The CONSORT statement: revised recommendations for improving the quality of reports of parallel-group randomized trials

To comprehend the results of a randomized controlled trial (RCT), readers must understand its design, conduct, analysis, and interpretation. That goal can be achieved only through complete transparency from authors. Despite several decades of educational efforts, the reporting of RCTs needs improvement. Investigators and editors developed the original CONSORT (Consolidated Standards of Reporting Trials) statement to help authors improve reporting by using a checklist and flow diagram. The revised CONSORT statement presented in this article incorporates new evidence and addresses some criticisms of the original statement. The checklist items pertain to the content of the Title, Abstract, Introduction, Methods, Results, and Comment. The revised checklist includes 22 items selected because empirical evidence indicates that not reporting the information is associated with biased estimates of treatment effect or because the information is essential to judge the reliability or relevance of the findings. We intended the flow diagram to depict the passage of participants through an RCT. The revised flow diagram depicts information from 4 stages of a trial (enrollment, intervention allocation, follow-up, and analysis). The diagram explicitly includes the number of participants, according to each intervention group, included in the primary data analysis. Inclusion of these numbers allows the reader to judge whether the authors have performed an intention-to-treat analysis. In sum, the CONSORT statement is intended to improve the reporting of an RCT, enabling readers to understand a trial's conduct and to assess the validity of its results

Balance algorithm for cluster randomized trials

<p>Abstract</p> <p>Background</p> <p>Within cluster randomized trials no algorithms exist to generate a full enumeration of a block randomization, balancing for covariates across treatment arms. Furthermore, often for practical reasons multiple blocks are required to fully randomize a study, which may not have been well balanced within blocks.</p> <p>Results</p> <p>We present a convenient and easy to use randomization tool to undertake allocation concealed block randomization. Our algorithm highlights allocations that minimize imbalance between treatment groups across multiple baseline covariates.</p> <p>We demonstrate the algorithm using a cluster randomized trial in primary care (the PRE-EMPT Study) and show that the software incorporates a trade off between independent random allocations that were likely to be imbalanced, and predictable deterministic approaches that would minimise imbalance. We extend the methodology of single block randomization to allocate to multiple blocks conditioning on previous allocations.</p> <p>Conclusion</p> <p>The algorithm is included as Additional file <supplr sid="S1">1</supplr> and we advocate its use for robust randomization within cluster randomized trials.</p> <suppl id="S1"> <title> <p>Additional File 1</p> </title> <text> <p><b>Cluster randomization allocation algorithm version 1.</b> Algorithms scripted in R to provide robust cluster randomization.</p> </text> <file name="1471-2288-8-65-S1.zip"> <p>Click here for file</p> </file> </suppl

High prevalence of potential biases threatens the interpretation of trials in patients with chronic disease

BACKGROUND: The complexity of chronic diseases is a challenge for investigators conducting randomized trials. The causes for this include the often difficult control for confounding, the selection of outcomes from many potentially important outcomes, the risk of missing data with long follow-up and the detection of heterogeneity of treatment effects. Our aim was to assess such aspects of trial design and analysis for four prevalent chronic diseases. METHODS: We included 161 randomized trials on drug and non-drug treatments for chronic obstructive pulmonary disease, type 2 diabetes mellitus, stroke and heart failure, which were included in current Cochrane reviews. We assessed whether these trials defined a single outcome or several primary outcomes, statistically compared baseline characteristics to assess comparability of treatment groups, reported on between-group comparisons, and we also assessed how they handled missing data and whether appropriate methods for subgroups effects were used. RESULTS: We found that only 21% of all chronic disease trials had a single primary outcome, whereas 33% reported one or more primary outcomes. Two of the fifty-one trials that tested for statistical significance of baseline characteristics adjusted the comparison for a characteristic that was significantly different. Of the 161 trials, 10% reported a within-group comparison only; 17% (n = 28) of trials reported how missing data were handled (50% (n = 14) carried forward last values, 27% (n = 8) performed a complete case analysis, 13% (n = 4) used a fixed value imputation and 10% (n = 3) used more advanced methods); and 27% of trials performed a subgroup analysis but only 23% of them (n = 10) reported an interaction test. Drug trials, trials published after wide adoption of the CONSORT (CONsolidated Standards of Reporting Trials) statement (2001 or later) and trials in journals with higher impact factors were more likely to report on some of these aspects of trial design and analysis. CONCLUSION: Our survey showed that an alarmingly large proportion of chronic disease trials do not define a primary outcome, do not use appropriate methods for subgroup analyses, or use naïve methods to handle missing data, if at all. As a consequence, biases are likely to be introduced in many trials on widely prescribed treatments for patients with chronic disease

What kind of evidence is it that Evidence-Based Medicine advocates want health care providers and consumers to pay attention to?

