Clinical trials : journal of the Society for Clinical Trials
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Subgroup analyses are frequently used to assess heterogeneity of treatment effects in randomised clinical trials. Inconsistent, improper and incomplete implementation, reporting and interpretation have been identified as ongoing challenges. Further, subgroup analyses were frequently criticised because of unreliable or potentially misleading results. More recently, recommendations and guidelines have been provided to improve the reporting of data in this regard. ⋯ Compared to previous reviews in this context, we observed improvements in the reporting of subgroup analyses of cardiovascular randomised clinical trials. Nonetheless, critical shortcomings, such as inconsistent reporting of the implementation and insufficient pre-specification, persist.
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Endpoint choice for randomized controlled trials of treatments for novel coronavirus-induced disease (COVID-19) is complex. Trials must start rapidly to identify treatments that can be used as part of the outbreak response, in the midst of considerable uncertainty and limited information. COVID-19 presentation is heterogeneous, ranging from mild disease that improves within days to critical disease that can last weeks to over a month and can end in death. While improvement in mortality would provide unquestionable evidence about the clinical significance of a treatment, sample sizes for a study evaluating mortality are large and may be impractical, particularly given a multitude of putative therapies to evaluate. Furthermore, patient states in between "cure" and "death" represent meaningful distinctions. Clinical severity scores have been proposed as an alternative. However, the appropriate summary measure for severity scores has been the subject of debate, particularly given the variable time course of COVID-19. Outcomes measured at fixed time points, such as a comparison of severity scores between treatment and control at day 14, may risk missing the time of clinical benefit. An endpoint such as time to improvement (or recovery) avoids the timing problem. However, some have argued that power losses will result from reducing the ordinal scale to a binary state of "recovered" versus "not recovered." ⋯ Time-to-event analysis methods have advantages in the COVID-19 setting, unless the optimal time for evaluating treatment effect is known in advance. Even when the optimal time is known, a time-to-event approach may increase power for interim analyses.
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Novel rationales for randomizing clusters rather than individuals appear to be emerging from the push for more pragmatic trials, for example, to facilitate trial recruitment, reduce the costs of research, and improve external validity. Such rationales may be driven by a mistaken perception that choosing cluster randomization lessens the need for informed consent. We reviewed a random sample of published cluster randomized trials involving only individual-level health care interventions to determine (a) the prevalence of reporting a rationale for the choice of cluster randomization; (b) the types of explicit, or if absent, apparent rationales for the use of cluster randomization; (c) the prevalence of reporting patient informed consent for study interventions; and (d) the types of justifications provided for waivers of consent. We considered cluster randomized trials for evaluating exclusively the individual-level health care interventions to focus on clinical trials where individual randomization is only theoretically possible and where there is a general expectation of informed consent. ⋯ Rationales for adopting cluster over individual randomization and for adopting consent waivers are emerging, related to the need to facilitate pragmatic trials. Greater attention to clear reporting of study design rationales, informed consent procedures, as well as justification for waivers is needed to ensure that such trials meet appropriate ethical standards.
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Background Most deaths following severe traumatic brain injury follow decisions to withdraw life-sustaining therapies. However, the incidence of the withdrawal of life-sustaining therapies and its potential impact on research data interpretation have been poorly characterized. The aim of this systematic review was to assess the reporting and the impact of withdrawal of life-sustaining therapies in randomized clinical trials of patients with severe traumatic brain injury. ⋯ An analysis carried out by imputing a 4% differential rate in instances of withdrawal of life-sustaining therapies between study groups yielded different results and conclusions in one third of the trials. Conclusion Data on the withdrawal of life-sustaining therapies are incompletely reported in randomized controlled trials of patients with severe traumatic brain injury. Given the high proportion of deaths due to the withdrawal of life-sustaining therapies in severe traumatic brain injury patients, and the potential of this medical decision to influence the results of clinical trials, instances of withdrawal of life-sustaining therapies should be systematically reported in clinical trials in this group of patients.
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Accurate information on harms arising from medical interventions is essential for assessing benefit-risk ratios. Since 2004, there has been an extension of the Consolidated Standards of Reporting Trials statement for reporting harms data in publications on randomized clinical trials. The objective of our study was to assess the quality of this reporting from academic randomized clinical trials on drugs. ⋯ Reporting of harms in French academic drug randomized clinical trials is suboptimal; moreover, this shortcoming is a critical barrier to evaluating the benefit-risk ratio of drug randomized clinical trials. Thus, the authors should be encouraged to adhere to the Consolidated Standards of Reporting Trials Harms extension.