Single Arm Phase Ii Survival Trial Design
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| Author | : Jianrong Wu |
| Publisher | : CRC Press |
| Total Pages | : 273 |
| Release | : 2021-07-19 |
| Genre | : Mathematics |
| ISBN | : 1000421732 |
Single-Arm Phase II Survival Trial Design provides a comprehensive summary to the most commonly- used methods for single-arm phase II trial design with time-to-event endpoints. Single-arm phase II trials are a key component for successfully developing advanced cancer drugs and treatments, particular for target therapy and immunotherapy in which time-to-event endpoints are often the primary endpoints. Most test statistics for single-arm phase II trial design with time-to-event endpoints are not available in commercial software. Key Features: Covers the most frequently used methods for single-arm phase II trial design with time-to-event endpoints in a comprehensive fashion. Provides new material on phase II immunotherapy trial design and phase II trial design with TTP ratio endpoint. Illustrates trial designs by real clinical trial examples Includes R code for all methods proposed in the book, enabling straightforward sample size calculation.
| Author | : Jianrong Wu |
| Publisher | : CRC Press |
| Total Pages | : 225 |
| Release | : 2021-08-06 |
| Genre | : Mathematics |
| ISBN | : 1000422488 |
Single-Arm Phase II Survival Trial Design provides a comprehensive summary to the most commonly- used methods for single-arm phase II trial design with time-to-event endpoints. Single-arm phase II trials are a key component for successfully developing advanced cancer drugs and treatments, particular for target therapy and immunotherapy in which time-to-event endpoints are often the primary endpoints. Most test statistics for single-arm phase II trial design with time-to-event endpoints are not available in commercial software. Key Features: Covers the most frequently used methods for single-arm phase II trial design with time-to-event endpoints in a comprehensive fashion. Provides new material on phase II immunotherapy trial design and phase II trial design with TTP ratio endpoint. Illustrates trial designs by real clinical trial examples Includes R code for all methods proposed in the book, enabling straightforward sample size calculation.
| Author | : Sin-Ho Jung |
| Publisher | : CRC Press |
| Total Pages | : 250 |
| Release | : 2013-05-02 |
| Genre | : Mathematics |
| ISBN | : 143987185X |
In cancer research, a traditional phase II trial is designed as a single-arm trial that compares the experimental therapy to a historical control. This simple trial design has led to several adverse issues, including increased false positivity of phase II trial results and negative phase III trials. To rectify these problems, oncologists and biostatisticians have begun to use a randomized phase II trial that compares an experimental therapy with a prospective control therapy. Randomized Phase II Cancer Clinical Trials explains how to properly select and accurately use diverse statistical methods for designing and analyzing phase II trials. The author first reviews the statistical methods for single-arm phase II trials since some methodologies for randomized phase II trials stem from single-arm phase II trials and many phase II cancer clinical trials still use single-arm designs. The book then presents methods for randomized phase II trials and describes statistical methods for both single-arm and randomized phase II trials. Although the text focuses on phase II cancer clinical trials, the statistical methods covered can also be used (with minor modifications) in phase II trials for other diseases and in phase III cancer clinical trials. Suitable for cancer clinicians and biostatisticians, this book shows how randomized phase II trials with a prospective control resolve the shortcomings of traditional single-arm phase II trials. It provides readers with numerous statistical design and analysis methods for randomized phase II trials in oncology.
| Author | : Jianrong Wu |
| Publisher | : CRC Press |
| Total Pages | : 243 |
| Release | : 2018-06-14 |
| Genre | : Mathematics |
| ISBN | : 0429892934 |
Statistical Methods for Survival Trial Design: With Applications to Cancer Clinical Trials Using R provides a thorough presentation of the principles of designing and monitoring cancer clinical trials in which time-to-event is the primary endpoint. Traditional cancer trial designs with time-to-event endpoints are often limited to the exponential model or proportional hazards model. In practice, however, those model assumptions may not be satisfied for long-term survival trials. This book is the first to cover comprehensively the many newly developed methodologies for survival trial design, including trial design under the Weibull survival models; extensions of the sample size calculations under the proportional hazard models; and trial design under mixture cure models, complex survival models, Cox regression models, and competing-risk models. A general sequential procedure based on the sequential conditional probability ratio test is also implemented for survival trial monitoring. All methodologies are presented with sufficient detail for interested researchers or graduate students.
