine and therefore study conclusions should be interpreted with caution.

Project description:ObjectiveTo investigate the impact of industry funding on reporting of subgroup analyses in randomised controlled trials.DesignSystematic review.Data sourcesMedline.Study selectionRandomised controlled trials published in 118 core clinical journals (defined by the National Library of Medicine) in 2007. 1140 study reports in a 1:1 ratio by high (five general medicine journals with largest number of total citations in 2007) versus lower impact journals, were randomly sampled. Two reviewers, independently and in duplicate, used standardised, piloted forms to screen study reports for eligibility and to extract data. They also used explicit criteria to determine whether a randomised controlled trial reported subgroup analyses. Logistic regression was used to examine the association of prespecified study characteristics with reporting versus not reporting of subgroup analyses.Results469 randomised controlled trials were included, of which 207 (44%) reported subgroup analyses. High impact journals (adjusted odds ratio 2.64, 95% confidence interval 1.62 to 4.33), non-surgical (versus surgical) trials (2.10, 1.26 to 3.50), and larger sample size (3.38, 1.64 to 6.99) were associated with more frequent reporting of subgroup analyses. The strength of association between trial funding and reporting of subgroups differed in trials with and without statistically significant primary outcomes (interaction P=0.02). In trials without statistically significant results for the primary outcome, industry funded trials were more likely to report subgroup analyses (2.29, 1.30 to 4.72) than non-industry funded trials. This was not true for trials with a statistically significant primary outcome (0.79, 0.46 to 1.36). Industry funded trials were associated with less frequent prespecification of subgroup hypotheses (31.3% v 38.0%, adjusted odds ratio 0.49, 0.26 to 0.94), and less use of the interaction test for analyses of subgroup effects (41.4% v 49.1%, 0.52, 0.28 to 0.97) than non-industry funded trials.ConclusionIndustry funded randomised controlled trials, in the absence of statistically significant primary outcomes, are more likely to report subgroup analyses than non-industry funded trials. Industry funded trials less frequently prespecify subgroup hypotheses and less frequently test for interaction than non-industry funded trials. Subgroup analyses from industry funded trials with negative results for the primary outcome should be viewed with caution.

Dataset Information

Selective reporting bias in randomised controlled trials from two network meta-analyses: comparison of clinical trial registrations and their respective publications.

Publications

Selective reporting bias in randomised controlled trials from two network meta-analyses: comparison of clinical trial registrations and their respective publications.

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