Design & Analysis of Clinical Trials for Economic Evaluation & Reimbursement: An Applied Approach Using SAS & STATA, 1st Edition (Hardback) book cover

Design & Analysis of Clinical Trials for Economic Evaluation & Reimbursement

An Applied Approach Using SAS & STATA, 1st Edition

By Iftekhar Khan

Chapman and Hall/CRC

313 pages | 56 B/W Illus.

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pub: 2015-11-18
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Economic evaluation has become an essential component of clinical trial design to show that new treatments and technologies offer value to payers in various healthcare systems. Although many books exist that address the theoretical or practical aspects of cost-effectiveness analysis, this book differentiates itself from the competition by detailing how to apply health economic evaluation techniques in a clinical trial context, from both academic and pharmaceutical/commercial perspectives. It also includes a special chapter for clinical trials in Cancer.

Design & Analysis of Clinical Trials for Economic Evaluation & Reimbursement is not just about performing cost-effectiveness analyses. It also emphasizes the strategic importance of economic evaluation and offers guidance and advice on the complex factors at play before, during, and after an economic evaluation.

Filled with detailed examples, the book bridges the gap between applications of economic evaluation in industry (mainly pharmaceutical) and what students may learn in university courses. It provides readers with access to SAS and STATA code. In addition, Windows-based software for sample size and value of information analysis is available free of charge—making it a valuable resource for students considering a career in this field or for those who simply wish to know more about applying economic evaluation techniques.

The book includes coverage of trial design, case report form design, quality of life measures, sample sizes, submissions to regulatory authorities for reimbursement, Markov models, cohort models, and decision trees. Examples and case studies are provided at the end of each chapter.

Presenting first-hand insights into how economic evaluations are performed from a drug development perspective, the book supplies readers with the foundation required to succeed in an environment where clinical trials and cost-effectiveness of new treatments are central. It also includes thought-provoking exercises for use in classroom and seminar discussions.


" . . . the book can be highly recommended to all researchers interested in implementing health-economic evaluations in investigator-initiated studies or pharmaceutical drug trials as well as MSc and postgraduate students of economics pursuing a career in the clinical drug development."

~International Society for Clinical Biostatistics

Table of Contents

Introduction to Economic Evaluation

Health Economics, Pharmacoeconomics, and Economic Evaluation

Important Concepts in Economic Evaluation

Health Economic Evaluation and Drug Development

Efficacy, Effectiveness and Efficiency

When Is a Pharmacoeconomic Hypothesis Possible?


Health Economic Evaluation Concepts

Incremental Cost-Effectiveness Ratio (ICER)

Incremental INMB

The Concept of Dominance

Types of Economic Evaluation

Statistical versus Health Economic Models


Appendix SAS/STATA Code

Designing Cost-Effectiveness into a Clinical Trial

Reasons for Collecting Economic Data in a Clinical Trial

Planning a Health Economic Evaluation in a Clinical Trial

Clinical Trial Design Issues in an Economic Evaluation

Integrating Economic Evaluation in a Clinical Trial: Considerations

CRF Design and Data Management Issues

Case Study of a Lung Cancer Trial with an Economic



Appendix: SAS/STATA

Analysing Cost Data Collected in a Clinical Trial

Collecting and Measuring Costs for the Case Report Form

Types of Costs

Other Concepts in Costs: Time Horizon and Discounting

CRFs for Collecting Resource Use Data in Clinical Trials

Statistical Modelling of Cost Data

Using Generalised Linear Models to Analyse Cost Data

Models for Skewed Distributions Outside the GLM Family of Distributions

Summary of Modelling Approaches

Handling Censored and Missing Costs

Strategies for Avoiding Missing Resource Data

Strategies for Analysing Cost Data When Data Are Missing or Censored

Imputation Methods

Censored Cost Data

Method of Lin et al. (1997)

Summary and Conclusion


Appendix: SAS/STATA Code

Quality of Life in Economic Evaluation

Quality of Life in Clinical Trials versus Quality of Life for Economic Evaluation

Disease-Specific and Generic Measures of HRQoL

HRQoL Instruments Used for the Purposes of Economic Evaluation

When HRQoL Data Have Not Been Collected in a Clinical Trial

HRQoL Metrics for Use in Economic Evaluations

Are Utility Measures Sensitive Enough for Detecting Treatment Differences?


Appendix 5A SAS/STATA Code

Technical Appendix: Beta Binomial Technical Details

Technical Appendix: Technical Summary of the GLM

Modelling in Economic Evaluation

Introduction to Modelling: Statistical versus Economic Modelling

Decision Tree Models

Markov Modelling/Cohort Simulation

Analysis of Patient-Level Data

Patient-Level Simulation

Other Issues in Modelling


Appendix: SAS/STATA Code

Sensitivity Analyses

Introduction to Sensitivity Analysis

One-Way Sensitivity Analysis

Two-Way Sensitivity Analysis


Bayesian Sensitivity Analyses

Issues in Interpreting and Reporting Results from Sensitivity Analysis


Appendix: SAS/STATA Code

Sample Size and Value of Information for Cost-Effectiveness Trials


Sample Sizes for Cost-Effectiveness

Sample Size Methods for Efficacy

Sample Size Formulae for Cost-Effectiveness: Examples

Factors Affecting Sample Sizes

The Minimum Sample Size to Establish Cost-Effectiveness

Bayesian Sample Size Approach

The Normality Assumption

Obtaining the Necessary Data and Tools for Calculating

Sample Size

Value of Information

Exercises for Chapter 8

Appendix 8A SAS/STATA Code

Technical Appendix 8B Derivation of Sample Size Formula

Technical Appendix 8C Comparison with Briggs and Tambour’s (2001) Approach

Mixed Treatment Comparisons, Evidence Synthesis





Appendix: SAS/STATA Code

Cost-Effectiveness Analyses of Cancer Trials


Modelling Patient-Level Data from Cancer Trials for Cost-


Flexible Parametric Survival Models

Modelling Survival Data Using a Flexible Parametric Model

Cost-Effectiveness of Lenalidomide

Transition Probabilities and Survival Rates

Handling Crossover (Treatment Switching) in Cancer Trials

Landmark Analysis and Presenting Survival Data by Tumour Response


Appendix: SAS/STATA Code

The Reimbursement Environment

Regulatory Requirements for Clinical Efficacy versus Payer Requirements for Value

Reimbursement and Payer Evidence Requirements across Different Countries

Market Access and Strategy

Value-Based Pricing

Submissions for Payer Evidence

Further Areas for Research





About the Author

Iftekhar Khan is a statistician, health economics researcher and academic at University College London (University of London). He has been an applied statistician for over 15 years in clinical trials, having worked in pharmaceutical companies and academic clinical trials units. Iftekhar Khan has completed degrees in statistics and mathematics from King’s College London, the University of Kent and the University of Cambridge, including a master’s in health economics and a PhD in health economic modelling (University College London).

About the Series

Chapman & Hall/CRC Biostatistics Series

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Subject Categories

BISAC Subject Codes/Headings:
MATHEMATICS / Probability & Statistics / General