Citation bias in the CONSORT comments on blinding
About: This article is published in BMJ.The article was published on 2010-01-01 and is currently open access. It has received 793 citations till now. The article focuses on the topics: Blinding.
Citations
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Queen Mary University of London1, Durham University2, University of Bristol3, Charité4, National Institutes of Health5, Liverpool School of Tropical Medicine6, University of Southampton7, University of Tasmania8, AstraZeneca9, University of Edinburgh10, Cardiff University11, Medical Research Council12, University of Florida13, University of Sydney14, Janssen Pharmaceutica15, University of Bern16
TL;DR: The ARRIVE guidelines are revised to update them and facilitate their use in practice and this explanation and elaboration document was developed as part of the revision.
Abstract: Improving the reproducibility of biomedical research is a major challenge. Transparent and accurate reporting is vital to this process; it allows readers to assess the reliability of the findings and repeat or build upon the work of other researchers. The ARRIVE guidelines (Animal Research: Reporting In Vivo Experiments) were developed in 2010 to help authors and journals identify the minimum information necessary to report in publications describing in vivo experiments. Despite widespread endorsement by the scientific community, the impact of ARRIVE on the transparency of reporting in animal research publications has been limited. We have revised the ARRIVE guidelines to update them and facilitate their use in practice. The revised guidelines are published alongside this paper. This explanation and elaboration document was developed as part of the revision. It provides further information about each of the 21 items in ARRIVE 2.0, including the rationale and supporting evidence for their inclusion in the guidelines, elaboration of details to report, and examples of good reporting from the published literature. This document also covers advice and best practice in the design and conduct of animal studies to support researchers in improving standards from the start of the experimental design process through to publication.
961 citations
University of Bologna1, Sapienza University of Rome2, University of Padua3, University of Turin4, University of Catania5, Academy for Urban School Leadership6, University of Florence7, University of Palermo8, University of Naples Federico II9, University of Udine10, The Catholic University of America11, University of Rome Tor Vergata12, Seconda Università degli Studi di Napoli13, University of Bari14, Catholic University of the Sacred Heart15, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico16
TL;DR: Long-term HA administration prolongs overall survival and might act as a disease modifying treatment in patients with decompensated cirrhosis in this trial.
290 citations
TL;DR: The CONSORT-AI (Consolidated Standards of Reporting Trials–Artificial Intelligence) extension is a new reporting guideline for clinical trials evaluating interventions with an AI component that will assist editors and peer reviewers to understand, interpret and critically appraise the quality of clinical trial design and risk of bias in the reported outcomes.
Abstract: The CONSORT 2010 (Consolidated Standards of Reporting Trials) statement provides minimum guidelines for reporting randomised trials. Its widespread use has been instrumental in ensuring transparency when evaluating new interventions. More recently, there has been a growing recognition that interventions involving artificial intelligence (AI) need to undergo rigorous, prospective evaluation to demonstrate impact on health outcomes.The CONSORT-AI extension is a new reporting guideline for clinical trials evaluating interventions with an AI component. It was developed in parallel with its companion statement for clinical trial protocols: SPIRIT-AI. Both guidelines were developed through a staged consensus process, involving a literature review and expert consultation to generate 29 candidate items, which were assessed by an international multi-stakeholder group in a two-stage Delphi survey (103 stakeholders), agreed on in a two-day consensus meeting (31 stakeholders) and refined through a checklist pilot (34 participants).The CONSORT-AI extension includes 14 new items, which were considered sufficiently important for AI interventions, that they should be routinely reported in addition to the core CONSORT 2010 items. CONSORT-AI recommends that investigators provide clear descriptions of the AI intervention, including instructions and skills required for use, the setting in which the AI intervention is integrated, the handling of inputs and outputs of the AI intervention, the human-AI interaction and providing analysis of error cases.CONSORT-AI will help promote transparency and completeness in reporting clinical trials for AI interventions. It will assist editors and peer-reviewers, as well as the general readership, to understand, interpret and critically appraise the quality of clinical trial design and risk of bias in the reported outcomes.
285 citations
TL;DR: The CONSORT extension to randomised crossover trials is presented, which aims to facilitate better reporting of crossover trials and revision of the CONSORT 2010 checklist is revised for crossover designs.
