Dose Finding by the Continual Reassessment Method (Chapman & Hall/CRC Biostatistics Series 41)
By: Ying Kuen Cheung (author)Hardback
1 - 2 weeks availability
As clinicians begin to realize the important role of dose-finding in the drug development process, there is an increasing openness to "novel" methods proposed in the past two decades. In particular, the Continual Reassessment Method (CRM) and its variations have drawn much attention in the medical community, though it has yet to become a commonplace tool. To overcome the status quo in phase I clinical trials, statisticians must be able to design trials using the CRM in a timely and reproducible manner. A self-contained theoretical framework of the CRM for researchers and graduate students who set out to learn and do research in the CRM and dose-finding methods in general, Dose Finding by the Continual Reassessment Method features: * Real clinical trial examples that illustrate the methods and techniques throughout the book * Detailed calibration techniques that enable biostatisticians to design a CRM in timely manner * Limitations of the CRM are outlined to aid in correct use of method This book supplies practical, efficient dose-finding methods based on cutting edge statistical research.
More than just a cookbook, it provides full, unified coverage of the CRM in addition to step-by-step guidelines to automation and parameterization of the methods used on a regular basis. A detailed exposition of the calibration of the CRM for applied statisticians working with dose-finding in phase I trials, the book focuses on the R package 'dfcrm' for the CRM and its major variants. The author recognizes clinicians' skepticism of model-based designs, and addresses their concerns that the time, professional, and computational resources necessary for accurate model-based designs can be major bottlenecks to the widespread use of appropriate dose-finding methods in phase I practice. The theoretically- and empirically-based methods in Dose Finding by the Continual Reassessment Method will lessen the statistician's burden and encourage the continuing development and implementation of model-based dose-finding methods.
Department of Biostatistics, Columbia University, USA
Fundamentals Introduction Dose Finding in Clinical Trials The Maximum Tolerated Dose An Overview of Methodology Bibliographic Notes Exercises and Further Results The Continual Reassessment Method Introduction One-Stage Bayesian CRM Two-Stage CRM Simulating CRM Trials Practical Modifications Bibliographic Notes Exercises and Further Results One-Parameter Dose-ToxicityModels Introduction -Equivalent Models Model Assumptions+ Proof of Theorem 4.1+ Exercises and Further Results Theoretical Properties Introduction Coherence Large-Sample Properties Proofs+ Exercises and Further Results Empirical Properties Introduction Operating Characteristics A Nonparametric Optimal Benchmark Exercises and Further Results Design Calibration Specifications of a CRM Design Introduction Specifying the Clinical Parameters A Roadmap for Choosing the Statistical Component The Trial-and-Error Approach: Two Case Studies Initial Guesses of Toxicity Probabilities Introduction Half-width ( ) of Indifferent Interval Calibration of 77 Case Study: The Bortezomib Trial Exercises and Further Results Least Informative Normal Prior Introduction Least Informative Prior Calibration of 93 Optimal Least Informative Model Revisiting the Bortezomib Trial Initial Design Introduction Ordering of Dose Sequences Building Reference Initial Designs Practical Issues Case Study: NeuSTART Exercises and Further Results CRM and Beyond The Time-to-Event CRM Introduction The Basic Approach Numerical Illustration Enrollment Scheduling Theoretical Properties+ Two-Stage Design BibliographicNotes Exercises and Further Results CRM withMultiparameter Models Introduction Curve-Free Methods Rigidity Two-Parameter CRM+ BibliographicNotes Exercise and Further Results When the CRM Fails Introduction Trade-Off Perspective of MTD Bivariate Dose Finding Stochastic Approximation Introduction The Past Literature The Present Relevance The Future Challenge Assumptions on M(x) and Y (x)+ Exercises and Further Results References Index
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- ID: 9781420091519
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