Statistical Inference for Medical 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 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: 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: 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: 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: Peter Muennig
Publisher: John Wiley & Sons
ISBN: 1119011280
Category : Medical
Languages : en
Pages : 561
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Book Description
The field's bestselling reference, updated with the latest tools, data, techniques, and the latest recommendations from the Second Panel on Cost-Effectiveness in Health and Medicine Cost-Effectiveness Analysis in Health is a practical introduction to the tools, methods, and procedures used worldwide to perform cost-effective research. Covering every aspect of a complete cost-effectiveness analysis, this book shows you how to find which data you need, where to find it, how to analyze it, and how to prepare a high-quality report for publication. Designed for the classroom or the individual learner, the material is presented in simple and accessible language for those who lack a biostatistics or epidemiology background, and each chapter includes real-world examples and "tips and tricks" that highlight key information. Exercises throughout allow you to test your understanding with practical application, and the companion website features downloadable data sets for students, as well as lecture slides and a test bank for instructors. This new third edition contains new discussion on meta-analysis and advanced modeling techniques, a long worked example using visual modeling software TreeAge Pro, and updated recommendations from the U.S. Public Health Service's Panel on Cost-Effectiveness in Health and Medicine. This is the second printing of the 3rd Edition, which has been corrected and revised for 2018 to reflect the latest standards and methods. Cost-effectiveness analysis is used to evaluate medical interventions worldwide, in both developed and developing countries. This book provides process-specific instruction in a concise, structured format to give you a robust working knowledge of common methods and techniques. Develop a thoroughly fleshed-out research project Work accurately with costs, probabilities, and models Calculate life expectancy and quality-adjusted life years Prepare your study and your data for publication Comprehensive analysis skills are essential for students seeking careers in public health, medicine, biomedical research, health economics, health policy, and more. Cost-Effectiveness Analysis in Health walks you through the process from a real-world perspective to help you build a skillset that's immediately applicable in the field.
Author: Peter Muennig
Publisher: John Wiley & Sons
ISBN: 1119011264
Category : Medical
Languages : en
Pages : 480
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Book Description
The field's bestselling reference, updated with the latest tools, data, techniques, and the latest recommendations from the Second Panel on Cost-Effectiveness in Health and Medicine Cost-Effectiveness Analysis in Health is a practical introduction to the tools, methods, and procedures used worldwide to perform cost-effective research. Covering every aspect of a complete cost-effectiveness analysis, this book shows you how to find which data you need, where to find it, how to analyze it, and how to prepare a high-quality report for publication. Designed for the classroom or the individual learner, the material is presented in simple and accessible language for those who lack a biostatistics or epidemiology background, and each chapter includes real-world examples and "tips and tricks" that highlight key information. Exercises throughout allow you to test your understanding with practical application, and the companion website features downloadable data sets for students, as well as lecture slides and a test bank for instructors. This new third edition contains new discussion on meta-analysis and advanced modeling techniques, a long worked example using visual modeling software TreeAge Pro, and updated recommendations from the U.S. Public Health Service's Panel on Cost-Effectiveness in Health and Medicine. This is the second printing of the 3rd Edition, which has been corrected and revised for 2018 to reflect the latest standards and methods. Cost-effectiveness analysis is used to evaluate medical interventions worldwide, in both developed and developing countries. This book provides process-specific instruction in a concise, structured format to give you a robust working knowledge of common methods and techniques. Develop a thoroughly fleshed-out research project Work accurately with costs, probabilities, and models Calculate life expectancy and quality-adjusted life years Prepare your study and your data for publication Comprehensive analysis skills are essential for students seeking careers in public health, medicine, biomedical research, health economics, health policy, and more. Cost-Effectiveness Analysis in Health walks you through the process from a real-world perspective to help you build a skillset that's immediately applicable in the field.
Author: Laura M. Yee
Publisher:
ISBN:
Category :
Languages : en
Pages : 83
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Book Description
Cost data are being collected more frequently in randomized clinical trials in order to assess the cost-effectiveness of experimental treatments. As such, the goal of this dissertation is to study three separate topics which advance the analysis of medical cost data. First, time between recurrent medical events may be correlated with the cost incurred at each event. As a result, it may be of interest to describe the relationship between recurrent events and recurrent medical costs by estimating a joint distribution. In this paper, we therefore formulate a nonparametric estimator for the joint distribution of recurrent events and recurrent medical costs in right-censored data. We also derive the asymptotic variance of our estimator, and present simulation studies to demonstrate the performance of our point and variance estimators. Our estimator is shown to perform well for a range of levels of correlation, demonstrating that our estimators can be employed in a variety of situations when the correlation structure may be unknown in advance. We apply our methods to hospitalization events and their corresponding costs in the second Multicenter Automatic Defibrillator Implantation Trial (MADIT-II), which was a randomized clinical trial studying the effect of implantable cardioverter-defibrillators in preventing ventricular arrhythmia. Next, as the costs of medical care increase, more studies are evaluating cost in addition to effectiveness of treatments. Cost-effectiveness in randomized clinical trials has typically been evaluated only at the end of follow-up. However, cost-effectiveness may change over time. We therefore propose a nonparametric estimator to assess the incremental cost-effectiveness ratio over time. We also derive the asymptotic variance of our estimator and present implementation of simultaneous confidence bands. Simulation studies demonstrate the performance of our proposed methods. We also illustrate our methods using data from a randomized clinical trial, the second Multicenter Automatic Defibrillator Implantation Trial (MADIT-II). This trial studied the effects of implantable cardioverter-defibrillators on patients at high risk for cardiac arrhythmia. Results show that our estimator performs well in large samples, indicating promising future directions in the field of cost-effectiveness. Finally, in randomized clinical trials that study cost as well as effectiveness, a common complication is often noncompliance to assigned treatment. In situations where compliance in the trial may differ from compliance rates in the population, it may be of interest to study complier average cost-effectiveness. In this paper, we relate the standard intention-to-treat parameters to the complier average causal effects of two well-known measures of cost-effectiveness, the incremental net benefit (INB) and the incremental cost-effectiveness ratio (ICER). In particular, we show that the intention-to-treat effects are proportional to the complier average effect in the case of the INB, but that the intention-to-treat effect can be interpreted as the complier average effect for the ICER. We outline the assumptions required for these relationships to hold and we also present simulation studies confirming these properties. This work provides some incentive for employing the ICER over the INB when researchers are interested in complier average cost-effectiveness.
Author: Pei-Yun Chen
Publisher:
ISBN:
Category : Cost effectiveness
Languages : en
Pages : 172
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Book Description
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: 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
