Author: Hui Gu Publisher: ISBN: Category : Clinical trials Languages : en Pages : 110
Book Description
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: Sarah R. Brown Publisher: John Wiley & Sons ISBN: 1118763637 Category : Medical Languages : en Pages : 260
Book Description
How to identify optimal phase II trial designs Providing a practical guide containing the information needed to make crucial decisions regarding phase II trial designs, A Practical Guide to Designing Phase II Trials in Oncology sets forth specific points for consideration between the statistician and clinician when designing a phase II trial, including issues such as how the treatment works, choice of outcome measure and randomization, and considering both academic and industry perspectives. A comprehensive and systematic library of available phase II trial designs is included, saving time otherwise spent considering multiple manuscripts, and real-life practical examples of using this approach to design phase II trials in cancer are given. A Practical Guide to Designing Phase II Trials in Oncology: Offers a structured and practical approach to phase II trial design Considers trial design from both an academic and industry perspective Includes a structured library of available phase II trial designs Is relevant to both clinical and statistical researchers at all levels Includes real life examples of applying this approach For those new to trial design, A Practical Guide to Designing Phase II Trials in Oncology will be a unique and practical learning tool, providing an introduction to the concepts behind informed decision making in phase II trials. For more experienced practitioners, the book will offer an overview of new, less familiar approaches to phase II trial design, providing alternative options to those which they may have previously used.
Author: Herman E. Ray Publisher: ISBN: Category : Clinical trials Languages : en Pages : 200
Book Description
The phase II clinical trial is a critical step in the drug development process. In the oncology setting, phase II studies typically evaluate one primary endpoint, which is efficacy. In practice, a binary measurement representing the response to the new treatment defines the efficacy. The single-arm, multiple-stage designs are popular and the Simon 2-Stage design is preferred. Although the study designs evaluate the efficacy, the subject's safety is an important concern. Safety is monitored through the number of grade 3 or grade 4 toxic events. The phase II clinical trial design based on the primary endpoint is typically augmented with an ad hoc monitoring rule. The studies are designed in two steps. First, the sample size and critical values are determined based on the primary endpoint. Then an ad hoc toxicity monitoring rule is applied to the study. Previous authors recommended a method to monitor toxic events after each patient is enrolled which is also known as continuous toxicity monitoring. A trial designed at the JG Brown Cancer Center combined the Simon 2-Stage design with continuous toxicity monitoring. We describe how to integrate the continuous toxicity monitoring methodology with the Simon 2-Stage design for response. Theoretical justification is given for the nominal size, power, probability of early termination (PET), and average sample size (ASN) of the combined testing procedure. A series of simulations were conducted to investigate the performance of the combined procedure. We discover that the type I error rate, type II error rate, PET, and ASN are subject to the correlation between toxicity and response. In fact, the study may have a smaller type I error rate than expected. The theoretical expressions derived to describe the operating characteristics of the combined procedure were utilized to create a new flexible, bivariate, multistage clinical trial. The design is considered flexible because it can monitor toxicity on a different schedule than response. An example is considered in which toxicity is measured after four equally spaced intervals and the response is evaluated only at the second and fourth toxicity examinations. This example corresponds to a data monitoring committee's meeting schedule that may happen every 6 months over a two year span. The effect of the correlation on the type I and type II error rates is examined through simulation. The simulations also examine the power over the range of response rates with a fixed toxicity rate in the alternative region and vice-versa. There are several single-arm, multiple-stage clinical trial designs that consider multiple endpoints at the same time. A subset of the designs includes those that consider both efficacy and toxicity as binary endpoints. A common problem, considered after the conduct of the trial, is appropriate inference given the repeated examinations of the multiple endpoints. We propose a uniformly minimum variance unbiased estimator (UMVUE) for the response in a multistage clinical trial design incorporating toxicity effects. The proposed estimator and the typical maximum likelihood estimator (MLE) are evaluated through simulation. The estimator requires further modification when continuous toxicity monitoring is combined with a multistage design for response. The modified estimator maintains low bias over the range of possible response values. The larger phase lIb or phase III clinical trial is the logical extension of the bivariate research based on exact calculations. The phase lIb or III clinical trials typically include an ad hoc toxicity monitoring rule ensuring participant protection. The designs also include provisions to allow early stopping for futility or efficacy utilizing group sequential theory or stochastic curtailment. We also examine a novel large sample clinical trial design that incorporates correlation between the response and toxicity events. The design uses the typical critical values associated with the standard normal distribution. It also searches for critical values specific to the global hypothesis associated with both response and toxicity. The bivariate test is then combined with efficacy and safety monitoring based on a flexible time-varying conditional power methodology. The type I and type II error rates of the bivariate test procedure, along with the bivariate test procedure combined with the conditional power methodology, are investigated through simulation. A modification is developed for the conditional power methodology to preserve the type I and type II error rates. In the end, the research extends the bivariate clinical trial designs in an attempt to make them more appealing in practice. Although, the research resulted in positive outcomes, additional work is required.
