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Clinical trials have two purposes -- to treat the patients in the trial, and to obtain information which increases our understanding of the disease and especially how patients respond to treatment. Statistical design provides a means to achieve both these aims, while statistical data analysis provides methods for extracting useful information from the trial data. Recent advances in statistical computing have enabled statisticians to implement very rapidly a broad array of methods which previously were either impractical or impossible. Biostatisticians are now able to provide much greater support to medical researchers working in both clinical and laboratory settings. As our collective toolkit of techniques for analyzing data has grown, it has become increasingly difficult for biostatisticians to keep up with all the developments in our own field. Recent Advances in Clinical Trial Design and Analysis brings together biostatisticians doing cutting-edge research and explains some of the more recent developments in biostatistics to clinicians and scientists who work in clinical trials.
Researchers in all clinical fields are fully aware of the importance of Quality of Life measurements in judging the efficacy of a given treatment. Psychological criteria play an important role in this evaluation. Assessment of Quality of Life in Clinical Trials: methods and practice explores the current state of the art and illustrates the benefits and potential of health related quality of life assessment in clinical trials. It covers a wide range of analytical issues, emphasizing new and innovative approaches that are of practical and clinical importance.
Researchers in all clinical fields are becoming increasingly aware of the importance of quality of life measurements in judging the efficacy of a given treatment, and it is becoming more common for psychological criteria to play an important role in the evaluation of therapies. In the past ten years a number of methods have been developed for carrying out such assessments. Quality of life research does however use special statistical methods which might well be unfamiliar to the clinician. Quality of life assessment in clinical trials: methods and practice explores these methods in a non-mathematical manner, comparing and contrasting the tools available to the clinician, and highlighting any potential pitfalls. It describes the methods used to collect and analyse quality of life data. The book will have widespread appeal to clinical trialists and researchers from a wide range of specialties.
Quality of life studies form an essential part of the evaluation of any treatment. Written by two authors who are well respected within this field, Quality of Life: The Assessment, Analysis and Interpretation of Patient-reported Outcomes, Second Edition lays down guidelines on assessing, analysing and interpreting quality of life data. The new edition of this standard book has been completely revised, updated and expanded to reflect many methodological developments emerged since the publication of the first edition. Covers the design of instruments, the practical aspects of implementing assessment, the analyses of the data, and the interpretation of the results Presents all essential information on Quality of Life Research in one comprehensive volume Explains the use of qualitative and quantitative methods, including the application of basic statistical methods Includes copious practical examples Fills a need in a rapidly growing area of interest New edition accommodates significant methodological developments, and includes chapters on computer adaptive testing and item banking, choosing an instrument, systematic reviews and meta analysis This book is of interest for everyone involved in quality of life research, and it is applicable to medical and non-medical, statistical and non-statistical readers. It is of particular relevance for clinical and biomedical researchers within both the pharmaceutical industry and practitioners in the fields of cancer and other chronic diseases. Reviews of the First Edition – Winner of the first prize in the Basis of Medicine Category of the BMA Medical Book Competition 2001: “This book is highly recommended to clinicians who are actively involved in the planning, analysis and publication of QoL research.” CLINICAL ONCOLOGY “This book is highly recommended reading.” QUALITY OF LIFE RESEARCH
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.
Based on Dr. Spilker's classic Quality of Life and Pharmacoeconomics in Clinical Trials, 2nd Edition, this streamlined sourcebook offers an easy-to-understand introduction to an increasingly critical aspect of health care. Seven succinct sections review key aspects of health-related quality of life and the essentials of pharmacoeconomics, providing expert answers to your most pressing questions: What generic HRQOL and disease-specific assessments are available? How are these scales chosen, used, and interpreted? What instruments do I need...and where can I find them? What is the relationship between pharmacoeconomics and quality of life? Between outcomes research and quality of life? Well-organized and easy to use, Quality of Life and Pharmacoeconomics: An Introduction will become a standard textbook for professionals and students in all areas of medical research and practice.
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.
This book reviews current methodology for assessing the health status of patients -- their 'quality of life' -- and shows how this methodology can be applied to specific diseases such as cancer, rheumatoid arthritis, angina and Parkinson's disease.
Patient-reported outcomes (PROs) are measures of how patients feel or what they are able to do in the context of their health status; PROs are reports, usually on questionnaires, about a patient's health conditions, health behaviors, or experiences with health care that individuals report directly, without modification of responses by clinicians or others; thus, they directly reflect the voice of the patient. PROs cover domains such as physical health, mental and emotional health, functioning, symptoms and symptom burden, and health behaviors. They are relevant for many activities: helping patients and their clinicians make informed decisions about health care, monitoring the progress of care, setting policies for coverage and reimbursement of health services, improving the quality of health care services, and tracking or reporting on the performance of health care delivery organizations. We address the major methodological issues related to choosing, administering, and using PROs for these purposes, particularly in clinical practice settings. We include a framework for best practices in selecting PROs, focusing on choosing appropriate methods and modes for administering PRO measures to accommodate patients with diverse linguistic, cultural, educational, and functional skills, understanding measures developed through both classic and modern test theory, and addressing complex issues relating to scoring and analyzing PRO data.