Statistical Inference for Costs and Incremental Cost-effectiveness Ratios with Censored Data PDF Download
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Author: Shuai Chen
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Cost-effectiveness analysis is widely conducted in the economic evaluation of new treatment options. In many clinical and observational studies of costs, data are often censored. Censoring brings challenges to both medical cost estimation and cost-effectiveness analysis. Although methods have been proposed for estimating the mean costs with censored data, they are often derived from theory and it is not always easy to understand how these methods work. We provide an alternative method for estimating the mean cost more efficiently based on a replace-from-the-right algorithm, and show that this estimator is equivalent to an existing estimator based on the inverse probability weighting principle and semiparametric efficiency theory. Therefore, we provide an intuitive explanation to a theoretically derived mean cost estimator. In many applications, it is also important to estimate the survival function of costs. We propose a generalized redistribute-to-the right algorithm for estimating the survival function of costs with censored data, and show that it is equivalent to a simple weighted survival estimator of costs based on inverse probability weighting techniques. Motivated by this redistribute-to-the-right principle, we also develop a more efficient survival estimator for costs, which has the desirable property of being monotone, and more efficient, although not always consistent. We conduct simulation to compare our method with some existing survival estimators for costs, and find the bias seems quite small. Thus, it may be considered as a candidate for survival estimator for costs in a real setting when the censoring is heavy and cost history information is available. Finally, we consider one special situation in conducting cost-effectiveness analysis, when the terminating events for survival time and costs are different. Traditional methods for statistical inference cannot deal with such data. We propose a new method for deriving the confidence interval for the incremental cost-effectiveness ratio under this situation, based on counting process and the general theory for missing data process. The simulation studies show that our method performs very well for some practical settings. Our proposed method has a great potential of being applied to a real setting when different terminating events exist for survival time and costs.
Author: Shuai Chen
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Cost-effectiveness analysis is widely conducted in the economic evaluation of new treatment options. In many clinical and observational studies of costs, data are often censored. Censoring brings challenges to both medical cost estimation and cost-effectiveness analysis. Although methods have been proposed for estimating the mean costs with censored data, they are often derived from theory and it is not always easy to understand how these methods work. We provide an alternative method for estimating the mean cost more efficiently based on a replace-from-the-right algorithm, and show that this estimator is equivalent to an existing estimator based on the inverse probability weighting principle and semiparametric efficiency theory. Therefore, we provide an intuitive explanation to a theoretically derived mean cost estimator. In many applications, it is also important to estimate the survival function of costs. We propose a generalized redistribute-to-the right algorithm for estimating the survival function of costs with censored data, and show that it is equivalent to a simple weighted survival estimator of costs based on inverse probability weighting techniques. Motivated by this redistribute-to-the-right principle, we also develop a more efficient survival estimator for costs, which has the desirable property of being monotone, and more efficient, although not always consistent. We conduct simulation to compare our method with some existing survival estimators for costs, and find the bias seems quite small. Thus, it may be considered as a candidate for survival estimator for costs in a real setting when the censoring is heavy and cost history information is available. Finally, we consider one special situation in conducting cost-effectiveness analysis, when the terminating events for survival time and costs are different. Traditional methods for statistical inference cannot deal with such data. We propose a new method for deriving the confidence interval for the incremental cost-effectiveness ratio under this situation, based on counting process and the general theory for missing data process. The simulation studies show that our method performs very well for some practical settings. Our proposed method has a great potential of being applied to a real setting when different terminating events exist for survival time and costs.
