Application of causal inference methods in the analyses of randomised controlled trials: a systematic review.
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SUBMITTER: Farmer RE
PROVIDER: S-EPMC5761133 | biostudies-literature | 2018 Jan
REPOSITORIES: biostudies-literature
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Project description:OBJECTIVE:Randomised controlled trials (RCT) are the gold standard to provide unbiased data. However, when patients have a treatment preference, randomisation may influence participation and outcomes (eg, external and internal validity). The aim of this study was to assess the influence of patients' preference in RCTs by analysing partially randomised patient preference trials (RPPT); an RCT and preference cohort combined. DESIGN:Systematic review and meta-analyses. DATA SOURCES:MEDLINE, Embase, PsycINFO and the Cochrane Library. ELIGIBILITY CRITERIA FOR SELECTING STUDIES:RPPTs published between January 2005 and October 2018 reporting on allocation of patients to randomised and preference cohorts were included. DATA EXTRACTION AND SYNTHESIS:Two independent reviewers extracted data. The main outcomes were the difference in external validity (participation and baseline characteristics) and internal validity (lost to follow-up, crossover and the primary outcome) between the randomised and the preference cohort within each RPPT, compared in a meta-regression using a Wald test. Risk of bias was not assessed, as no quality assessment for RPPTs has yet been developed. RESULTS:In total, 117 of 3734 identified articles met screening criteria and 44 were eligible (24 873 patients). The participation rate in RPPTs was >95% in 14 trials (range: 48%-100%) and the randomisation refusal rate was >50% in 26 trials (range: 19%-99%). Higher education, female, older age, race and prior experience with one treatment arm were characteristics of patients declining randomisation. The lost to follow-up and cross-over rate were significantly higher in the randomised cohort compared with the preference cohort. Following the meta-analysis, the reported primary outcomes were comparable between both cohorts of the RPPTs, mean difference 0.093 (95% CI -0.178 to 0.364, p=0.502). CONCLUSIONS:Patients' preference led to a substantial proportion of a specific patient group refusing randomisation, while it did not influence the primary outcome within an RPPT. Therefore, RPPTs could increase external validity without compromising the internal validity compared with RCTs. PROSPERO REGISTRATION NUMBER:CRD42019094438.
| S-EPMC6797441 | biostudies-other
Project description:IntroductionCausal methods have been adopted and adapted across health disciplines, particularly for the analysis of single studies. However, the sample sizes necessary to best inform decision-making are often not attainable with single studies, making pooled individual-level data analysis invaluable for public health efforts. Researchers commonly implement causal methods prevailing in their home disciplines, and how these are selected, evaluated, implemented and reported may vary widely. To our knowledge, no article has yet evaluated trends in the implementation and reporting of causal methods in studies leveraging individual-level data pooled from several studies. We undertake this review to uncover patterns in the implementation and reporting of causal methods used across disciplines in research focused on health outcomes. We will investigate variations in methods to infer causality used across disciplines, time and geography and identify gaps in reporting of methods to inform the development of reporting standards and the conversation required to effect change.Methods and analysisWe will search four databases (EBSCO, Embase, PubMed, Web of Science) using a search strategy developed with librarians from three universities (Heidelberg University, Harvard University, and University of California, San Francisco). The search strategy includes terms such as 'pool*', 'harmoniz*', 'cohort*', 'observational', variations on 'individual-level data'. Four reviewers will independently screen articles using Covidence and extract data from included articles. The extracted data will be analysed descriptively in tables and graphically to reveal the pattern in methods implementation and reporting. This protocol has been registered with PROSPERO (CRD42020143148).Ethics and disseminationNo ethical approval was required as only publicly available data were used. The results will be submitted as a manuscript to a peer-reviewed journal, disseminated in conferences if relevant, and published as part of doctoral dissertations in Global Health at the Heidelberg University Hospital.
| S-EPMC8593733 | biostudies-literature
Project description:INTRODUCTION:In some randomised trials, the primary interest is in the mechanisms by which an intervention exerts its effects on health outcomes. That is, clinicians and policy-makers may be interested in how the intervention works (or why it does not work) through hypothesised causal mechanisms. In this article, we highlight the value of understanding causal mechanisms in randomised trials by applying causal mediation analysis to two randomised trials of complex interventions. MAIN BODY:In the first example, we examine a potential mechanism by which an exercise programme for rheumatoid arthritis of the hand could improve hand function. In the second example, we explore why a rehabilitation programme for ankle fractures failed to improve lower-limb function through hypothesised mechanisms. We outline critical assumptions that are required for making valid causal inferences from these analyses, and provide results of sensitivity analyses that are used to assess the degree to which the estimated causal mediation effects could have been biased by residual confounding. CONCLUSION:This paper demonstrates how the application of causal mediation analyses to randomised trials can identify the mechanisms by which complex interventions exert their effects. We discuss methodological issues and assumptions that should be considered when mediation analyses of randomised trials are used to inform clinical practice and policy decisions.