Author: Sin-Ho Jung Publisher: CRC Press ISBN: 143987185X Category : Mathematics Languages : en Pages : 250
Book Description
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 ISBN: 1000421732 Category : Mathematics Languages : en Pages : 273
Book Description
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: Institute of Medicine Publisher: National Academies Press ISBN: 0309171148 Category : Medical Languages : en Pages : 221
Book Description
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: Susan Halabi Publisher: CRC Press ISBN: 1351620967 Category : Medical Languages : en Pages : 701
Book Description
There is an increasing need for educational resources for statisticians and investigators. Reflecting this, the goal of this book is to provide readers with a sound foundation in the statistical design, conduct, and analysis of clinical trials. Furthermore, it is intended as a guide for statisticians and investigators with minimal clinical trial experience who are interested in pursuing a career in this area. The advancement in genetic and molecular technologies have revolutionized drug development. In recent years, clinical trials have become increasingly sophisticated as they incorporate genomic studies, and efficient designs (such as basket and umbrella trials) have permeated the field. This book offers the requisite background and expert guidance for the innovative statistical design and analysis of clinical trials in oncology. Key Features: Cutting-edge topics with appropriate technical background Built around case studies which give the work a "hands-on" approach Real examples of flaws in previously reported clinical trials and how to avoid them Access to statistical code on the book’s website Chapters written by internationally recognized statisticians from academia and pharmaceutical companies Carefully edited to ensure consistency in style, level, and approach Topics covered include innovating phase I and II designs, trials in immune-oncology and rare diseases, among many others
Author: Shivaani Kummar Publisher: Academic Press ISBN: 0128125705 Category : Medical Languages : en Pages : 235
Book Description
Novel Designs of Early Phase Trials for Cancer Therapeutics provides a comprehensive review by leaders in the field of the process of drug development, the integration of molecular profiling, the changes in early phase trial designs, and endpoints to optimally develop a new generation of cancer therapeutics. The book discusses topics such as statistical perspectives on cohort expansions, the role and application of molecular profiling and how to integrate biomarkers in early phase trials. Additionally, it discusses how to incorporate patient reported outcomes in phase one trials. This book is a valuable resource for medical oncologists, basic and translational biomedical scientists, and trainees in oncology and pharmacology who are interested in learning how to improve their research by using early phase trials. Brings a comprehensive review and recommendations for new clinical trial designs for modern cancer therapeutics Provides the reader with a better understanding on how to design and implement early phase oncology trials Presents a better and updated understanding of the process of developing new treatments for cancer, the exciting scientific advances and how they are informing drug development
Author: Hui Gu
Author: Sarah R. Brown
Author: Herman E. Ray
Author: Sin-Ho Jung
Author: Jianrong Wu
Author: Institute of Medicine
Author: 
Author: 陳嘉民
Author: Susan Halabi
Author: Shivaani Kummar