Author: Shuai Chen
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Cost-effectiveness analysis is widely conducted in the economic evaluation of new treatments, due to skyrocketing health care costs and limited resource available. Censored costs data poses a unique problem for cost estimation due to "induced informative censoring" problem. Thus, many standard approaches for survival analysis are not valid for the analysis of cost data. We first derive the confidence interval for the incremental cost-effectiveness ratio for a special case, when terminating events are different for survival time and costs. Then we study how to intuitively explain some existing estimators for costs, based on the generalized redistribute-to-the-right algorithm. Motivated by that idea, we also propose two improved survival estimators of costs, based on generalized redistribute-to-the-right algorithm and kernel method. We first consider one special situation in conducting cost-effectiveness analysis, when the terminating events for survival time and costs are different. Traditional methods for statistical inference cannot deal with such data. We propose a new method for deriving the confidence interval for the incremental cost-effectiveness ratio under this situation, based on the counting process theory and the general theory for missing data process. The simulation studies and real data example show that our method performs very well for some practical settings. In addition, we provide intuitive explanation to a mean cost estimator and a survival estimator for costs, based on generalized redistribute-to-the-right algorithm. Since those estimators are derived based on the inverse probability weighting principle and semiparametric efficiency theory, it is not always easy to understand how these methods work. Therefore, our work engenders a better understanding of those theoretically derived cost estimators. Motivated by the idea of generalized redistribute-to-the-right algorithm, we propose an estimator for the survival function of costs. The proposed estimator is naturally monotone, more efficient than some existing survival estimators, and has a quite small bias in many realistic settings. We further propose a kernel-based survival estimator for costs. The latter estimator, which is asymptotically unbiased, overcomes the deficiency of the former estimator, while preserving the nice properties. Our proposed estimators outperform existing estimators under various scenarios in simulation and real data example. The electronic version of this dissertation is accessible from http://hdl.handle.net/1969.1/155096
Author: Andrew R. Willan
Publisher: John Wiley & Sons
ISBN: 0470856270
Category : Mathematics
Languages : en
Pages : 210
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Book Description
The statistical analysis of cost-effectiveness data is becoming increasingly important within health and medical research. Statistical Analysis of Cost-Effectiveness Data provides a practical book that synthesises the huge amount of research that has taken place in the area over the last two decades. Comprising an up-to-date overview of the statistical analysis of cost-effectiveness data, the book is supported by numerous worked examples from the author’s own experience. It has been written in a style suitable for medical statisticians and health care professionals alike. Key features include: an overview of statistical methods used in the analysis of cost-effectiveness data. coverage of Bayesian methodology. illustrated throughout by worked examples using real data. suitability for health care professionals with limited statistical knowledge. discussion of software used for data analysis. An essential reference for biostatisticians and health economists engaged in cost-effectiveness analysis of health-care interventions, both in academia and industry. Also of interest to graduate students of biostatistics, public health and economics.
Author: Iftekhar Khan
Publisher: CRC Press
ISBN: 0429531842
Category : Mathematics
Languages : en
Pages : 334
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Book Description
Cancer is a major healthcare burden across the world and impacts not only the people diagnosed with various cancers but also their families, carers, and healthcare systems. With advances in the diagnosis and treatment, more people are diagnosed early and receive treatments for a disease where few treatments options were previously available. As a result, the survival of patients with cancer has steadily improved and, in most cases, patients who are not cured may receive multiple lines of treatment, often with financial consequences for the patients, insurers and healthcare systems. Although many books exist that address economic evaluation, Economic Evaluation of Cancer Drugs using Clinical Trial and Real World Data is the first unified text that specifically addresses the economic evaluation of cancer drugs. The authors discuss how to perform cost-effectiveness analyses while emphasising the strategic importance of designing cost-effectiveness into cancer trials and building robust economic evaluation models that have a higher chance of reimbursement if truly cost-effective. They cover the use of real-world data using cancer registries and discuss how such data can support or complement clinical trials with limited follow up. Lessons learned from failed reimbursement attempts, factors predictive of successful reimbursement and the different payer requirements across major countries including US, Australia, Canada, UK, Germany, France and Italy are also discussed. The book includes many detailed practical examples, case studies and thought-provoking exercises for use in classroom and seminar discussions. Iftekhar Khan is a medical statistician and health economist and a lead statistician at Oxford Unviersity’s Center for Statistics in Medicine. Professor Khan is also a Senior Research Fellow in Health Economics at University of Warwick and is a Senior Statistical Assessor within the Licensing Division of the UK Medicine and Health Regulation Agency. Ralph Crott is a former professor in Pharmacoeconomics at the University of Montreal in Quebec, Canada and former head of the EORTC Health Economics Unit and former senior health economist at the Belgian HTA organization. Zahid Bashir has over twelve years experience working in the pharmaceutical industry in medical affairs and oncology drug development where he is involved in the design and execution of oncology clinical trials and development of reimbursement dossiers for HTA submission.
