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Elsevier

Translational Radiation Oncology

  • 1 Edición - 3 de agosto de 2023
  • Última edición
  • Editores: Jeffrey A. Bakal, Daniel Kim, David Wazer, Adam E.M. Eltorai
  • Idioma: Inglés

Translational Radiation Oncology covers the principles of evidence-based medicine and applies them to the design of translational research. The book provides valuable discussio… Leer más

Descripción

Translational Radiation Oncology covers the principles of evidence-based medicine and applies them to the design of translational research. The book provides valuable discussions on the critical appraisal of published studies and recent developments in radiation oncology, allowing readers to learn how to evaluate the quality of such studies with respect to measuring outcomes and make effective use of all types of evidence. By reading this book, researchers have access to a practical approach to help them navigate challenging considerations in study design and implementation.

It is a valuable resource for researchers, oncologists and members of biomedical field who want to understand more about translational research applied to the field of radiation oncology. Translational medicine serves as an indispensable tool in grant writing and funding efforts, so understanding how to apply its principles to research is necessary to guarantee that results will be impactful to patients.

Puntos claves

  • Provides a clear process for understanding, designing, executing and analyzing clinical and translational research
  • Presents practical, step-by-step guidance to help readers take ideas from the lab to the bedside
  • Written by a team of oncologists, radiologists and clinical research experts that fully cover translational research in radiation oncology

De interès para

Researchers on radiation oncology, clinicians, oncologists

Índice

INTRODUCTION 1. Introduction2. Translational Process3. Scientific Method4. Basic Research

PRE-CLINCIAL: DISCOVERY & DEVELOPMENT 5. Overview of Preclinical Research6. What problem are you Solving?7. Types of Interventions8. Drug discovery9. Drug Testing10. Device Discovery and Prototyping11. Device Testing12. Diagnostic Discovery13. Diagnostic Testing14. Procedural Technique Development15. Behavioral Intervention16. Artificial Intelligence

CLINICAL: FUNDAMENTALS 17. Introduction to clinical research: What is it? Why is it needed?18. The question: Types of research questions and how to develop them19. Study population: Who and why them?20. Outcome measurements: What data is being collected and why?21. Optimizing the Question: Balancing Significance and Feasibility22. Statistical Efficiency in Study Design

STATISTICAL PRINCIPLES 23. Basic statistical principles24. Distributions25. Hypotheses and error types26. Power27. Regression28. Continuous variable analyses: t-test, Man Whitney, Wilcoxin rank29. Categorical variable analyses: Chi-square, fisher exact, Mantel hanzel30. Analysis of variance31. Correlation32. Biases33. Basic science statistics34. Sample Size35. Statistical Software

CLINICAL: STUDY TYPES 36. Design principles: Hierarchy of study types37. Case series: Design, measures, classic example38. Case-control study: Design, measures, classic example39. Cohort study: Design, measures, classic example40. Cross-section study: Design, measures, classic example41. Longitudinal Study: Design, Measures, Classic Example42. Meta-analysis: Design, measures, real-world examples43. Cost-effectiveness study: Design, measures, classic example44. Diagnostic test evaluation: Design, measures, classic example 45. Reliability study: Design, measures, classic example46. Database studies47. Surveys and questionnaires: Design, measures, classic example48. Qualitative methods and mixed methods49. Visual analytics: design, measures, classic example

CLINICAL TRIALS 50. Randomized control: Design, measures, classic example51. Nonrandomized control: Design, measures, classic example52. Historical control: Design, measures, classic example53. Cross-over: Design, measures, classic example54. Factorial design: Design, measures, classic example55. Large, pragmatic: Design, measures, classic example56. Equivalence and noninferiority: Design, measures, classic example57. Adaptive: Design, measures, classic example58. Randomization: Fixed or adaptive procedures59. Blinding: Who and how?60. Multicenter considerations61. Phase 0 Trials: Window of Opportunity62. Registries63. Phases of Clinical Trials64. IDEAL Framework