BACKGROUND: In 1992, Evidence-Based Medicine advocates proclaimed a "new paradigm", in which evidence from health care research is the best basis for decisions for individual patients and health systems. Hailed in New York Times Magazine in 2001 as one of the most influential ideas of the year, this approach was initially and provocatively pitted against the traditional teaching of medicine, in which the key elements of knowing for clinical purposes are understanding of basic pathophysiologic mechanisms of disease coupled with clinical experience. This paper reviews the origins, aspirations, philosophical limitations, and practical challenges of evidence-based medicine. DISCUSSION: EBM has long since evolved beyond its initial (mis)conception, that EBM might replace traditional medicine. EBM is now attempting to augment rather than replace individual clinical experience and understanding of basic disease mechanisms. EBM must continue to evolve, however, to address a number of issues including scientific underpinnings, moral stance and consequences, and practical matters of dissemination and application. For example, accelerating the transfer of research findings into clinical practice is often based on incomplete evidence from selected groups of people, who experience a marginal benefit from an expensive technology, raising issues of the generalizability of the findings, and increasing problems with how many and who can afford the new innovations in care. SUMMARY: Advocates of evidence-based medicine want clinicians and consumers to pay attention to the best findings from health care research that are both valid and ready for clinical application. Much remains to be done to reach this goal

Outcome based subgroup analysis: a neglected concern

A subgroup of clinical trial subjects identified by baseline characteristics is a proper subgroup while a subgroup determined by post randomization events or measures is an improper subgroup. Both types of subgroups are often analyzed in clinical trial papers. Yet, the extensive scrutiny of subgroup analyses has almost exclusively attended to the former. The analysis of improper subgroups thereby not only flourishes in numerous disguised ways but also does so without a corresponding awareness of its pitfalls. Comparisons of the grade of angina in a heart disease trial, for example, usually include only the survivors. This paper highlights some of the distinct ways in which outcome based subgroup analysis occurs, describes the hazards associated with it, and proposes a simple alternative approach to counter its analytic bias. Data from six published trials show that outcome based subgroup analysis, like proper subgroup analysis, may be performed in a post-hoc fashion, overdone, selectively reported, and over interpreted. Six hypothetical trial scenarios illustrate the forms of hidden bias related to it. That bias can, however, be addressed by assigning clinically appropriate scores to the usually excluded subjects and performing an analysis that includes all the randomized subjects. A greater level of awareness about the practice and pitfalls of outcome based subgroup analysis is needed. When required, such an analysis should maintain the integrity of randomization. This issue needs greater practical and methodologic attention than has been accorded to it thus far

Pre-referral rectal artesunate in severe malaria: flawed trial

<p>Abstract</p> <p>Background</p> <p>Immediate injectable treatment is essential for severe malaria. Otherwise, the afflicted risk lifelong impairment or death. In rural areas of Africa and Asia, appropriate care is often miles away. In 2009, Melba Gomes and her colleagues published the findings of a randomized, placebo-controlled trial of rectal artesunate for suspected severe malaria in such remote areas. Enrolling nearly 18,000 cases, the aim was to evaluate whether, as patients were in transit to a health facility, a pre-referral artesunate suppository blocked disease progression sufficiently to reduce these risks. The affirmative findings of this, the only trial on the issue thus far, have led the WHO to endorse rectal artesunate as a pre-referral treatment for severe malaria. In the light of its public health importance and because its scientific quality has not been assessed for a systematic review, our paper provides a detailed evaluation of the design, conduct, analysis, reporting, and practical features of this trial.</p> <p>Results</p> <p>We performed a checklist-based and an in-depth evaluation of the trial. The evaluation criteria were based on the CONSORT statement for reporting clinical trials, the clinical trial methodology literature, and practice in malaria research. Our main findings are: The inclusion and exclusion criteria and the sample size justification are not stated. Many clearly ineligible subjects were enrolled. The training of the recruiters does not appear to have been satisfactory. There was excessive between center heterogeneity in design and conduct. Outcome evaluation schedule was not defined, and in practice, became too wide. Large gaps in the collection of key data were evident. Primary endpoints were inconsistently utilized and reported; an overall analysis of the outcomes was not done; analyses of time to event data had major flaws; the stated intent-to-treat analysis excluded a third of the randomized subjects; the design-indicated stratified or multi-variate analysis was not done; many improper subgroups were analyzed in a post-hoc fashion; the analysis and reporting metric was deficient. There are concerns relating to patient welfare at some centers. Exclusion of many cases from data analysis compromised external validity. A bias-controlled reanalysis of available data does not lend support to the conclusions drawn by the authors.</p> <p>Conclusions</p> <p>This trial has numerous serious deficiencies in design, implementation, and methods of data analysis. Interpretation and manner of reporting are wanting, and the applicability of the findings is unclear. The trial conduct could have been improved to better protect patient welfare. The totality of these problems make it a flawed study whose conclusions remain subject to appreciable doubt.</p

