Clinical trials : journal of the Society for Clinical Trials
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Comparative Study
A comprehensive comparison of the continual reassessment method to the standard 3 + 3 dose escalation scheme in Phase I dose-finding studies.
An extensive literature has covered the statistical properties of the Continual Reassessment Method (CRM) and the modifications of this method. While there are some applications of CRM designs in recent Phase I trials, the standard method (SM) of escalating doses after three patients with an option for an additional three patients SM remains very popular, mainly due to its simplicity. From a practical perspective, clinicians are interested in designs that can estimate the MTD using fewer patients for a fixed number of doses, or can test more dose levels for a given sample size. ⋯ We show that CRM-based methods are an improvement over the SM in terms of accuracy and optimal dose allocation in almost all cases, except when the true dose is among the lower levels.
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In non-cancer phase II trials, dose-finding trials are usually carried out using fixed designs, in which several doses including a placebo are randomly distributed to patients. However, in certain vulnerable populations, such as neonates or infants, there is an heightened requirement for safety, precluding randomization. ⋯ In phase II dose-finding studies in which failure targets are below 20%, the CRM appears quite sensitive to first unexpected outcomes. Using a power model for dose-response improves some behavior if the trial is started at the first dose level and includes at least three to five patients at the starting dose before applying the CRM allocation rule.
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Treatment group imbalances in baseline stroke severity in the NINDS intravenous t-PA for acute stroke treatment trial led to controversy regarding the efficacy of tissue plasminogen activator (t-PA) in the treatment of acute ischemic stroke. ⋯ With new NIH requirements for data-sharing, the frequency of re-analysis of clinical trial data may increase substantially. This re-evaluation provides a blueprint for future re-evaluations of other trials. These best practices include re-analysis of the study data, after suitable replication, by an independent multidisciplinary committee, including a skilled statistical programmer analyst. Primary investigators should address significant errors determined in such re-analyses.
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In analysing clinical trials designed to show superiority of one treatment compared to another, it is standard to use an intention to treat analytic approach. In active-controlled noninferiority studies, this is not standard, due to concerns that such an analysis will inflate the chance of falsely rejecting the null hypothesis, accepting therapeutic noninferiority when it is not justified. ⋯ In this commentary, we argue that these same justifications carry over to noninferiority studies, and that for those and other reasons it should be the preferred analytic approach. We review regulatory guidelines, and propose a number of approaches to minimizing the potential disadvantages of the ITT approach in the noninferiority setting.
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Intention-to-treat (ITT) is an approach to the analysis of randomized controlled trials (RCT) in which patients are analyzed as randomized regardless of the treatment actually received. ⋯ This study emphasizes that authors use the label ;intention-to-treat' quite differently. The most common use refers to the analysis of all available subjects as randomized regardless of the missing data aspect.