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An investigation of the impact of futility analysis in publicly funded trials.

ABSTRACT: Publicly funded trials regularly fail to recruit their target sample size or find a significant positive result. Adaptive clinical trials which may partly mediate against the problems are not often applied. In this paper we investigate the potential of a form of adaption in a clinical trial - a futility analysis - to see if it has potential to improve publicly funded trials.Outcome data from trials funded by two UK bodies, the Health Technology Assessment (HTA) programme and the UK Medical Research Council (MRC), were collected. These data were then used to simulate each trial with a single futility analysis using conditional power, undertaken after 50% to 90% of the patients had been recruited. Thirty-three trials recruiting between 2002 and 2008 met the inclusion criteria. Stopping boundaries of conditional powers of 20%, 30% and 40% were considered and outcomes included the number of trials successfully stopped and number of patients saved.Inclusion of a futility analysis after 75% of the patients had been recruited would have potentially resulted in 10 trials, which went on to have negative results, correctly stopping for futility using a stopping boundary of 30%. A total of 807 patients across all the trials would potentially have been saved using these futility parameters. The proportion of studies successfully recruiting would also have increased from 45% to 64%.A futility assessment has the potential to increase efficiency, save patients and decrease costs in publicly funded trials. While there are logistical issues in undertaking futility assessments we recommend that investigators should aim to include a futility analysis in their trial design wherever possible.

SUBMITTER: Sully BG

PROVIDER: S-EPMC3945066 | biostudies-other | 2014 Feb

REPOSITORIES: biostudies-other

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An investigation of the impact of futility analysis in publicly funded trials.

Sully Benjamin G O BG Julious Steven A SA Nicholl Jon J

Trials 20140217

<h4>Background</h4>Publicly funded trials regularly fail to recruit their target sample size or find a significant positive result. Adaptive clinical trials which may partly mediate against the problems are not often applied. In this paper we investigate the potential of a form of adaption in a clinical trial - a futility analysis - to see if it has potential to improve publicly funded trials.<h4>Methods</h4>Outcome data from trials funded by two UK bodies, the Health Technology Assessment (HTA) ...[more]

PMID: 24533447

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Project description:BACKGROUND/AIMS:Randomized clinical trials are widely recognized as essential to address worldwide clinical and public health research questions. However, their size and duration can overwhelm available public and private resources. To remain competitive in international research settings, advocates and practitioners of clinical trials must implement practices that reduce their cost. We identify approaches and practices for large, publicly funded, international trials that reduce cost without compromising data integrity and recommend an approach to cost reporting that permits comparison of clinical trials. METHODS:We describe the organizational and financial characteristics of The International Network for Strategic Initiatives in Global HIV Trials, an infectious disease research network that conducts multiple, large, long-term, international trials, and examine challenges associated with simple and streamlined governance and an infrastructure and financial management model that is based on performance, transparency, and accountability. RESULTS:It is possible to reduce costs of participants' follow-up and not compromise clinical trial quality or integrity. The International Network for Strategic Initiatives in Global HIV Trials network has successfully completed three large HIV trials using cost-efficient practices that have not adversely affected investigator enthusiasm, accrual rates, loss-to-follow-up, adherence to the protocol, and completion of data collection. This experience is relevant to the conduct of large, publicly funded trials in other disease areas, particularly trials dependent on international collaborations. CONCLUSION:New approaches, or creative adaption of traditional clinical trial infrastructure and financial management tools, can render large, international clinical trials more cost-efficient by emphasizing structural simplicity, minimal up-front costs, payments for performance, and uniform algorithms and fees-for-service, irrespective of location. However, challenges remain. They include institutional resistance to financial change, growing trial complexity, and the difficulty of sustaining network infrastructure absent stable research work. There is also a need for more central monitoring, improved and harmonized regulations, and a widely applied metric for measuring and comparing cost efficiency in clinical trials. ClinicalTrials.gov is recommended as a location where standardized trial cost information could be made publicly accessible.

Project description:ImportanceFor findings from clinical trials to be actionable, outcomes measured in trials must be fully defined and, when appropriate, defined consistently across trials. Otherwise, it is difficult to compare findings between trials, combine results in meta-analyses, or leverage findings collectively to inform health care decision-making.ObjectiveTo identify and characterize outcomes specified in ClinicalTrials.gov records for publicly funded clinical trials for 3 high-burden, high-prevalence eye conditions.Design, setting, and participantsClinicalTrials.gov, a registry of publicly and privately supported clinical studies, was searched on January 31, 2019, for records of clinical trials for age-related macular degeneration (AMD), dry eye, or refractive error. The search was limited to trials funded by the National Eye Institute but did not impose a date restriction. Five elements of a well-specified outcome were extracted from each outcome stated in each record, including the domain, method of measurement, metric, method of aggregation, and time points.Main outcomes and measuresNumber of outcome domains specified for trials for AMD, dry eye, and refractive error and the number of trial records specifying each unique domain.ResultsA total of 49 unique outcome domains specified across 39 records of trials were identified. The median (interquartile range) number of records specifying each unique outcome domain was 1 (1-3), 1.5 (1-2), and 1 (1-1) for AMD, dry eye, and refractive error, respectively. Even when the same domains were registered across multiple trials, the time point, specific metric, and method of aggregation were specified in multiple ways.Conclusions and relevanceThere were too many outcomes with too little overlap in the sample of trials that were examined. Differences in how outcomes are measured across trials make it difficult to compare results, even for well-established domains, such as visual acuity. To reduce this waste in eye and vision research, the time is ripe for agreeing on what outcomes to measure.

