Survival Analysis Methods for Recurrent Medical Cost Data

Survival Analysis Methods for Recurrent Medical Cost Data PDF 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.

Survival Analysis Methods for Recurrent Medical Cost Data

Survival Analysis Methods for Recurrent Medical Cost Data PDF 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.

The Statistical Analysis of Recurrent Events

The Statistical Analysis of Recurrent Events PDF Author: Richard J. Cook
Publisher: Springer Science & Business Media
ISBN: 0387698094
Category : Medical
Languages : en
Pages : 415

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Book Description
This book presents models and statistical methods for the analysis of recurrent event data. The authors provide broad, detailed coverage of the major approaches to analysis, while emphasizing the modeling assumptions that they are based on. More general intensity-based models are also considered, as well as simpler models that focus on rate or mean functions. Parametric, nonparametric and semiparametric methodologies are all covered, with procedures for estimation, testing and model checking.

Modelling Survival Data in Medical Research, Second Edition

Modelling Survival Data in Medical Research, Second Edition PDF Author: David Collett
Publisher: CRC Press
ISBN: 1584883251
Category : Mathematics
Languages : en
Pages : 413

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Book Description
Critically acclaimed and resoundingly popular in its first edition, Modelling Survival Data in Medical Research has been thoroughly revised and updated to reflect the many developments and advances--particularly in software--made in the field over the last 10 years. Now, more than ever, it provides an outstanding text for upper-level and graduate courses in survival analysis, biostatistics, and time-to-event analysis.The treatment begins with an introduction to survival analysis and a description of four studies that lead to survival data. Subsequent chapters then use those data sets and others to illustrate the various analytical techniques applicable to such data, including the Cox regression model, the Weibull proportional hazards model, and others. This edition features a more detailed treatment of topics such as parametric models, accelerated failure time models, and analysis of interval-censored data. The author also focuses the software section on the use of SAS, summarising the methods used by the software to generate its output and examining that output in detail. Profusely illustrated with examples and written in the author's trademark, easy-to-follow style, Modelling Survival Data in Medical Research, Second Edition is a thorough, practical guide to survival analysis that reflects current statistical practices.

Modelling Survival Data in Medical Research

Modelling Survival Data in Medical Research PDF Author: David Collett
Publisher: CRC Press
ISBN: 1498731694
Category : Mathematics
Languages : en
Pages : 538

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Book Description
Modelling Survival Data in Medical Research describes the modelling approach to the analysis of survival data using a wide range of examples from biomedical research.Well known for its nontechnical style, this third edition contains new chapters on frailty models and their applications, competing risks, non-proportional hazards, and dependent censo

Survival Analysis

Survival Analysis PDF Author: David G. Kleinbaum
Publisher: Springer
ISBN: 0387291504
Category : Mathematics
Languages : en
Pages : 597

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Book Description
An excellent introduction for all those coming to the subject for the first time. New material has been added to the second edition and the original six chapters have been modified. The previous edition sold 9500 copies world wide since its release in 1996. Based on numerous courses given by the author to students and researchers in the health sciences and is written with such readers in mind. Provides a "user-friendly" layout and includes numerous illustrations and exercises. Written in such a way so as to enable readers learn directly without the assistance of a classroom instructor. Throughout, there is an emphasis on presenting each new topic backed by real examples of a survival analysis investigation, followed up with thorough analyses of real data sets.

Analysis of Multivariate Survival Data

Analysis of Multivariate Survival Data PDF Author: Philip Hougaard
Publisher: Springer Science & Business Media
ISBN: 1461213045
Category : Mathematics
Languages : en
Pages : 559

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Book Description
Survival data or more general time-to-event data occur in many areas, including medicine, biology, engineering, economics, and demography, but previously standard methods have requested that all time variables are univariate and independent. This book extends the field by allowing for multivariate times. As the field is rather new, the concepts and the possible types of data are described in detail. Four different approaches to the analysis of such data are presented from an applied point of view.

Applied Survival Analysis

Applied Survival Analysis PDF Author: David W. Hosmer
Publisher:
ISBN: 9780585381930
Category : Mathematics
Languages : en
Pages : 386

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Book Description
A Practical, Up-To-Date Guide To Modern Methods In The Analysis Of Time To Event Data. The rapid proliferation of powerful and affordable statistical software packages over the past decade has inspired the development of an array of valuable new methods for analyzing survival time data. Yet there continues to be a paucity of statistical modeling guides geared to the concerns of health-related researchers who study time to event data. This book helps bridge this important gap in the literature. Applied Survival Analysis is a comprehensive introduction to regression modeling for time to event data used in epidemiological, biostatistical, and other health-related research. Unlike other texts on the subject, it focuses almost exclusively on practical applications rather than mathematical theory and offers clear, accessible presentations of modern modeling techniques supplemented with real-world examples and case studies. While the authors emphasize the proportional hazards model, descriptive methods and parametric models are also considered in some detail. Key topics covered in depth include: * Variable selection. * Identification of the scale of continuous covariates. * The role of interactions in the model. * Interpretation of a fitted model. * Assessment of fit and model assumptions. * Regression diagnostics. * Recurrent event models, frailty models, and additive models. * Commercially available statistical software and getting the most out of it. Applied Survival Analysis is an ideal introduction for graduate students in biostatistics and epidemiology, as well as researchers in health-related fields.

Recurrent Events Data Analysis for Product Repairs, Disease Recurrences, and Other Applications

Recurrent Events Data Analysis for Product Repairs, Disease Recurrences, and Other Applications PDF Author: Wayne B. Nelson
Publisher: SIAM
ISBN: 0898715229
Category : Technology & Engineering
Languages : en
Pages : 157

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Book Description
Survival data consist of a single event for each population unit, namely, end of life, which is modeled with a life distribution. However, many applications involve repeated-events data, where a unit may accumulate numerous events over time. This applied book provides practitioners with basic nonparametric methods for such data.

Recurrent Events Data Analysis for Product Repairs, Disease Recurrences, and Other Applications

Recurrent Events Data Analysis for Product Repairs, Disease Recurrences, and Other Applications PDF Author: Wayne Nelson
Publisher: Cambridge University Press
ISBN: 9780898715224
Category : Mathematics
Languages : en
Pages : 176

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Book Description
Survival data consist of a single event for each population unit, namely, end of life, which is modeled with a life distribution. However, many applications involve repeated-events data, where a unit may accumulate numerous events over time. This applied book provides practitioners with basic nonparametric methods for such data.

Survival and Event History Analysis

Survival and Event History Analysis PDF Author: Odd Aalen
Publisher: Springer Science & Business Media
ISBN: 038768560X
Category : Mathematics
Languages : en
Pages : 550

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Book Description
The aim of this book is to bridge the gap between standard textbook models and a range of models where the dynamic structure of the data manifests itself fully. The common denominator of such models is stochastic processes. The authors show how counting processes, martingales, and stochastic integrals fit very nicely with censored data. Beginning with standard analyses such as Kaplan-Meier plots and Cox regression, the presentation progresses to the additive hazard model and recurrent event data. Stochastic processes are also used as natural models for individual frailty; they allow sensible interpretations of a number of surprising artifacts seen in population data. The stochastic process framework is naturally connected to causality. The authors show how dynamic path analyses can incorporate many modern causality ideas in a framework that takes the time aspect seriously. To make the material accessible to the reader, a large number of practical examples, mainly from medicine, are developed in detail. Stochastic processes are introduced in an intuitive and non-technical manner. The book is aimed at investigators who use event history methods and want a better understanding of the statistical concepts. It is suitable as a textbook for graduate courses in statistics and biostatistics.