[PDF] Methods For Planning And Evaluating Clinical Trials With Composite Endpoints eBook

Author : Geraldine Rauch
Publisher : Springer
Page : 254 pages
File Size : 22,28 MB
Release : 2018-05-22
Category : Medical
ISBN : 3319737708

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This book addresses the most important aspects of how to plan and evaluate clinical trials with a composite primary endpoint to guarantee a clinically meaningful and valid interpretation of the results. Composite endpoints are often used as primary efficacy variables for clinical trials, particularly in the fields of oncology and cardiology. These endpoints combine several variables of interest within a single composite measure, and as a result, all variables that are of major clinical relevance can be considered in the primary analysis without the need to adjust for multiplicity. Moreover, composite endpoints are intended to increase the size of the expected effects thus making clinical trials more powerful. The book offers practical advice for statisticians and medical experts involved in the planning and analysis of clinical trials. For readers who are mainly interested in the application of the methods, all the approaches are illustrated with real-world clinical trial examples, and the software codes required for fast and easy implementation are provided. The book also discusses all the methods in the context of relevant guidelines related to the topic. To benefit most from the book, readers should be familiar with the principles of clinical trials and basic statistical methods.

Author : Kees van Montfort
Publisher : Springer
Page : 364 pages
File Size : 11,96 MB
Release : 2014-10-07
Category : Mathematics
ISBN : 3642553451

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This book describes various ways of approaching and interpreting the data produced by clinical trial studies, with a special emphasis on the essential role that biostatistics plays in clinical trials. Over the past few decades the role of statistics in the evaluation and interpretation of clinical data has become of paramount importance. As a result the standards of clinical study design, conduct and interpretation have undergone substantial improvement. The book includes 18 carefully reviewed chapters on recent developments in clinical trials and their statistical evaluation, with each chapter providing one or more examples involving typical data sets, enabling readers to apply the proposed procedures. The chapters employ a uniform style to enhance comparability between the approaches.

Author : Institute of Medicine
Publisher : National Academies Press
Page : 236 pages
File Size : 44,98 MB
Release : 2015-04-20
Category : Medical
ISBN : 0309316324

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Data sharing can accelerate new discoveries by avoiding duplicative trials, stimulating new ideas for research, and enabling the maximal scientific knowledge and benefits to be gained from the efforts of clinical trial participants and investigators. At the same time, sharing clinical trial data presents risks, burdens, and challenges. These include the need to protect the privacy and honor the consent of clinical trial participants; safeguard the legitimate economic interests of sponsors; and guard against invalid secondary analyses, which could undermine trust in clinical trials or otherwise harm public health. Sharing Clinical Trial Data presents activities and strategies for the responsible sharing of clinical trial data. With the goal of increasing scientific knowledge to lead to better therapies for patients, this book identifies guiding principles and makes recommendations to maximize the benefits and minimize risks. This report offers guidance on the types of clinical trial data available at different points in the process, the points in the process at which each type of data should be shared, methods for sharing data, what groups should have access to data, and future knowledge and infrastructure needs. Responsible sharing of clinical trial data will allow other investigators to replicate published findings and carry out additional analyses, strengthen the evidence base for regulatory and clinical decisions, and increase the scientific knowledge gained from investments by the funders of clinical trials. The recommendations of Sharing Clinical Trial Data will be useful both now and well into the future as improved sharing of data leads to a stronger evidence base for treatment. This book will be of interest to stakeholders across the spectrum of research-from funders, to researchers, to journals, to physicians, and ultimately, to patients.

Author : Moisés Gómez-Mateu
Publisher :
Page : 168 pages
File Size : 37,22 MB
Release : 2016
Category :
ISBN :