Reporting on covariate adjustment in randomised controlled trials before and after revision of the 2001 CONSORT statement: a literature review

<p>Abstract</p> <p>Objectives</p> <p>To evaluate the use and reporting of adjusted analysis in randomised controlled trials (RCTs) and compare the quality of reporting before and after the revision of the CONSORT Statement in 2001.</p> <p>Design</p> <p>Comparison of two cross sectional samples of published articles.</p> <p>Data Sources</p> <p>Journal articles indexed on PubMed in December 2000 and December 2006.</p> <p>Study Selection</p> <p>Parallel group RCTs with a full publication carried out in humans and published in English</p> <p>Main outcome measures</p> <p>Proportion of articles reported adjusted analysis; use of adjusted analysis; the reason for adjustment; the method of adjustment and the reporting of adjusted analysis results in the main text and abstract.</p> <p>Results</p> <p>In both cohorts, 25% of studies reported adjusted analysis (84/355 in 2000 vs 113/422 in 2006). Compared with articles reporting only unadjusted analyses, articles that reported adjusted analyses were more likely to specify primary outcomes, involve multiple centers, perform stratified randomization, be published in general medical journals, and recruit larger sample sizes. In both years a minority of articles explained why and how covariates were selected for adjustment (20% to 30%). Almost all articles specified the statistical methods used for adjustment (99% in 2000 vs 100% in 2006) but only 5% and 10%, respectively, reported both adjusted and unadjusted results as recommended in the CONSORT guidelines.</p> <p>Conclusion</p> <p>There was no evidence of change in the reporting of adjusted analysis results five years after the revision of the CONSORT Statement and only a few articles adhered fully to the CONSORT recommendations.</p

Protocol for a randomised controlled trial examining the impact of a web-based personally controlled health management system on the uptake of influenza vaccination rates

<p>Abstract</p> <p>Background</p> <p>Online social networking and personally controlled health management systems (PCHMS) offer a new opportunity for developing innovative interventions to prevent diseases of public health concern (e.g., influenza) but there are few comparative studies about patterns of use and impact of these systems.</p> <p>Methods/Design</p> <p>A 2010 CONSORT-compliant randomised controlled trial with a two-group parallel design will assess the efficacy of a web-based PCHMS called <it>Healthy.me </it>in facilitating the uptake of influenza vaccine amongst university students and staff. Eligible participants are randomised either to obtain access to <it>Healthy.me </it>or a 6-month waitlist. Participants complete pre-study, post-study and monthly surveys about their health and utilisation of health services. A post-study clinical audit will be conducted to validate self-reports about influenza vaccination and visits to the university health service due to influenza-like illness (ILI) amongst a subset of participants. 600 participants older than 18 years with monthly access to the Internet and email will be recruited. Participants who (i) discontinue the online registration process; (ii) report obtaining an influenza vaccination in 2010 before the commencement of the study; or (iii) report being influenced by other participants to undertake influenza vaccination will be excluded from analysis. The primary outcome measure is the number of participants obtaining influenza vaccination during the study. Secondary outcome measures include: number of participants (i) experiencing ILI symptoms, (ii) absent from or experiencing impairment in work or study due to ILI symptoms, (iii) using health services or medications due to ILI symptoms; (iv) expressing positive or negative attitudes or experiences towards influenza vaccination, via their reasons of receiving (or not receiving) influenza vaccine; and (v) their patterns of usage of <it>Healthy.me </it>(e.g., frequency and timing of hits, duration of access, uptake of specific functions).</p> <p>Discussion</p> <p>This study will provide new insights about the utility of online social networking and PCHMS for public health and health promotion. It will help to assess whether a web-based PCHMS, with connectivity to a health service provider, containing information and self-management tools, can improve the uptake of preventive health services amongst university students and staff.</p> <p>Trial registration</p> <p><a href="http://www.anzctr.org.au/ACTRN12610000386033.aspx">ACTRN12610000386033</a> (Australian New Zealand Clinical Trials Registry)</p