Handbook of statistics in clinical oncology
著者
書誌事項
Handbook of statistics in clinical oncology
(A Chapman & Hall book)
CRC, 2017, c2012
3rd ed
- : pbk
大学図書館所蔵 全2件
  青森
  岩手
  宮城
  秋田
  山形
  福島
  茨城
  栃木
  群馬
  埼玉
  千葉
  東京
  神奈川
  新潟
  富山
  石川
  福井
  山梨
  長野
  岐阜
  静岡
  愛知
  三重
  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
  タイ
  イギリス
  ドイツ
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注記
"First issued in paperback 2017"--T.p. verso
Includes bibliographical references and index
内容説明・目次
内容説明
Many new challenges have arisen in the area of oncology clinical trials. New cancer therapies are often based on cytostatic or targeted agents, which pose new challenges in the design and analysis of all phases of trials. The literature on adaptive trial designs and early stopping has been exploding. Inclusion of high-dimensional data and imaging techniques have become common practice, and statistical methods on how to analyse such data have been refined in this area. A compilation of statistical topics relevant to these new advances in cancer research, this third edition of Handbook of Statistics in Clinical Oncology focuses on the design and analysis of oncology clinical trials and translational research.
Addressing the many challenges that have arisen since the publication of its predecessor, this third edition covers the newest developments involved in the design and analysis of cancer clinical trials, incorporating updates to all four parts:
Phase I trials: Updated recommendations regarding the standard 3 + 3 and continual reassessment approaches, along with new chapters on phase 0 trials and phase I trial design for targeted agents.
Phase II trials: Updates to current experience in single-arm and randomized phase II trial designs. New chapters include phase II designs with multiple strata and phase II/III designs.
Phase III trials: Many new chapters include interim analyses and early stopping considerations, phase III trial designs for targeted agents and for testing the ability of markers, adaptive trial designs, cure rate survival models, statistical methods of imaging, as well as a thorough review of software for the design and analysis of clinical trials.
Exploratory and high-dimensional data analyses: All chapters in this part have been thoroughly updated since the last edition. New chapters address methods for analyzing SNP data and for developing a score based on gene expression data. In addition, chapters on risk calculators and forensic bioinformatics have been added.
Accessible to statisticians and oncologists interested in clinical trial methodology, the book is a single-source collection of up-to-date statistical approaches to research in clinical oncology.
目次
Choosing a Phase I Design. Dose Finding Designs Based on the Continual Reassessment Method. Pharmacokinetics in Clinical Oncology: Statistical Issues. Statistics of Phase 0 Trials. CRM Trials for Assessing Toxicity and Efficacy. Seamless Phase I/II Trial Design for Assessing Toxicity and Efficacy for Targeted Agents. Overview of Phase II Clinical Trials. Designs Based on Toxicity and Response. Designs Using Time to Event Endpoints/Single Arm versus Randomized Phase II. Phase II Selection Designs. Phase II with Multiple Subgroups: Designs Incorporating Disease Subtype or Genetic Heterogeneity. Phase II/III Designs. On Use of Covariates in Randomization and Analysis of Clinical Trials. Factorial Designs with Time to Event Endpoints. Early Stopping of Clinical Trials. Noninferiority Trials. Phase III Trials for Targeted Agents. Adaptive Trial Designs. Design of a Clinical Trial for Testing the Ability of a Continuous Marker to Predict Therapy Benefit. Software for Design and Analysis of Clinical Trials. Cure-Rate Survival Models in Clinical Trials. Design and Analysis of Quality of Life Data. Economic Analyses alongside Cancer Clinical Trials. Structural and Molecular Imaging in Cancer Therapy Clinical Trials. Prognostic Factor Studies. Predictive Modeling of Gene Expression Data. Explained Variation and Explained Randomness for Proportional Hazards Models. Prognostic Groups by Tree-Based Partitioning and Data Refinement Methods. Risk Calculators. Developing a Score Based upon Gene Expression Profiling and Validation. Analysis of DNA Microarrays. Methods for SNP Regression Analysis in Clinical Studies: Selection, Shrinkage, and Logic. Forensic Bioinformatics. Index.
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