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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The Women's Health Initiative (WHI) randomized trial of estrogen plus progestin (E + P) was terminated early based on an assessment of harms exceeding benefits for disease prevention. The results contravened prevailing wisdom and a large body of literature regarding benefits of menopausal hormone therapy. The results and their interpretation have been the subject of considerable debate. ⋯ Developing a formal trial monitoring plan with a view towards influencing clinical practice is useful for creating consensus among DSMB members regarding the evidence that would justify stopping a trial and the framework to be used to address statistical complexities. Departures from design assumptions typically occur. These reinforce the role of the DSMB in exercising their judgment, and the judicious adaptation of these statistical guidelines in monitoring and reporting trials. In communicating the results in such circumstances, priority should be given to presenting as fair, accurate and transparent a view of the data and findings as current methods and technology allow.
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The analysis of clinical trials with dropout usually assumes the missing data are ;missing at random', i.e. given an individual's past observed data, their probability of dropout does not depend on their present outcome. However, in many settings this assumption is implausible, so it is sensible to assess the robustness of conclusions to departures from missing at random. ⋯ Our proposed approach allows for the greater uncertainty introduced by missing data that are potentially informatively missing. It can therefore claim to be a truly conservative method, unlike methods such as ;last observation carried forward'. It is practical and accessible to non-statisticians. It should be considered as part of the design and analysis of future clinical trials.