| Author | : Institute of Medicine |
| Publisher | : National Academies Press |
| Total Pages | : 221 |
| Release | : 2001-01-01 |
| Genre | : Medical |
| ISBN | : 0309171148 |
Clinical trials are used to elucidate the most appropriate preventive, diagnostic, or treatment options for individuals with a given medical condition. Perhaps the most essential feature of a clinical trial is that it aims to use results based on a limited sample of research participants to see if the intervention is safe and effective or if it is comparable to a comparison treatment. Sample size is a crucial component of any clinical trial. A trial with a small number of research participants is more prone to variability and carries a considerable risk of failing to demonstrate the effectiveness of a given intervention when one really is present. This may occur in phase I (safety and pharmacologic profiles), II (pilot efficacy evaluation), and III (extensive assessment of safety and efficacy) trials. Although phase I and II studies may have smaller sample sizes, they usually have adequate statistical power, which is the committee's definition of a "large" trial. Sometimes a trial with eight participants may have adequate statistical power, statistical power being the probability of rejecting the null hypothesis when the hypothesis is false. Small Clinical Trials assesses the current methodologies and the appropriate situations for the conduct of clinical trials with small sample sizes. This report assesses the published literature on various strategies such as (1) meta-analysis to combine disparate information from several studies including Bayesian techniques as in the confidence profile method and (2) other alternatives such as assessing therapeutic results in a single treated population (e.g., astronauts) by sequentially measuring whether the intervention is falling above or below a preestablished probability outcome range and meeting predesigned specifications as opposed to incremental improvement.
| Author | : Hui Gu |
| Publisher | : |
| Total Pages | : 110 |
| Release | : 2017 |
| Genre | : Clinical trials |
| ISBN | : |
The main purpose of a single-arm phase II cancer trial of a new regimen is to determine whether it has sufficient anti-tumor activity against a specific type of tumor to warrant its further clinical development. Such a research question can be answered under the frame- work of hypothesis testing. With the advent of targeted therapies that prolong disease stabilization, cancer patients typically experience stable disease (SD) rather than tumor shrinkage. It has been shown that patients with SD also achieve clinical benefits. There- fore, when evaluating the anti-tumor activity of a new treatment, clinicians are interested not only in overall response rate (complete or partial response(s)), but also in other types of measurements indicating clinical benefit. Taking two primary efficacy endpoints as an example, if the new treatment can improve on either endpoint(s), it may be promising for further evaluation. Therefore, "OR" logical relationship between the two primary efficacy endpoints is used when specifying the alternative hypothesis. In phase II cancer clinical trials, two-stage designs rather than single-stage ones are widely used for its possibility of early termination for futility to protect cancer patients. Motivated by two real cancer clinical trials, we propose a single-arm two-stage phase II cancer clinical trial design with two dichotomous alternative primary efficacy endpoints. Because of unknown correlation between two endpoints at the design stage, minimax rule is used to determine the optimal design, which minimizes the maximum of the expected sample size among all possible correlations, subject to the type I and II error constraints. Optimal designs for a variety of design parameters as well as the corresponding operating characteristics are provided. In addition, the statistical inferences of the design are studied. The MLE point estimators as well as confidence regions for the true event rates for the two efficacy endpoints are derived. Three types of confidence regions are obtained by inverting likelihood based test statistics: Wald, Score, and Likelihood ratio statistics. Among the three, the likelihood ratio-type confidence region performs the best in terms of good coverage probability and comparable expected area, and thus is recommended for this two-endpoint two-stage design.