CLINICAL: PREPARATION 65. Patient Perspectives66. Ethics and review boards67. Regulatory considerations for new drugs and devices68. Funding approaches69. Conflicts of Interest70. Subject recruitment71. Data management72. Quality control73. Special Populations74. Report Forms: Harm and Quality of Life 75. Subject adherence76. Survival analysis

REGULATORY BASICS 77. FDA overview78. IND79. New drug application80. Devices81. Radiation-Emitting Electronic Products82. Orphan Drugs83. Biologics84. Combination Products85. CMC and GxP86. Post-Market Drug Safety Monitoring87. Post-Market Device Safety Monitoring

CLINICAL IMPLEMENTATION 88. Implementation Research89. Design and Analysis90. Mixed-Methods Research91. Guideline Development92. Cooperative Group Research93. Digital Health

PUBLIC HEALTH 94. Public Health95. Epidemiology96. Factors97. Good Questions98. Population- and Environmental-Specific Considerations99. Law, Policy, and Ethics100. Public Health Institutions and Systems101. DEI (Diversity, equity, inclusion)

PRACTICAL RESOURCES102. Ethics in Scientific Publishing103. Presenting Data104. Manuscript Preparation105. Promoting Research106. Social Media107. Quality Improvement108. Education to translate research into practice109. Team Science and Building a Team110. Patent Basics111. Venture Pathways112. SBIR/STTR113. Sample Forms and Templates

Detalles del producto

  • Edición: 1
  • Última edición
  • Publicado: 3 de agosto de 2023
  • Idioma: Inglés

Sobre los editores

JB

Jeffrey A. Bakal

Dr. Bakal, is the Program Director for Provincial Research Data Services at Alberta Health Services, which operates the Alberta Strategy for Patient Oriented Research (SPOR) data platform. He also leads the Health Service Statistical and Analytics Methods teams. Over 10 years, he has worked with health services data, including randomized clinical trials. He completed his PhD jointly through the Department of Mathematics and Statistics and the School of Physical Health and Education at Queen’s University. His work includes methodological contributions and analyses supporting international studies spanning business strategy, ophthalmology, cardiology, and geriatric medicine, as well as analyses of kinematic data, through peer-reviewed publications and conference presentations. Current interests include developing statistical methodology for time-to-event data and building classification tools to support patient decision-making processes.
Afiliaciones y experiencia
Division General Internal Medicine, Faculty of Medicine and Dentistry, University of Alberta, Edmonton Alberta, Canada

DK

Daniel Kim

Daniel Kim works in Radiation Oncology at the Inova Schar Cancer Institute, Fairfax, VA, USA.
Afiliaciones y experiencia
Radiation Oncology, Inova Schar Cancer Institute, Fairfax, VA, USA

DW

David Wazer

David E. Wazer, MD, is Professor and Chairman of the Department of Radiation Oncology at Brown University. He is radiation oncologist-in-chief at Rhode Island Hospital, the Miriam Hospital, Newport Hospital, and Women and Infants Hospital. He serves as Director of the Lifespan Cancer Institute. Dr. Wazer’s current areas of clinical research include the study of the efficacy, toxicity, and cost/utility analysis of image-guided radiation therapy, proton beam radiotherapy, partial breast irradiation, and brachytherapy. He is actively involved in the development of clinical trials for cancers of the breast, skin, GI tract, and lung. He is also actively engaged in multiple initiatives to promote and advance oncology care in the developing world.
Afiliaciones y experiencia
Professor and Chairman, Department of Radiation Oncology, Warren Alpert Medical School, Brown University, USA

AE

Adam E.M. Eltorai

Dr Adam E. M. Eltorai, MD, PhD completed his graduate studies in Biomedical Engineering and Biotechnology along with his medical degree from Brown University. His work has spanned the translational spectrum with a focus on medical technology innovation and development. Dr. Eltorai has published numerous articles and books.

Afiliaciones y experiencia
Harvard Medical School, Boston, MA, USA

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