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Frontiers of Biostatistical Methods and Applications in Clinical Oncology

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Cover of 'Frontiers of Biostatistical Methods and Applications in Clinical Oncology'

Table of Contents

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    Book Overview
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    Chapter 1 Challenges for Biometry in 21st Century Oncology
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    Chapter 2 Statistical Challenges with the Advances in Cancer Therapies
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    Chapter 3 Random Walk and Parallel Crossing Bayesian Optimal Interval Design for Dose Finding with Combined Drugs
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    Chapter 4 A Comparative Study of Model-Based Dose-Finding Methods for Two-Agent Combination Trials
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    Chapter 5 Evaluation of Safety in Biomarker Driven Multiple Agent Phase IB Trial
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    Chapter 6 Bayesian Phase II Single-Arm Designs
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    Chapter 7 Phase III Clinical Trial Designs Incorporating Predictive Biomarkers: An Overview
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    Chapter 8 Bayesian, Utility-Based, Adaptive Enrichment Designs with Frequentist Error Control
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    Chapter 9 Evaluating Personalized Medicine in Multi-marker Multi-treatment Clinical Trials: Accounting for Heterogeneity
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    Chapter 10 The Probability of Being in Response Function and Its Applications
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    Chapter 11 Cure-Rate Survival Models and Their Application to Cancer Clinical Trials
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    Chapter 12 Evaluation of Surrogate Endpoints Using a Meta-Analysis Approach with Individual Patient Data: Summary of a Gastric Cancer Meta-Analysis Project
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    Chapter 13 Machine Learning Techniques in Cancer Prognostic Modeling and Performance Assessment
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    Chapter 14 Optimal Three-Group Splits Based on a Survival Outcome
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    Chapter 15 A Smooth Basis for Clinical Subgroup Analysis
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    Chapter 16 Meta-Analysis of Prognostic Studies Evaluating Time-Dependent Diagnostic and Predictive Capacities of Biomarkers
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    Chapter 17 Statistical Methodology and Engineering for Next Generation Clinical Risk Calculators
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    Chapter 18 Evaluation of Cancer Risk in Epidemiologic Studies with Genetic and Molecular Data
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    Chapter 19 Effect of Helicobacter pylori Eradication on Gastric Cancer Prevention in Korea: A Randomized Controlled Clinical Trial
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    Chapter 20 Contemporary Evaluation of Breast Cancer Screening
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    Chapter 21 Mediation Analysis for Multiple Causal Mechanisms
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    Chapter 22 Sample Size Calculation for Differential Expression Analysis of RNA-Seq Data
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    Chapter 23 Efficient Study Designs and Semiparametric Inference Methods for Developing Genomic Biomarkers in Cancer Clinical Research
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    Chapter 24 Supervised Dimension-Reduction Methods for Brain Tumor Image Data Analysis
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    Chapter 25 An Evaluation of Gene Set Analysis for Biomarker Discovery with Applications to Myeloma Research
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