Author: Henry A. Glick
Publisher: OUP Oxford
ISBN: 0191508055
Category : Medical
Languages : en
Pages : 265
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Book Description
It is becoming increasingly important to examine the relationship between the outcomes of a clinical trial and the costs of the medical therapy under study. The results of such analysis can affect reimbursement decisions for new medical technologies, drugs, devices or diagnostics. It can aid companies seeking to make claims about the cost-effectiveness of their product, as well as allowing early consideration of the economic value of therapies which may be important to improving initial adoption decisions. It is also vital for addressing the requirements of regulatory bodies. Economic Evaluation in Clinical Trials provides practical advice on how to conduct cost-effectiveness analyses in controlled trials of medical therapies. This new edition has been extensively rewritten and revised; topics discussed range from design issues such as the types of services that should be measured and price weights, to assessment of quality-adjusted life years. Illustrative materials, case histories and worked examples are included to encourage the reader to apply the methods discussed. These exercises are supported with datasets, programmes and solutions made available online.
Author: Douglas E. Faries
Publisher: SAS Press
ISBN: 9781607642275
Category : Medical care
Languages : en
Pages : 0
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Book Description
This book guides researchers in performing and presenting high-quality analyses of all kinds of non-randomized studies, including analyses of observational studies, claims database analyses, assessment of registry data, survey data, pharmaco-economic data, and many more applications. The text is sufficiently detailed to provide not only general guidance, but to help the researcher through all of the standard issues that arise in such analyses. Just enough theory is included to allow the reader to understand the pros and cons of alternative approaches and when to use each method. The numerous contributors to this book illustrate, via real-world numerical examples and SAS code, appropriate implementations of alternative methods. The end result is that researchers will learn how to present high-quality and transparent analyses that will lead to fair and objective decisions from observational data. This book is part of the SAS Press program.
Author: Corina Mihaela Sirbu
Publisher:
ISBN:
Category : Medical care, Cost of
Languages : en
Pages : 432
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Book Description
Author: Marthe R. Gold
Publisher: Oxford University Press
ISBN: 9780195108248
Category : Business & Economics
Languages : en
Pages : 462
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Book Description
Cost-effectiveness in health and medicine presents a consensus of experts on appropriate methods for standardizing the conduct of CEAs for use in policy arenas. Standardization is of particular importance for CEA, because it allows comparisons of the costs and health outcomes of alternative methods of improving health, such as public health programs and medical technologies. The book provides a detailed discussion of the theoretical background underlying areas of controversy, and uses theory to guide explicit recommendations for study conduct.
Author: D.R. Helsel
Publisher: Elsevier
ISBN: 0080875084
Category : Science
Languages : en
Pages : 539
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Book Description
Data on water quality and other environmental issues are being collected at an ever-increasing rate. In the past, however, the techniques used by scientists to interpret this data have not progressed as quickly. This is a book of modern statistical methods for analysis of practical problems in water quality and water resources. The last fifteen years have seen major advances in the fields of exploratory data analysis (EDA) and robust statistical methods. The 'real-life' characteristics of environmental data tend to drive analysis towards the use of these methods. These advances are presented in a practical and relevant format. Alternate methods are compared, highlighting the strengths and weaknesses of each as applied to environmental data. Techniques for trend analysis and dealing with water below the detection limit are topics covered, which are of great interest to consultants in water-quality and hydrology, scientists in state, provincial and federal water resources, and geological survey agencies. The practising water resources scientist will find the worked examples using actual field data from case studies of environmental problems, of real value. Exercises at the end of each chapter enable the mechanics of the methodological process to be fully understood, with data sets included on diskette for easy use. The result is a book that is both up-to-date and immediately relevant to ongoing work in the environmental and water sciences.
Author: Nancy Devlin
Publisher: Springer Nature
ISBN: 3030476227
Category : Medical
Languages : en
Pages : 114
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Book Description
This open access book is the first published guide about how to analyse data produced by the EQ-5D, one of the most widely used Patient Reported Outcomes questionnaires world wide. The authors provide practical, clear and comprehensive guidance in five concise chapters. Following an overview of the EQ-5D and its analysis, we describe how the questionnaire data – the EQ-5D profile and EQ VAS – can be analysed in different ways to generate important insights into peoples’ health. We then show how the value sets which accompany the EQ-5D can be applied to summarise patients’ data. The final chapter deals with advanced topics, including the use of Minimally Important Differences, case-mix adjustment, mapping, and more. This book is essential for those new to analyzing EQ-5D data and will be also be valuable for those with more experience. The methods can be applied to any EQ-5D instrument (for example, the three- and five-level and Youth versions) and many of the methods described will be equally relevant to other Patient Reported Outcomes instruments.
