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Design and analysis of clinical trials for predictive medicine / [edited by] Shigeyuki Matsui, Marc Buyse and Richard Simon.

Contributor(s): Material type: TextTextSeries: Chapman & Hall/CRC biostatistics seriesPublication details: Boca Raton : CRC Press, ©2015.Description: xvii, 381 p. : illustrations ; 24 cmISBN:
  • 9781466558151
Subject(s): DDC classification:
  • 000SB:615.5 23 M434
Contents:
Section I. Introductory overview -- Section II. Early clinical trials using biomarkers -- Section III. Phase III randomized clinical trials using biomarkers -- Section IV. Analysis of high-dimensional data and genomic signature developments -- Section V. Randomized trials with biomarker development and validation --Section VI. Evaluation of surrogate biomarkers.
Summary: This book is one of the first attempts to contribute to this evolution by laying a foundation for the use of appropriate statistical designs and methods in future clinical trials for predictive medicine. It is a useful resource for clinical biostatisticians, researchers focusing on predictive medicine, clinical investigators, translational scientists, and graduate biostatistics students.
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Holdings
Item type Current library Call number Status Date due Barcode Item holds
Books ISI Library, Kolkata 000SB:615.5 M434 (Browse shelf(Opens below)) Available 137250
Total holds: 0

Includes bibliographical references and index.

Section I. Introductory overview --
Section II. Early clinical trials using biomarkers --
Section III. Phase III randomized clinical trials using biomarkers --
Section IV. Analysis of high-dimensional data and genomic signature developments --
Section V. Randomized trials with biomarker development and validation --Section VI. Evaluation of surrogate biomarkers.

This book is one of the first attempts to contribute to this evolution by laying a foundation for the use of appropriate statistical designs and methods in future clinical trials for predictive medicine. It is a useful resource for clinical biostatisticians, researchers focusing on predictive medicine, clinical investigators, translational scientists, and graduate biostatistics students.

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