Journal•ISSN: 1946-6315
Statistics in Biopharmaceutical Research
Taylor & Francis
About: Statistics in Biopharmaceutical Research is an academic journal published by Taylor & Francis. The journal publishes majorly in the area(s): Medicine & Computer science. It has an ISSN identifier of 1946-6315. Over the lifetime, 738 publications have been published receiving 5229 citations. The journal is also known as: Stat Biopharm Res & SBR.
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TL;DR: This work considers the general situation of testing multiple hypotheses repeatedly in time using recently developed graphical approaches and focuses on closed testing procedures using weighted group sequential Bonferroni tests for the intersection hypotheses.
Abstract: In 1997, Robert T. O’Neill introduced the framework of structuring the experimental questions to best reflect the clinical study’s objectives. This task comprises the identification of the study’s primary, secondary, and exploratory objectives and the requirements as to when the corresponding statistical tests are considered meaningful. A topic that has been considered much less in the literature until very recently is the application of group sequential trial designs to multiple endpoints. In 2007, Hung, Wang, and O’Neill showed that borrowing testing strategies naively from trial designs without interim analyses may not maintain the familywise Type I error rate at level α. The authors gave examples in the context of testing two hierarchically ordered endpoints in two-armed group sequential trials with one interim analysis. We consider the general situation of testing multiple hypotheses repeatedly in time using recently developed graphical approaches. We focus on closed testing procedures using weighted...
88 citations
TL;DR: A broad vision for the future of clinical trials consistent with increased pragmatism is described, with greater focus on using endpoints to analyze patients rather than patients to analyze endpoints particularly in late-phase/stage clinical trials.
Abstract: In the future, clinical trials will have an increased emphasis on pragmatism, providing a practical description of the effects of new treatments in realistic clinical settings. Accomplishing pragmatism requires better summaries of the totality of the evidence in ways that clinical trials consumers—patients, physicians, insurers—find transparent and allow for informed benefit:risk decision-making.The current approach to the analysis of clinical trials is to analyze efficacy and safety separately and then combine these analyses into a benefit:risk assessment. Many assume that this will effectively describe the impact on patients. But this approach is suboptimal for evaluating the totality of effects on patients.We discuss methods for benefit:risk assessment that have greater pragmatism than methods that separately analyze efficacy and safety. These include the concepts of within-patient analyses and composite benefit:risk endpoints with a goal of understanding how to analyze one patient before tryin...
81 citations
TL;DR: A two-stage Bliss independence response surface model is presented to estimate an overall interaction index (τ) with 95% confidence interval (CI) and the application of overall τ helps investigators to make decision easier and accelerate the preclinical drug screening.
Abstract: To test the anticancer effect of combining two drugs targeting different biological pathways, the popular way to show synergistic effect of drug combination is a heat map or surface plot based on t...
70 citations
TL;DR: Results of a comprehensive simulation study are presented that compares and contrasts five new adaptive dose-ranging designs for a variety of different scenarios.
Abstract: The main goals in an adaptive dose-ranging study are to detect dose response, to determine if any doses(s) meets clinical relevance, to estimate the dose-response, and then to decide on the dose(s) (if any) to take into the confirmatory Phase III. Adaptive dose-ranging study designs may result in power gains to detect dose response and higher precision in estimating the target dose and the dose response curve. In this article, we complement the library of available methods with five new adaptive dose-ranging designs. Due to their inherent complexity, the operating characteristics can be assessed only through intensive simulations. We present here results of a comprehensive simulation study that compares and contrasts these designs for a variety of different scenarios.
68 citations
TL;DR: The log-rank test is most powerful under proportional hazards (PH) as mentioned in this paper, however, non-PH patterns are often observed in clinical trials, such as in immuno-oncology; therefore, alternative methods ar...
Abstract: The log-rank test is most powerful under proportional hazards (PH). In practice, non-PH patterns are often observed in clinical trials, such as in immuno-oncology; therefore, alternative methods ar...
58 citations