Description
Statistical Analysis of Cost-effectiveness Data Cost-effectiveness analysis is the simultaneous Statistical comparison of two or more groups with respect to costs and effectiveness. A prime example of this is the comparison of health-care interventions, where there is a growing expectation from policymakers that evidence supporting the cost-effectiveness of new interventions be provided along with customary data on efficacy and safety. Statistical Analysis of Cost-effectiveness Data provides an overview of the statistical methods used in such analysis and gives an illustrated summary of the key developments in statistical issues related to cost-effectiveness comparisons, over the last decade. * Provides an up-to-date overview of statistical methods used in the analysis of cost-effectiveness data. * Discusses all the major issues in the field, including: * Parameter estimation for both censored and uncensored data; * Making inference using cost-effectiveness ratios; * Incremental net benefit plots and cost-effectiveness ratios; * Incremental net benefit plots and cost-effectiveness acceptability curves; * Covariate adjustment and sub-group analyses; * Multinational trials; * Sample size determinations using both classical and Bayesian approaches. * Illustrated throughout by worked examples from the authors’ own experiences. Statistical Analysis of Cost-effectiveness Data is ideal for biostatisticians and health economists both in academia and industry. There is also much of use for graduate students of biostatistics, public health and economics, as well as individuals working in government regulator agencies. STATISTICS IN PRACTICE A series of practical books outlining the use of statistical techniques in a wide range of applications areas: * HUMAN AND BIOLOGICAL SCIENCES * EARTH AND ENVIRONMENTAL SCIENCES * INDUSTRY, COMMERCE AND FINANCE Preface. 1. Concepts. 1.1 Introduction. 1.2 Cost-effectiveness data and the parameters of interest. 1.3 The cost-effectiveness plane, the ICER and INB. 1.4 Outline. 2. Parameter Estimation for Non-censored Data. 2.1 Introduction. 2.2 Cost. 2.2.1 Sample means for estimating incremental cost. 2.2.2 Using multiple regression models. 2.2.3 Transformation (and the retransformation problem). 2.2.4 Generalized linear models. 2.2.5 Two-part models for excess zeros. 2.2.6 Cost prediction models. 2.3 Effectiveness. 2.3.1 Probability of surviving. 2.3.2 Mean survival time. 2.3.3 Mean quality-adjusted survival time. 2.3.4 Mean quality-adjusted survival: controlling for baseline utility. 2.4 Summary. 3. Parameter Estimation for Censored Data. 3.1 Introduction. 3.2 Mean Cost. 3.2.1 Direct (Lin) method. 3.2.2 Inverse-probability weighting. 3.3 Effectiveness. 3.3.1 Probability of surviving. 3.3.2 Mean survival time. 3.3.3 Mean quality-adjusted survival time. 3.4 Summary. 4. Cost-effectiveness Analysis. 4.1 Introduction. 4.2 Incremental cost-effectiveness ratio. 4.3 Incremental net benefit. 4.4 The cost-effectiveness acceptability curve. 4.5 Using bootstrap methods. 4.6 A Bayesian incremental net benefit approach. 4.7 Kinked thresholds. 4.8 Summary. 5. Cost-effectiveness Analysis: Examples. 5.1 Introduction. 5.2 The CADET-Hp trial. 5.3 Symptomatic hormone-resistant prostate cancer. 5.4 The Canadian implantable defibrillator study (CIDS). 5.5 The EVALUATE trial. 5.6 Bayesian approach applied to the UK PDS study. 5.7 Summary. 6. Power and Sample Size Determination. 6.1 Introduction. 6.2 Approaches based on the cost-effectiveness plane. 6.2.1 Briggs and Gray. 6.2.2 Willan and O’Brien. 6.2.3 Gardiner et al.. 6.3 The classical approach based on net benefit. 6.3.1 The method. 6.3.2 Example. 6.4 Bayesian take on the classical approach. 6.4.1 The Method. 6.4.2 Example. 6.5 The value of information approach. 6.5.1 The method. 6.5.2 Example. 6.6 Summary. 7. Covariate Adjustment and Sub-group Analysis. 7.1 Introduction. 7.2 Non-censored data. 7.2.1 Example, non-censored data. 7.3 Censored data. 7.3.1 Cost. 7.3.2 Quality-adjusted survival time. 7.3.3 Survival time. 7.3.4 The Canadian implantable defibrillator study (CIDS). 7.3.5 The evaluate trial. 7.4 Summary. 8. Multicenter and Multinational Trials. 8.1 Introduction. 8.2 Background to multinational cost-effectiveness. 8.3 Fixed effect approaches. 8.3.1 Willke et al.. 8.3.2 Cook et al.. 8.4 Random effects approaches. 8.4.1 Aggregate level analysis: multicenter trials. 8.4.2 Aggregate level analysis: multinational trials. 8.4.3 Hierarchical modeling. 8.5 Summary. 9. Modeling Cost-effectiveness. 9.1 Introduction. 9.2 A general framework for modeling cost-effectiveness results. 9.3 Case study: an economic appraisal of the goal study. 9.3.1 The GOAL study. 9.3.2 Standard approach to estimating cost-effectiveness. 9.3.3 An alternative approach to estimating cost-effectiveness. 9.3.4 Comparing the two analyses of GOAL. 9.4 Summary. References. Author Index. Subject Index. Series List.