| S-EPMC6708183 | biostudies-other
Project description:UNLABELLED:This review is an abridged version of a Cochrane Review previously published in the Cochrane Database of Systematic Reviews 2010, Issue 4, Art. No.: MR000013 DOI: 10.1002/14651858.MR000013.pub5 (see www.thecochranelibrary.com for information). Cochrane Reviews are regularly updated as new evidence emerges and in response to feedback, and Cochrane Database of Systematic Reviews should be consulted for the most recent version of the review. OBJECTIVE:To identify interventions designed to improve recruitment to randomised controlled trials, and to quantify their effect on trial participation. DESIGN:Systematic review. DATA SOURCES:The Cochrane Methodology Review Group Specialised Register in the Cochrane Library, MEDLINE, EMBASE, ERIC, Science Citation Index, Social Sciences Citation Index, C2-SPECTR, the National Research Register and PubMed. Most searches were undertaken up to 2010; no language restrictions were applied. STUDY SELECTION:Randomised and quasi-randomised controlled trials, including those recruiting to hypothetical studies. Studies on retention strategies, examining ways to increase questionnaire response or evaluating the use of incentives for clinicians were excluded. The study population included any potential trial participant (eg, patient, clinician and member of the public), or individual or group of individuals responsible for trial recruitment (eg, clinicians, researchers and recruitment sites). Two authors independently screened identified studies for eligibility. RESULTS:45 trials with over 43 000 participants were included. Some interventions were effective in increasing recruitment: telephone reminders to non-respondents (risk ratio (RR) 1.66, 95% CI 1.03 to 2.46; two studies, 1058 participants), use of opt-out rather than opt-in procedures for contacting potential participants (RR 1.39, 95% CI 1.06 to 1.84; one study, 152 participants) and open designs where participants know which treatment they are receiving in the trial (RR 1.22, 95% CI 1.09 to 1.36; two studies, 4833 participants). However, the effect of many other strategies is less clear, including the use of video to provide trial information and interventions aimed at recruiters. CONCLUSIONS:There are promising strategies for increasing recruitment to trials, but some methods, such as open-trial designs and opt-out strategies, must be considered carefully as their use may also present methodological or ethical challenges. Questions remain as to the applicability of results originating from hypothetical trials, including those relating to the use of monetary incentives, and there is a clear knowledge gap with regard to effective strategies aimed at recruiters.
| S-EPMC3586125 | biostudies-literature
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.
| S-EPMC6173170 | biostudies-literature
Project description:The usual development cycles are too slow for the development of vaccines, diagnostics and treatments in pandemics such as the ongoing SARS-CoV-2 pandemic. Given the pressure in such a situation, there is a risk that findings of early clinical trials are overinterpreted despite their limitations in terms of size and design. Motivated by a non-randomized open-label study investigating the efficacy of hydroxychloroquine in patients with COVID-19, we describe in a unified fashion various alternative approaches to the analysis of non-randomized studies. A widely used tool to reduce the impact of treatment-selection bias are so-called propensity score (PS) methods. Conditioning on the propensity score allows one to replicate the design of a randomized controlled trial, conditional on observed covariates. Extensions include the g-computation approach, which is less frequently applied, in particular in clinical studies. Moreover, doubly robust estimators provide additional advantages. Here, we investigate the properties of propensity score based methods including three variations of doubly robust estimators in small sample settings, typical for early trials, in a simulation study. R code for the simulations is provided.
| S-EPMC7834813 | biostudies-literature
Project description:BackgroundRecruitment of participants into randomised controlled trials (RCTs) is critical for successful trial conduct. Although there have been two previous systematic reviews on related topics, the results (which identified specific interventions) were inconclusive and not generalizable. The aim of our study was to evaluate the relative effectiveness of recruitment strategies for participation in RCTs.Methods and findingsA systematic review, using the PRISMA guideline for reporting of systematic reviews, that compared methods of recruiting individual study participants into an actual or mock RCT were included. We searched MEDLINE, Embase, The Cochrane Library, and reference lists of relevant studies. From over 16,000 titles or abstracts reviewed, 396 papers were retrieved and 37 studies were included, in which 18,812 of at least 59,354 people approached agreed to participate in a clinical RCT. Recruitment strategies were broadly divided into four groups: novel trial designs (eight studies), recruiter differences (eight studies), incentives (two studies), and provision of trial information (19 studies). Strategies that increased people's awareness of the health problem being studied (e.g., an interactive computer program [relative risk (RR) 1.48, 95% confidence interval (CI) 1.00-2.18], attendance at an education session [RR 1.14, 95% CI 1.01-1.28], addition of a health questionnaire [RR 1.37, 95% CI 1.14-1.66]), or a video about the health condition (RR 1.75, 95% CI 1.11-2.74), and also monetary incentives (RR1.39, 95% CI 1.13-1.64 to RR 1.53, 95% CI 1.28-1.84) improved recruitment. Increasing patients' understanding of the trial process, recruiter differences, and various methods of randomisation and consent design did not show a difference in recruitment. Consent rates were also higher for nonblinded trial design, but differential loss to follow up between groups may jeopardise the study findings. The study's main limitation was the necessity of modifying the search strategy with subsequent search updates because of changes in MEDLINE definitions. The abstracts of previous versions of this systematic review were published in 2002 and 2007.ConclusionRecruitment strategies that focus on increasing potential participants' awareness of the health problem being studied, its potential impact on their health, and their engagement in the learning process appeared to increase recruitment to clinical studies. Further trials of recruitment strategies that target engaging participants to increase their awareness of the health problems being studied and the potential impact on their health may confirm this hypothesis. Please see later in the article for the Editors' Summary.