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The conclusions from randomized clinical trials (RCT) rely on the primary endpoint (PE), which is chosen at the design stage of the study; thus, it is of utmost importance to select it appropriately. In RCT, there should generally be only one PE, and it should be able to provide the most clinically relevant and scientific evidence regarding the potential efficacy of the new treatment. Composite endpoints (CE) consist of the union of two or more outcomes and are often used in RCT. When the focus is time-to-event analysis, CE refer to the elapse time from randomization until the first component of the CE. In oncology trials, for instance, progression-free survival is defined as the time to disease progression or death. The decision on whether to use a CE versus a single component as the PE is controversial. The advantages and drawbacks regarding the use of CE have been extensively discussed in the literature. Gómez and Lagakos develop a statistical methodology to evaluate the convenience of using a relevant endpoint RE versus a CE consisting of the union of the RE plus another additional endpoint (AE). Their strategy is based on the value of the asymptotic relative efficiency (ARE), which relates the efficiency of using the logrank test based on the RE versus the efficiency based on the CE. The ARE is expressed as a function of the marginal laws of the time to each component RE and AE, the probabilities of observing each component in the control group, the hazard ratios measured by each component of the CE between the two treatment groups, and the correlation between components. This thesis explores, elaborates on, implements and applies the ARE method. We have also developed a new online platform named CompARE that facilitates the practical use of this method. The ARE method has been applied to cardiovascular studies. We have made further progress into the theoretical meaning of the ARE and have explored how to handle the probability and the hazard ratio of a combination of endpoints. In cardiovascular trials, it is common to use CE. We systematically examine the use of CE in this field by means of a literature search and the discussion of several case studies. Based on the ARE methodology, we provide guidelines for the informed choice of the PE. We prove that the usual interpretation of the ARE as the ratio of sample sizes holds and that it can be applied to evaluate the efficiency of the RE versus the CE. Furthermore, we carry out a simulation study to empirically check the proximity between the ratio of finite sample sizes and the ARE. We discuss how to derive the probabilities and hazard ratios when they come from a combination of several components. Furthermore, it is shown that the combined hazard ratio (HR*) is, in general, not constant over time, even if the hazard ratio of the marginal components are. This non-constant behaviour might have a strong influence on the interpretation of treatment effect and on sample size assessment. We evaluate the behaviour of the HR* in respect to the marginal parameters, and we study its departure from constancy, depending on different scenarios. This thesis has implemented the ARE methodology on the online platform CompARE. Clinicians and biostatisticians can use CompARE to study the performance of different endpoints in a variety of scenarios. CompARE has an intuitive interface and it is a convenient tool for better informed decisions regarding the PE. Results from different parameter settings are shown immediately by means of tables and plots. CompARE is extended to quantify specific values for the combined probability and hazard ratios. When the user cannot anticipate some of the needed parameters, CompARE provides a range of plausible values. Moreover, the departure from constancy of a combined hazard ratio can be explored by visualizing its shape over time. Sample size computations are implemented as well.

Author : Agency for Healthcare Research and Quality/AHRQ
Publisher : Government Printing Office
Page : 385 pages
File Size : 40,56 MB
Release : 2014-04-01
Category : Medical
ISBN : 1587634333

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This User’s Guide is intended to support the design, implementation, analysis, interpretation, and quality evaluation of registries created to increase understanding of patient outcomes. For the purposes of this guide, a patient registry is an organized system that uses observational study methods to collect uniform data (clinical and other) to evaluate specified outcomes for a population defined by a particular disease, condition, or exposure, and that serves one or more predetermined scientific, clinical, or policy purposes. A registry database is a file (or files) derived from the registry. Although registries can serve many purposes, this guide focuses on registries created for one or more of the following purposes: to describe the natural history of disease, to determine clinical effectiveness or cost-effectiveness of health care products and services, to measure or monitor safety and harm, and/or to measure quality of care. Registries are classified according to how their populations are defined. For example, product registries include patients who have been exposed to biopharmaceutical products or medical devices. Health services registries consist of patients who have had a common procedure, clinical encounter, or hospitalization. Disease or condition registries are defined by patients having the same diagnosis, such as cystic fibrosis or heart failure. The User’s Guide was created by researchers affiliated with AHRQ’s Effective Health Care Program, particularly those who participated in AHRQ’s DEcIDE (Developing Evidence to Inform Decisions About Effectiveness) program. Chapters were subject to multiple internal and external independent reviews.

Author : National Research Council
Publisher : National Academies Press
Page : 163 pages
File Size : 44,73 MB
Release : 2010-12-21
Category : Medical
ISBN : 030918651X

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Randomized clinical trials are the primary tool for evaluating new medical interventions. Randomization provides for a fair comparison between treatment and control groups, balancing out, on average, distributions of known and unknown factors among the participants. Unfortunately, these studies often lack a substantial percentage of data. This missing data reduces the benefit provided by the randomization and introduces potential biases in the comparison of the treatment groups. Missing data can arise for a variety of reasons, including the inability or unwillingness of participants to meet appointments for evaluation. And in some studies, some or all of data collection ceases when participants discontinue study treatment. Existing guidelines for the design and conduct of clinical trials, and the analysis of the resulting data, provide only limited advice on how to handle missing data. Thus, approaches to the analysis of data with an appreciable amount of missing values tend to be ad hoc and variable. The Prevention and Treatment of Missing Data in Clinical Trials concludes that a more principled approach to design and analysis in the presence of missing data is both needed and possible. Such an approach needs to focus on two critical elements: (1) careful design and conduct to limit the amount and impact of missing data and (2) analysis that makes full use of information on all randomized participants and is based on careful attention to the assumptions about the nature of the missing data underlying estimates of treatment effects. In addition to the highest priority recommendations, the book offers more detailed recommendations on the conduct of clinical trials and techniques for analysis of trial data.

Author : Lemuel A. Moyé
Publisher : Springer Science & Business Media
Page : 470 pages
File Size : 26,47 MB
Release : 2003-07-30
Category : Medical
ISBN : 9780387007274

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Concentrating on the rationale for the analyses, the difficulties posed by their interpretation, easily understood solutions, and useful problem sets, this book will help clinical investigators understand multiple analysis procedures and key issues. It is written for advanced medical students, clinical investigators at all levels, research groups within the pharmaceutical industry, regulators at the local, state, and federal level, and biostatisticians.