| Author | : Christopher Jennison |
| Publisher | : CRC Press |
| Total Pages | : 416 |
| Release | : 1999-09-15 |
| Genre | : Mathematics |
| ISBN | : 9781584888581 |
Group sequential methods answer the needs of clinical trial monitoring committees who must assess the data available at an interim analysis. These interim results may provide grounds for terminating the study-effectively reducing costs-or may benefit the general patient population by allowing early dissemination of its findings. Group sequential methods provide a means to balance the ethical and financial advantages of stopping a study early against the risk of an incorrect conclusion. Group Sequential Methods with Applications to Clinical Trials describes group sequential stopping rules designed to reduce average study length and control Type I and II error probabilities. The authors present one-sided and two-sided tests, introduce several families of group sequential tests, and explain how to choose the most appropriate test and interim analysis schedule. Their topics include placebo-controlled randomized trials, bio-equivalence testing, crossover and longitudinal studies, and linear and generalized linear models. Research in group sequential analysis has progressed rapidly over the past 20 years. Group Sequential Methods with Applications to Clinical Trials surveys and extends current methods for planning and conducting interim analyses. It provides straightforward descriptions of group sequential hypothesis tests in a form suited for direct application to a wide variety of clinical trials. Medical statisticians engaged in any investigations planned with interim analyses will find this book a useful and important tool.
| Author | : Steven Piantadosi |
| Publisher | : Springer Nature |
| Total Pages | : 2573 |
| Release | : 2022-07-19 |
| Genre | : Medical |
| ISBN | : 3319526367 |
This is a comprehensive major reference work for our SpringerReference program covering clinical trials. Although the core of the Work will focus on the design, analysis, and interpretation of scientific data from clinical trials, a broad spectrum of clinical trial application areas will be covered in detail. This is an important time to develop such a Work, as drug safety and efficacy emphasizes the Clinical Trials process. Because of an immense and growing international disease burden, pharmaceutical and biotechnology companies continue to develop new drugs. Clinical trials have also become extremely globalized in the past 15 years, with over 225,000 international trials ongoing at this point in time. Principles in Practice of Clinical Trials is truly an interdisciplinary that will be divided into the following areas: 1) Clinical Trials Basic Perspectives 2) Regulation and Oversight 3) Basic Trial Designs 4) Advanced Trial Designs 5) Analysis 6) Trial Publication 7) Topics Related Specific Populations and Legal Aspects of Clinical Trials The Work is designed to be comprised of 175 chapters and approximately 2500 pages. The Work will be oriented like many of our SpringerReference Handbooks, presenting detailed and comprehensive expository chapters on broad subjects. The Editors are major figures in the field of clinical trials, and both have written textbooks on the topic. There will also be a slate of 7-8 renowned associate editors that will edit individual sections of the Reference.
| Author | : National Academies of Sciences, Engineering, and Medicine |
| Publisher | : National Academies Press |
| Total Pages | : 111 |
| Release | : 2016-11-07 |
| Genre | : Medical |
| ISBN | : 0309442583 |
On March 3-4, 2016, the National Academies of Sciences, Engineering, and Medicine's Forum on Neuroscience and Nervous System Disorders held a workshop in Washington, DC, bringing together key stakeholders to discuss opportunities for improving the integrity, efficiency, and validity of clinical trials for nervous system disorders. Participants in the workshop represented a range of diverse perspectives, including individuals not normally associated with traditional clinical trials. The purpose of this workshop was to generate discussion about not only what is feasible now, but what may be possible with the implementation of cutting-edge technologies in the future.
| Author | : Guogen Shan |
| Publisher | : Academic Press |
| Total Pages | : 68 |
| Release | : 2016-01-22 |
| Genre | : Mathematics |
| ISBN | : 0128039485 |
Exact Statistical Inference for Categorical Data discusses the way asymptotic approaches have been often used in practice to make statistical inference. This book introduces both conditional and unconditional exact approaches for the data in 2 by 2, or 2 by k contingency tables, and is an ideal reference for users who are interested in having the convenience of applying asymptotic approaches, with less computational time. In addition to the existing conditional exact inference, some efficient, unconditional exact approaches could be used in data analysis to improve the performance of the testing procedure. Demonstrates how exact inference can be used to analyze data in 2 by 2 tables Discusses the analysis of data in 2 by k tables using exact inference Explains how exact inference can be used in genetics
