Nancy A. Obuchowski – författare

Handbook for Clinical Trials of Imaging and Image-Guided Interventions is the first single-source, multi-disciplinary reference, based on the didactic sessions presented at the annual ‘Clinical Trials Methodology Workshop’ for radiologists, radiation oncologists and imaging scientists (sponsored by the Radiological Society of North America (RSNA)). It focuses on educating radiologists, radiation oncologists and those involved in imaging research with how to design and conduct clinical trials to evaluate imaging technology and imaging biomarkers.The internationally renowned contributors take a broad approach, starting with principles of technology assessment, and then move into specific topics covering the clinical trials of therapy and clinical research in imaging guided interventions including radiotherapy. They discuss the use of imaging as a predictor of therapeutic response, screening trial design, and the practicalities of how to run an efficient clinical trial and good working practices. Later chapters provide a comprehensive array of quantitative methods including: an introduction to statistical considerations in study design, biostatistical analysis methods and their role in clinical imaging research, methods for quantitative imaging biomarker studies, and an introduction to cost effectiveness analysis.Handbook for Clinical Trials of Imaging and Image-Guided Interventions will educate and prepare radiologists at all levels and in all capacities in planning and conducting clinical imaging trials.

The definitive resource for ensuring diagnostic tests meet the highest standards of statistical rigor and clinical effectiveness Statistical Methods in Diagnostic Medicine, 3rd Edition by Xiao-Hua Zhou, Jiarui Sun, Gene A. Pennello, Nancy A. Obuchowski and Donna K. McClish delivers the most comprehensive treatment of statistical methodologies for diagnostic test evaluation available today. The authors of the 2nd Edition – Peking University PKU Distinguished Chair Professor Zhou, Cleveland Clinic Professor Obuchowski, and Virginia Commonwealth University Professor Donna McClish – team with U.S. Food and Drug Administration senior mathematical statistician Pennello and doctoral researcher Sun to address a critical challenge facing medical professionals: ensuring that diagnostic tests used in clinical practice are accurate, methodologically sound, free from bias, and effective. This edition provides practitioners and researchers with the statistical foundation necessary to design, analyze, and validate diagnostic studies that can withstand regulatory scrutiny and clinical demands. The book has been thoroughly revised to incorporate the latest advances in diagnostic test methodology, featuring significant expansions in biomarker evaluation and benefit-risk assessment. The authors have restructured content to improve cohesion through integrated case studies that span multiple chapters, while updating each section with contemporary methods and streamlining discussions of older techniques to focus on the most relevant approaches for today’s diagnostic challenges. Readers will also find: Three entirely new chapters covering statistical methods for risk prediction, quantitative imaging biomarkers, and efficacy and effectiveness of biomarkers and other tests.Enhanced coverage of sample size calculations, accuracy estimation methods, and comparative analysis techniques for competing diagnostic testsAdvanced analytical approaches including methods for comparing correlated ROC curves in multi-reader studies and techniques for correcting verification biasComprehensive treatment of regression analysis applications in diagnostic accuracy research with updated methodological guidanceIntegrated case studies that demonstrate real-world application of statistical methods across different diagnostic scenarios and study designsPerfect for biostatisticians, applied statisticians, clinical researchers, and regulatory professionals working in diagnostic medicine, Statistical Methods in Diagnostic Medicine will also benefit graduate students and researchers interested in gaining the statistical expertise needed to design robust diagnostic studies.