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Presentation of continuous outcomes in randomised trials: an observational study.

ABSTRACT: To characterise the percentage of available outcome data being presented in reports of randomised clinical trials with continuous outcome measures, thereby determining the potential for incomplete reporting bias.Descriptive cross sectional study.A random sample of 200 randomised trials from issues of 20 medical journals in a variety of specialties during 2007-09.For each paper's best reported primary outcome, we calculated the fraction of data reported using explicit scoring rules. For example, a two arm trial with 100 patients per limb that reported 2 sample sizes, 2 means, and 2 standard deviations reported 6/200 data elements (1.5%), but if that paper included a scatterplot with 200 points it would score 200/200 (100%). We also assessed compliance with 2001 CONSORT items about the reporting of results.The median percentage of data reported for the best reported continuous outcome was 9% (interquartile range 3-26%) but only 3.5% (3-7%) when we adjusted studies to 100 patients per arm to control for varying study size; 17% of articles showed 100% of the data. Tables were the predominant means of presenting the most data (59% of articles), but papers that used figures reported a higher proportion of data. There was substantial heterogeneity among journals with respect to our primary outcome and CONSORT compliance.We studied continuous outcomes of randomised trials in higher impact journals. Results may not apply to categorical outcomes, other study designs, or other journals.Trialists present only a small fraction of available data. This paucity of data may increase the potential for incomplete reporting bias, a failure to present all relevant information about a study's findings.

SUBMITTER: Schriger DL

PROVIDER: S-EPMC3668620 | biostudies-literature | 2012 Dec

REPOSITORIES: biostudies-literature

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Presentation of continuous outcomes in randomised trials: an observational study.

Schriger David L DL Savage Dan F DF Altman Douglas G DG

BMJ (Clinical research ed.) 20121218

<h4>Objective</h4>To characterise the percentage of available outcome data being presented in reports of randomised clinical trials with continuous outcome measures, thereby determining the potential for incomplete reporting bias.<h4>Design</h4>Descriptive cross sectional study.<h4>Data sources</h4>A random sample of 200 randomised trials from issues of 20 medical journals in a variety of specialties during 2007-09.<h4>Main outcome measures</h4>For each paper's best reported primary outcome, we ...[more]

PMID: 23249670

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Project description:BACKGROUND:In individually randomised trials we might expect interventions delivered in groups or by care providers to result in clustering of outcomes for participants treated in the same group or by the same care provider. In partially nested randomised controlled trials (pnRCTs) this clustering only occurs in one trial arm, commonly the intervention arm. It is important to measure and account for between-cluster variability in trial design and analysis. We compare analysis approaches for pnRCTs with continuous outcomes, investigating the impact on statistical inference of cluster sizes, coding of the non-clustered arm, intracluster correlation coefficient (ICCs), and differential variance between intervention and control arm, and provide recommendations for analysis. METHODS:We performed a simulation study assessing the performance of six analysis approaches for a two-arm pnRCT with a continuous outcome. These include: linear regression model; fully clustered mixed-effects model with singleton clusters in control arm; fully clustered mixed-effects model with one large cluster in control arm; fully clustered mixed-effects model with pseudo clusters in control arm; partially nested homoscedastic mixed effects model, and partially nested heteroscedastic mixed effects model. We varied the cluster size, number of clusters, ICC, and individual variance between the two trial arms. RESULTS:All models provided unbiased intervention effect estimates. In the partially nested mixed-effects models, methods for classifying the non-clustered control arm had negligible impact. Failure to account for even small ICCs resulted in inflated Type I error rates and over-coverage of confidence intervals. Fully clustered mixed effects models provided poor control of the Type I error rates and biased ICC estimates. The heteroscedastic partially nested mixed-effects model maintained relatively good control of Type I error rates, unbiased ICC estimation, and did not noticeably reduce power even with homoscedastic individual variances across arms. CONCLUSIONS:In general, we recommend the use of a heteroscedastic partially nested mixed-effects model, which models the clustering in only one arm, for continuous outcomes similar to those generated under the scenarios of our simulations study. However, with few clusters (3-6), small cluster sizes (5-10), and small ICC (?0.05) this model underestimates Type I error rates and there is no optimal model.

Project description:BackgroundRandomised controlled trials (RCTs) provide valuable information for developing harm profiles but current analysis practices to detect between-group differences are suboptimal. Drug trials routinely screen continuous clinical and biological data to monitor participant harm. These outcomes are regularly dichotomised into abnormal/normal values for analysis. Despite the simplicity gained for clinical interpretation, it is well established that dichotomising outcomes results in a considerable reduction in information and thus statistical power. We propose an automated procedure for the routine implementation of the distributional method for the dichotomisation of continuous outcomes proposed by Peacock and Sauzet, which retains the precision of the comparison of means.MethodsWe explored the use of a distributional approach to compare differences in proportions based on the comparison of means which retains the power of the latter. We applied this approach to the screening of clinical and biological data as a means to detect 'signals' for potential adverse drug reactions (ADRs). Signals can then be followed-up in further confirmatory studies. Three distributional methods suitable for different types of distributions are described. We propose the use of an automated approach using the observed data to select the most appropriate distribution as an analysis strategy in a RCT setting for multiple continuous outcomes. We illustrate this approach using data from three RCTs assessing the efficacy of mepolizumab in asthma or COPD. Published reference ranges were used to define the proportions of participants with abnormal values for a subset of 10 blood tests. The between-group distributional and empirical differences in proportions were estimated for each blood test and compared.ResultsWithin trials, the distributions varied across the 10 outcomes demonstrating value in a practical approach to selecting the distributional method in the context of multiple adverse event outcomes. Across trials, there were three outcomes where the method chosen by the automated procedure varied for the same outcome. The distributional approach identified three signals (eosinophils, haematocrit, and haemoglobin) compared to only one when using the Fisher's exact test (eosinophils) and two identified by use of the 95% confidence interval for the difference in proportions (eosinophils and potassium).ConclusionWhen dichotomisation of continuous adverse event outcomes aids clinical interpretation, we advocate use of a distributional approach to retain statistical power. Methods are now easy to implement. Retaining information is especially valuable in the context of the analysis of adverse events in RCTs. The routine implementation of this automated approach requires further evaluation.