| S-EPMC2976724 | biostudies-literature
Project description:To provide an overview and a critical appraisal of the use of responder analyses in published randomised controlled trials (RCTs) of interventions for chronic low back pain (LBP). The methodology used for the analyses, including the justification, as well as the implications of responder analyses on the conclusions was explored.A convenience sample of four systematic reviews evaluating 162 RCTs of interventions for chronic LBP was used to identify individual trials. Randomised trials were screened by two reviewers and included if they performed and reported a responder analysis (i.e. the proportion of participants achieving a pre-defined level of improvement). The cutoff value for responders, the period of follow-up, and the outcome measure used were extracted. Information on how RCT authors justified the methodology of their responder analyses was also appraised.Twenty-eight articles (17%) using 20 different definitions of responders were included in this appraisal. Justification for the definition of responders was absent in 80% of the articles. Pain was the most frequently used domain for the definition of response (50%), followed by back-specific function (30%) and a combination of pain and function (20%). A reduction in pain intensity ?50% was the most common threshold used to define responders (IQR 33-60%).Few RCTs of interventions for chronic LBP report responder analyses. Where responder analyses are used, the methods are inconsistent. When performing responder analyses authors are encouraged to follow the recommended guidelines, using empirically derived cutoffs, and present results alongside mean differences.
| S-EPMC3960418 | biostudies-other
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.
| S-EPMC6313893 | biostudies-other
Project description:Premature discontinuation and other forms of noncompliance with treatment assignment can complicate causal inference of treatment effects in randomized trials. The intent-to-treat analysis gives unbiased estimates for causal effects of treatment assignment on outcome, but may understate potential benefit or harm of actual treatment. The corresponding upper confidence limit can also be underestimated.To compare estimates of the hazard ratio and upper bound of the two-sided 95% confidence interval from causal inference methods that account for noncompliance with those from the intent-to-treat analysis.We used simulations with parameters chosen to reflect cardiovascular safety trials of diabetes drugs, with a focus on upper bound estimates relative to 1.3, based on regulatory guidelines. A total of 1000 simulations were run under each parameter combination for a hypothetical trial of 10,000 total subjects randomly assigned to active treatment or control at 1:1 ratio. Noncompliance was considered in the form of treatment discontinuation and cross-over at specified proportions, with an assumed true hazard ratio of 0.9, 1, and 1.3, respectively. Various levels of risk associated with being a non-complier (independent of treatment status) were evaluated. Hazard ratio and upper bound estimates from causal survival analysis and intent-to-treat were obtained from each simulation and summarized under each parameter setting.Causal analysis estimated the true hazard ratio with little bias in almost all settings examined. Intent-to-treat was unbiased only when the true hazard ratio?=?1; otherwise it underestimated both benefit and harm. When upper bound estimates from intent-to-treat were ?1.3, corresponding estimates from causal analysis were also ?1.3 in almost 100% of the simulations, regardless of the true hazard ratio. When upper bound estimates from intent-to-treat were <1.3 and the true hazard ratio?=?1, corresponding upper bound estimates from causal analysis were ?1.3 in up to 66% of the simulations under some settings.Simulations cannot cover all scenarios for noncompliance in real randomized trials.Causal survival analysis was superior to intent-to-treat in estimating the true hazard ratio with respect to bias in the presence of noncompliance. However, its large variance should be considered for safety upper bound exclusion especially when the true hazard ratio?=?1. Our simulations provided a broad reference for practical considerations of bias-variance trade-off in dealing with noncompliance in cardiovascular safety trials of diabetes drugs. Further research is warranted for the development and application of causal inference methods in the evaluation of safety upper bounds.
| S-EPMC4420771 | biostudies-literature