Abstract: Evidence shows the quality of reporting of randomised controlled trials is not optimal. The lack of transparent reporting impedes readers from judging the reliability and validity of trial findings, prevents researchers from extracting information for systematic reviews, and results in research waste. The Consolidated Standards of Reporting Trials (CONSORT) statement was developed to improve the reporting of randomised controlled trials. The primary focus of the statement was on parallel group trials with two treatment groups. Crossover trials are a particular type of trial for chronic conditions in which participants are randomised to a sequence of interventions. They are a useful and efficient design because participants act as their own control. However, the reporting of crossover trials has been variable and incomplete, which hinders their use in clinical decision making and by future researchers. We present the CONSORT extension to randomised crossover trials, which aims to facilitate better reporting of crossover trials. The CONSORT 2010 checklist is revised for crossover designs, and introduces a modified flowchart and baseline table to enhance transparency. Examples of good reporting and evidence based rationale for CONSORT crossover checklist items are provided.
263 citations
TL;DR: Methylprednisolone pulse administration at the beginning of the early pulmonary phase of illness decreased the mortality rate and improved pulmonary involvement, oxygen saturation and inflammatory markers in COVID-19 patients.
Abstract: Background There are no determined treatment agents for the severe coronavirus disease 2019 (COVID-19); therefore, it is suggested that methylprednisolone, as an immunosuppressive treatment, can reduce the inflammation of the respiratory system. Methods We conducted a single-blind, randomised, controlled, clinical trial involving severe hospitalised patients with confirmed COVID-19 at the early pulmonary phase of the illness in Iran. The patients were randomly allocated in a 1:1 ratio by block randomisation method to receive standard care with methylprednisolone pulse (intravenous injection, 250 mg·day−1 for 3 days) or standard care alone. The study endpoint was the time of clinical improvement or death, whichever came first. Primary and safety analysis was done in the intention-to-treat (ITT) population. Results Sixty-eight eligible patients underwent randomisation (34 patients in each group) from April 20, till Jun 20, 2020. In the standard care group, six patients received corticosteroids by the attending physician during treatment and excluded from the ITT population. Patients with clinical improvement were higher in the methylprednisolone group than in the standard care group (94·1% versus 57·1%), and the mortality rate was numerically lower in the methylprednisolone group (5·9% versus 42.9%; p Conclusions Our results suggested that methylprednisolone pulse could be an efficient therapeutic agent for hospitalised severe COVID-19 patients at the pulmonary phase.
260 citations
References
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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
TL;DR: Whether vitamin C has an effect on the common cold has been a subject of controversy for at least 60 years, but what does the evidence show?
Abstract: Whether vitamin C has an effect on the common cold has been a subject of controversy for at least 60 years. What does the evidence show?
722 citations
TL;DR: No statistically significant effect of placebo interventions is found in four clinical conditions that had been investigated in three trials or more: pain, nausea, smoking, and depression, but confidence intervals were wide.
Abstract: Background
Placebo interventions are often claimed to substantially improve patient-reported and observer-reported outcomes in many clinical conditions, but most reports on effects of placebos are based on studies that have not randomised patients to placebo or no treatment Two previous versions of this review from 2001 and 2004 found that placebo interventions in general did not have clinically important effects, but that there were possible beneficial effects on patient-reported outcomes, especially pain Since then several relevant trials have been published
Objectives
Our primary aims were to assess the effect of placebo interventions in general across all clinical conditions, and to investigate the effects of placebo interventions on specific clinical conditions Our secondary aims were to assess whether the effect of placebo treatments differed for patient-reported and observer-reported outcomes, and to explore other reasons for variations in effect
Search methods
We searched the Cochrane Central Register of Controlled Trials (CENTRAL, The Cochrane Library Issue 4, 2007), MEDLINE (1966 to March 2008), EMBASE (1980 to March 2008), PsycINFO (1887 to March 2008) and Biological Abstracts (1986 to March 2008) We contacted experts on placebo research, and read references in the included trials
Selection criteria
We included randomised placebo trials with a no-treatment control group investigating any health problem
Data collection and analysis
Two authors independently assessed trial quality and extracted data We contacted study authors for additional information Trials with binary data were summarised using relative risk (a value of less than 1 indicates a beneficial effect of placebo), and trials with continuous outcomes were summarised using standardised mean difference (a negative value indicates a beneficial effect of placebo)
Main results
Outcome data were available in 202 out of 234 included trials, investigating 60 clinical conditions We regarded the risk of bias as low in only 16 trials (8%), five of which had binary outcomes
