Clinical trials : journal of the Society for Clinical Trials
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All studies classified as research involving human participants require research ethics review. Most regulation and guidance on ethical oversight of research involving human participants was written for pharmacotherapy interventions. Interpretation of such guidance for cluster-randomized trials and stepped-wedge trials, which commonly evaluate complex non-therapeutic interventions such as knowledge translation, public health, or health service delivery interventions, can pose challenges to researchers and regulators. ⋯ Through an ethical analysis of two case studies, we argue that stepped-wedge trials, like parallel arm cluster trials, are systematic investigations designed to produce generalizable knowledge. We contend that stepped-wedge trials usually include human research participants, which may be patients, health care providers, or both. Stepped-wedge trials are therefore research involving human participants for the purpose of ethical review. Nevertheless, the use of a waiver or alteration of consent may be appropriate in many stepped-wedge trials due to the infeasibility of obtaining informed consent and the low-risk nature of the interventions. To ensure that traditional ethical principles such as respect for persons are upheld, these studies must undergo research ethics review.
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Observational Study
Administrative claims data to support pragmatic clinical trial outcome ascertainment on cardiovascular health.
Health plan administrative claims data present a cost-effective complement to traditional trial-specific ascertainment of clinical events typically conducted through patient report or a single health system electronic health record. We aim to demonstrate the value of health plan claims data in improving the capture of endpoints in longitudinal pragmatic clinical trials. ⋯ This study demonstrated the value of supplementing longitudinal site-based clinical studies with administrative claims data. Our results suggest that claims data together with network partner electronic health record data constitute an effective vehicle to capture patient outcomes since >30% of patients have non-fatal and fatal events outside of enrolling sites.
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Randomized Controlled Trial
Caregiver-guided pain coping skills training for patients with advanced cancer: Background, design, and challenges for the CaringPals study.
Pain is a major concern of patients with advanced cancer and their caregivers. There is strong evidence that pain coping skills training interventions based on cognitive-behavioral principles can reduce pain severity and pain interference. However, few such interventions have been tested for patients with advanced cancer and their family caregivers. This study aims to test the efficacy of a caregiver-guided pain coping skills training protocol on patient and caregiver outcomes. ⋯ The CaringPals trial addresses a gap in research in pain coping skills training interventions by addressing the unique needs of patients with advanced cancer and their caregivers. Findings from this study may lead to advances in the clinical care of patients with advanced cancer and pain, as well as a better understanding of the effects of training family caregivers to help patients cope with pain.
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Randomisation in small clinical trials is a delicate matter, due to the tension between the conflicting aims of balanced groups and unpredictable allocations. The commonly used method of permuted block randomisation has been heavily criticised for its high predictability. This article introduces merged block randomisation, a novel and conceptually simple restricted randomisation design for small clinical trials (less than 100 patients per stratum). Merged block randomisation is a simple procedure that can be carried out without need for a computer. Merged block randomisation is not restricted to 1:1 randomisation, but is readily applied to unequal target allocations and to more than two treatment groups. ⋯ Merged block randomisation is a versatile restricted randomisation method that outperforms permuted block randomisation and is a good choice for small clinical trials where imbalance is a main concern, especially in multicentre trials where the number of patients per centre may be small.
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In the era of targeted therapies, clinical trials in oncology are rapidly evolving, wherein patients from multiple diseases are now enrolled and treated according to their genomic mutation(s). In such trials, known as basket trials, the different disease cohorts form the different baskets for inference. Several approaches have been proposed in the literature to efficiently use information from all baskets while simultaneously screening to find individual baskets where the drug works. Most proposed methods are developed in a Bayesian paradigm that requires specifying a prior distribution for a variance parameter, which controls the degree to which information is shared across baskets. ⋯ Based on the simulation results, we recommend that those involved in designing basket trials that implement hierarchical modeling avoid using a prior distribution that places a majority of the density mass near zero for the variance parameter. Priors with this property force the model to share information regardless of the true efficacy configuration of the baskets. Many commonly used inverse-gamma prior specifications have this undesirable property. We recommend to instead consider the more robust uniform prior or half-t prior on the standard deviation.