Stopping Randomized Trials Early for Benefit: A Protocol of the Study Of Trial Policy Of Interim Truncation-2 (STOPIT-2)

Trials (Impact Factor: 1.73). 07/2009; 10(1). DOI: 10.1186/1745-6215-10-49
Source: OAI

ABSTRACT Background: Randomized clinical trials (RCTs) stopped early for benefit often receive great attention and affect clinical practice, but pose interpretational challenges for clinicians, researchers, and policy makers. Because the decision to stop the trial may arise from catching the treatment effect at a random high, truncated RCTs (tRCTs) may overestimate the true treatment effect. The Study Of Trial Policy Of Interim Truncation (STOPIT-1), which systematically reviewed the epidemiology and reporting quality of tRCTs, found that such trials are becoming more common, but that reporting of stopping rules and decisions were often deficient. Most importantly, treatment effects were often implausibly large and inversely related to the number of the events accrued. The aim of STOPIT-2 is to determine the magnitude and determinants of possible bias introduced by stopping RCTs early for benefit. Methods/Design: We will use sensitive strategies to search for systematic reviews addressing the same clinical question as each of the tRCTs identified in STOPIT-1 and in a subsequent literature search. We will check all RCTs included in each systematic review to determine their similarity to the index tRCT in terms of participants, interventions, and outcome definition, and conduct new meta-analyses addressing the outcome that led to early termination of the tRCT. For each pair of tRCT and systematic review of corresponding non-tRCTs we will estimate the ratio of relative risks, and hence estimate the degree of bias. We will use hierarchical multivariable regression to determine the factors associated with the magnitude of this ratio. Factors explored will include the presence and quality of a stopping rule, the methodological quality of the trials, and the number of total events that had occurred at the time of truncation.Finally, we will evaluate whether Bayesian methods using conservative informative priors to "regress to the mean" overoptimistic tRCTs can correct observed biases. Discussion: A better understanding of the extent to which tRCTs exaggerate treatment effects and of the factors associated with the magnitude of this bias can optimize trial design and data monitoring charters, and may aid in the interpretation of the results from trials stopped early for benefit.

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Available from: German Malaga, Sep 29, 2015
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    • "Our study is designed to comprehensively address the analysis, reporting, and claim of subgroup effects in a representative sample of recent RCTs. This study protocol follows the publications of two other protocols [24,25] which reflects our continuing efforts to make objectives and design of methodological studies more transparent. "
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    ABSTRACT: Subgroup analyses in randomized trials examine whether effects of interventions differ between subgroups of study populations according to characteristics of patients or interventions. However, findings from subgroup analyses may be misleading, potentially resulting in suboptimal clinical and health decision making. Few studies have investigated the reporting and conduct of subgroup analyses and a number of important questions remain unanswered. The objectives of this study are: 1) to describe the reporting of subgroup analyses and claims of subgroup effects in randomized controlled trials, 2) to assess study characteristics associated with reporting of subgroup analyses and with claims of subgroup effects, and 3) to examine the analysis, and interpretation of subgroup effects for each study's primary outcome. We will conduct a systematic review of 464 randomized controlled human trials published in 2007 in the 118 Core Clinical Journals defined by the National Library of Medicine. We will randomly select journal articles, stratified in a 1:1 ratio by higher impact versus lower impact journals. According to 2007 ISI total citations, we consider the New England Journal of Medicine, JAMA, Lancet, Annals of Internal Medicine, and BMJ as higher impact journals. Teams of two reviewers will independently screen full texts of reports for eligibility, and abstract data, using standardized, pilot-tested extraction forms. We will conduct univariable and multivariable logistic regression analyses to examine the association of pre-specified study characteristics with reporting of subgroup analyses and with claims of subgroup effects for the primary and any other outcomes. A clear understanding of subgroup analyses, as currently conducted and reported in published randomized controlled trials, will reveal both strengths and weaknesses of this practice. Our findings will contribute to a set of recommendations to optimize the conduct and reporting of subgroup analyses, and claim and interpretation of subgroup effects in randomized trials.
    Trials 11/2009; 10(1):101. DOI:10.1186/1745-6215-10-101 · 1.73 Impact Factor
  • FMC - Formación Médica Continuada en Atención Primaria 09/2009; 16(7). DOI:10.1016/S1134-2072(09)71971-1
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    ABSTRACT: Concerns about the completeness and accuracy of reporting of randomized clinical trials (RCTs) and the impact of poor reporting on decision-making have been documented in the medical field over the past several decades. Experience from RCTs in human medicine would suggest that failure to report critical trial features can be associated with biased estimated effect measures, and there is evidence to suggest similar biases occur in RCTs conducted in livestock populations. In response to these concerns, standardized guidelines for reporting RCTs were developed and implemented in human medicine. The Consolidated Standards of Reporting Trials (CONSORT) statement was first published in 1996 with a revised edition published in 2001. The CONSORT statement consists of a 22-item checklist for reporting a RCT and a flow diagram to follow the number of participants at each stage of a trial. An explanation and elaboration document not only defines and discusses the importance of each of the items, but also provides examples of how this information could be supplied in a publication. Differences between human and livestock populations necessitate modifications to the CONSORT statement to maximize its usefulness for RCTs involving livestock. These have been addressed in an extension of the CONSORT statement titled the REFLECT statement: Methods and processes of creating reporting guidelines for randomized control trials for livestock and food safety. The modifications made for livestock trials specifically addressed the common use of group housing and group allocation to intervention in livestock studies, the use of a deliberate challenge model in some trials, and common use of non-clinical outcomes, such as contamination with a foodborne pathogen. In addition, the REFLECT statement for RCTs in livestock populations proposed specific terms or further clarified terms as they pertained to livestock studies.
    Journal of food protection 03/2010; 73(3):579-603. DOI:10.1111/j.1863-2378.2009.01312.x · 1.85 Impact Factor
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