In 44 studies with binary outcomes (6041 patients), there was moderate heterogeneity (P < 0001; I2 45%) but no clear difference in effects between small and large trials (symmetrical funnel plot) The overall pooled effect of placebo was a relative risk of 093 (95% confidence interval (CI) 088 to 099) The pooled relative risk for patient-reported outcomes was 093 (95% CI 086 to 100) and for observer-reported outcomes 093 (95% CI 085 to 102) We found no statistically significant effect of placebo interventions in four clinical conditions that had been investigated in three trials or more: pain, nausea, smoking, and depression, but confidence intervals were wide The effect on pain varied considerably, even among trials with low risk of bias
In 158 trials with continuous outcomes (10,525 patients), there was moderate heterogeneity (P < 0001; I2 42%), and considerable variation in effects between small and large trials (asymmetrical funnel plot) It is therefore a questionable procedure to pool all the trials, and we did so mainly as a basis for exploring causes for heterogeneity We found an overall effect of placebo treatments, standardised mean difference (SMD) -023 (95% CI -028 to -017) The SMD for patient-reported outcomes was -026 (95% CI -032 to -019), and for observer-reported outcomes, SMD -013 (95% CI -024 to -002) We found an effect on pain, SMD -028 (95% CI -036 to -019)); nausea, SMD -025 (-046 to -004)), asthma (-035 (-070 to -001)), and phobia (SMD -063 (95% CI -117 to -008)) The effect on pain was very variable, also among trials with low risk of bias Four similarly-designed acupuncture trials conducted by an overlapping group of authors reported large effects (SMD -068 (-085 to -050)) whereas three other pain trials reported low or no effect (SMD -013 (-028 to 003)) The pooled effect on nausea was small, but consistent The effects on phobia and asthma were very uncertain due to high risk of bias There was no statistically significant effect of placebo interventions in the seven other clinical conditions investigated in three trials or more: smoking, dementia, depression, obesity, hypertension, insomnia and anxiety, but confidence intervals were wide
Meta-regression analyses showed that larger effects of placebo interventions were associated with physical placebo interventions (eg sham acupuncture), patient-involved outcomes (patient-reported outcomes and observer-reported outcomes involving patient cooperation), small trials, and trials with the explicit purpose of studying placebo Larger effects of placebo were also found in trials that did not inform patients about the possible placebo intervention
Authors' conclusions
We did not find that placebo interventions have important clinical effects in general However, in certain settings placebo interventions can influence patient-reported outcomes, especially pain and nausea, though it is difficult to distinguish patient-reported effects of placebo from biased reporting The effect on pain varied, even among trials with low risk of bias, from negligible to clinically important Variations in the effect of placebo were partly explained by variations in how trials were conducted and how patients were informed
527 citations
TL;DR: Analysis of data showed that ascorbic acid had at best only a minor influence on the duration and severity of colds, and that the effects demonstrated might be explained equally well by a break in the double blind.
Abstract: Three hundred eleven employees of the National Institutes of Health volunteered to take 1 gm of ascorbic acid or lactose placebo in capsules three times a day for nine months. At the onset of a cold, the volunteers were given an additional 3 gm daily of either a placebo or ascorbic acid. One hundred ninety volunteers completed the study. Dropouts were defined as those who missed at least one month of drug ingestion. They represented 44% of the placebo group and 34% of those taking ascorbic acid. Analysis of these data showed that ascorbic acid had at best only a minor influence on the duration and severity of colds, and that the effects demonstrated might be explained equally well by a break in the double blind. (JAMA231:1038-1042, 1975)
232 citations
TL;DR: In this article, the authors examined double blind trials of two or more non-steroidal anti-inflammatory drugs in rheumatoid arthritis to see whether there was any bias in the references they cited.
Abstract: Articles published before 1985 describing double blind trials of two or more non-steroidal anti-inflammatory drugs in rheumatoid arthritis were examined to see whether there was any bias in the references they cited. Althogether 244 articles meeting the criteria were found through a Medline search and through examining the reference lists of the articles retrieved. The drugs compared in the studies were classified as new or as control drugs and the outcome of the trial as positive or not positive. The reference lists of all papers with references to other trials on the new drug were then examined for reference bias. Positive bias was judged to have occurred if the reference list contained a higher proportion of references with a positive outcome for that drug than among all the articles assumed to have been available to the authors (those published more than two years earlier than the index article). Altogether 133 of the 244 articles were excluded for various reasons--for example, 44 because of multiple publication and 19 because they had no references. Among the 111 articles analysed bias was not possible in the references of 35 (because all the references gave the same outcome); 10 had a neutral selection of references, 22 a negative selection, and 44 a positive selection--a significant positive bias. This bias was not caused by better scientific standing of the cited articles over the uncited ones. Thus retrieving literature by scanning reference lists may produce a biased sample of articles, and reference bias may also render the conclusions of an article less reliable.
207 citations