Project description:OBJECTIVE:To assess the association between intake of non-sugar sweeteners (NSS) and important health outcomes in generally healthy or overweight/obese adults and children. DESIGN:Systematic review following standard Cochrane review methodology. DATA SOURCES:Medline (Ovid), Embase, Cochrane CENTRAL, WHO International Clinical Trials Registry Platform, Clinicaltrials.gov, and reference lists of relevant publications. ELIGIBILITY CRITERIA FOR SELECTING STUDIES:Studies including generally healthy adults or children with or without overweight or obesity were eligible. Included study designs allowed for a direct comparison of no intake or lower intake of NSS with higher NSS intake. NSSs had to be clearly named, the dose had to be within the acceptable daily intake, and the intervention duration had to be at least seven days. MAIN OUTCOME MEASURES:Body weight or body mass index, glycaemic control, oral health, eating behaviour, preference for sweet taste, cancer, cardiovascular disease, kidney disease, mood, behaviour, neurocognition, and adverse effects. RESULTS:The search resulted in 13?941 unique records. Of 56 individual studies that provided data for this review, 35 were observational studies. In adults, evidence of very low and low certainty from a limited number of small studies indicated a small beneficial effect of NSSs on body mass index (mean difference -0.6, 95% confidence interval -1.19 to -0.01; two studies, n=174) and fasting blood glucose (-0.16 mmol/L, -0.26 to -0.06; two, n=52). Lower doses of NSSs were associated with lower weight gain (-0.09 kg, -0.13 to -0.05; one, n=17?934) compared with higher doses of NSSs (very low certainty of evidence). For all other outcomes, no differences were detected between the use and non-use of NSSs, or between different doses of NSSs. No evidence of any effect of NSSs was seen on overweight or obese adults or children actively trying to lose weight (very low to moderate certainty). In children, a smaller increase in body mass index z score was observed with NSS intake compared with sugar intake (-0.15, -0.17 to -0.12; two, n=528, moderate certainty of evidence), but no significant differences were observed in body weight (-0.60 kg, -1.33 to 0.14; two, n=467, low certainty of evidence), or between different doses of NSSs (very low to moderate certainty). CONCLUSIONS:Most health outcomes did not seem to have differences between the NSS exposed and unexposed groups. Of the few studies identified for each outcome, most had few participants, were of short duration, and their methodological and reporting quality was limited; therefore, confidence in the reported results is limited. Future studies should assess the effects of NSSs with an appropriate intervention duration. Detailed descriptions of interventions, comparators, and outcomes should be included in all reports. SYSTEMATIC REVIEW REGISTRATION:Prospero CRD42017047668.

Project description:BackgroundDespite efforts to improve the accuracy and transparency of the design, conduct, and reporting of randomised controlled trials (RCTs), deficiencies remain. Such deficiencies contribute to significant, avoidable waste of health research investment and impede reproducibility. This study aimed to synthesise and critically analyse changes over time in the conduct and reporting of internationally published evidence on patient and/or population health-oriented RCTs conducted in one country.MethodsThis observational study drew on systematic review methods. We searched six databases for published RCTs (database inception to December 2018) where ≥ 80% of participants were recruited in the Republic of Ireland. RCTs of interventions targeted at patients, providers and/or policy makers intended to improve health, healthcare or health research were included. For each study, screening, data extraction and methodological quality appraisal were conducted by one member of the author team.ResultsFrom 17,560 titles and abstracts, 752 unique RCTs were published in 745 papers between 1968 and 2018, with a steady year-on-year increase since 1968. The number of participants was in the range of 2-8628. The majority were parallel design (86%) and classified as treatment evaluation. Of the 418 RCTs published since the introduction of mandatory clinical trial registration by the International Committee of Medical Journal Editors in 2005, 32% (n = 134) provided a trial registration number. This increased to 47% when taking studies published between 2013 and 2018 (n = 232). Since the 1996 publication of the CONSORT statement, 16% of included RCTs made specific reference to a standardised reporting guideline and this increased to 31% for more recent studies published between 2013 and 2018. Overall, 7% (n = 53) of studies referred to a published study protocol, increasing to 20% for studies published between 2013 and 2018.ConclusionEvidence from this single-country study of RCTs published in the international literature suggests that both the number overall, the number registered and the number referencing reporting guidelines have increased steadily over time. Despite widespread endorsement of reporting standards, reporting of RCTs remains suboptimal in domains such as compliance with the CONSORT statement and prospective trial registration. Researchers, funders and journal editors, nationally and internationally, should continue to focus on improving reporting and examining avoidable waste of health research investment.

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Presentation of continuous outcomes in randomised trials: an observational study.

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Presentation of continuous outcomes in randomised trials: an observational study.

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