Project description:BackgroundIn cluster randomised controlled trials (cRCTs), groups of individuals (rather than individuals) are randomised to minimise the risk of contamination and/or efficiently use limited resources or solve logistic and administrative problems. A major concern in the primary analysis of cRCT is the use of appropriate statistical methods to account for correlation among outcomes from a particular group/cluster. This review aimed to investigate the statistical methods used in practice for analysing the primary outcomes in publicly funded cluster randomised controlled trials, adherence to the CONSORT (Consolidated Standards of Reporting Trials) reporting guidelines for cRCTs and the recruitment abilities of the cluster trials design.MethodsWe manually searched the United Kingdom's National Institute for Health Research (NIHR) online Journals Library, from 1 January 1997 to 15 July 2021 chronologically for reports of cRCTs. Information on the statistical methods used in the primary analyses was extracted. One reviewer conducted the search and extraction while the two other independent reviewers supervised and validated 25% of the total trials reviewed.ResultsA total of 1942 reports, published online in the NIHR Journals Library were screened for eligibility, 118 reports of cRCTs met the initial inclusion criteria, of these 79 reports containing the results of 86 trials with 100 primary outcomes analysed were finally included. Two primary outcomes were analysed at the cluster-level using a generalized linear model. At the individual-level, the generalized linear mixed model was the most used statistical method (80%, 80/100), followed by regression with robust standard errors (7%) then generalized estimating equations (6%). Ninety-five percent (95/100) of the primary outcomes in the trials were analysed with appropriate statistical methods that accounted for clustering while 5% were not. The mean observed intracluster correlation coefficient (ICC) was 0.06 (SD, 0.12; range, - 0.02 to 0.63), and the median value was 0.02 (IQR, 0.001-0.060), although 42% of the observed ICCs for the analysed primary outcomes were not reported.ConclusionsIn practice, most of the publicly funded cluster trials adjusted for clustering using appropriate statistical method(s), with most of the primary analyses done at the individual level using generalized linear mixed models. However, the inadequate analysis and poor reporting of cluster trials published in the UK is still happening in recent times, despite the availability of the CONSORT reporting guidelines for cluster trials published over a decade ago.

Project description:BackgroundOpinions and practices vary around the issue of performing multiple statistical tests in randomised controlled trials (RCTs). We carried out a study to collate information about opinions and practices using a methodological rapid review and a survey, specifically of publicly funded pragmatic RCTs that are not seeking marketing authorisation. The aim was to identify the circumstances under which researchers would make a statistical adjustment for multiplicity.MethodsA review was performed extracting information from articles reporting primary analyses of pragmatic RCTs in one of seven high quality medical journals, in January to June (inclusive) 2018. A survey (Survey Monkey) eliciting opinions and practices around multiplicity was distributed to the 47 registered clinical trials units (CTUs) in the UK.ResultsOne hundred and thirty-eight RCTs were included in the review, and survey responses were received from 27/47 (57%) CTUs. Both the review and survey indicated that adjusting for multiplicity was considered most important for multiple treatment comparisons; adjustment was performed for 11/23 (48%) published trials, and 24/27 (89%) CTU statisticians reported they would consider adjustment. Opinions and practices varied around adjustment for multiplicity arising from multiple primary outcomes and interim analyses. Adjustment was considered less important for multiplicity due to multiple secondary outcomes (adjustment performed for 17/136 [13%] published trials and 3/27 [11%] CTU statisticians would consider adjustment) and subgroup analyses (8/85 [9%] published trials adjusted and 6/27 CTU [22%] statisticians would consider adjustment).ConclusionsThere is variation in opinions about adjustment for multiplicity among both statisticians reporting RCTs and applied statisticians working in CTUs. Further guidance is needed on the circumstances in which adjustment should be considered in relation to primary trial hypotheses, and if there are any situations in which adjustment would be recommended in the context of secondary analyses.

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An investigation of the impact of futility analysis in publicly funded trials.

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An investigation of the impact of futility analysis in publicly funded trials.

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