Translational Radiation Oncology (eBook, ePUB)

Redaktion: Bakal, Jeffrey A.; Eltorai, Adam E. M.; Wazer, David; Kim, Daniel

• Format: ePub

Produktbeschreibung

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.

• 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

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Produktdetails

• Verlag: Elsevier Science & Techn.
• Seitenzahl: 500
• Erscheinungstermin: 3. August 2023
• Englisch
• ISBN-13: 9780323884242
• Artikelnr.: 68534414

Inhaltsangabe

INTRODUCTION 1. Introduction
2. Translational Process
3. Scientific Method
4. Basic Research PRE-CLINCIAL: DISCOVERY AND DEVELOPMENT 5. Overview of Preclinical Research
6. What problem are you Solving?
7. Types of Interventions
8. Drug discovery
9. Drug Testing
10. Device Discovery and Prototyping
11. Device Testing
12. Diagnostic Discovery
13. Diagnostic Testing
14. Procedural Technique Development
15. Behavioral Intervention
16. 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 them
19. Study population: Who and why them?
20. Outcome measurements: What data is being collected and why?
21. Optimizing the Question: Balancing Significance and Feasibility
22. Statistical Efficiency in Study Design STATISTICAL PRINCIPLES 23. Basic statistical principles
24. Distributions
25. Hypotheses and error types
26. Power
27. Regression
28. Continuous variable analyses: t-test, Man Whitney, Wilcoxin rank
29. Categorical variable analyses: Chi-square, fisher exact, Mantel hanzel
30. Analysis of variance
31. Correlation
32. Biases
33. Basic science statistics
34. Sample Size
35. Statistical Software CLINICAL: STUDY TYPES 36. Design principles: Hierarchy of study types
37. Case series: Design, measures, classic example
38. Case-control study: Design, measures, classic example
39. Cohort study: Design, measures, classic example
40. Cross-section study: Design, measures, classic example
41. Longitudinal Study: Design, Measures, Classic Example
42. Meta-analysis: Design, measures, real-world examples
43. Cost-effectiveness study: Design, measures, classic example
44. Diagnostic test evaluation: Design, measures, classic example
45. Reliability study: Design, measures, classic example
46. Database studies
47. Surveys and questionnaires: Design, measures, classic example
48. Qualitative methods and mixed methods
49. Visual analytics: design, measures, classic example CLINICAL TRIALS 50. Randomized control: Design, measures, classic example
51. Nonrandomized control: Design, measures, classic example
52. Historical control: Design, measures, classic example
53. Cross-over: Design, measures, classic example
54. Factorial design: Design, measures, classic example
55. Large, pragmatic: Design, measures, classic example
56. Equivalence and noninferiority: Design, measures, classic example
57. Adaptive: Design, measures, classic example
58. Randomization: Fixed or adaptive procedures
59. Blinding: Who and how?
60. Multicenter considerations
61. Phase 0 Trials: Window of Opportunity
62. Registries
63. Phases of Clinical Trials
64. IDEAL Framework CLINICAL: PREPARATION 65. Patient Perspectives
66. Ethics and review boards
67. Regulatory considerations for new drugs and devices
68. Funding approaches
69. Conflicts of Interest
70. Subject recruitment
71. Data management
72. Quality control
73. Special Populations
74. Report Forms: Harm and Quality of Life
75. Subject adherence
76. Survival analysis REGULATORY BASICS 77. FDA overview
78. IND
79. New drug application
80. Devices
81. Radiation-Emitting Electronic Products
82. Orphan Drugs
83. Biologics
84. Combination Products
85. CMC and GxP
86. Post-Market Drug Safety Monitoring
87. Post-Market Device Safety Monitoring CLINICAL IMPLEMENTATION 88. Implementation Research
89. Design and Analysis
90. Mixed-Methods Research
91. Guideline Development
92. Cooperative Group Research
93. Digital Health PUBLIC HEALTH 94. Public Health
95. Epidemiology
96. Factors
97. Good Questions
98. Population- and Environmental-Specific Considerations
99. Law, Policy, and Ethics
100. Public Health Institutions and Systems
101. DEI (Diversity, equity, inclusion) PRACTICAL RESOURCES102. Ethics in Scientific Publishing
103. Presenting Data
104. Manuscript Preparation
105. Promoting Research
106. Social Media
107. Quality Improvement
108. Education to translate research into practice
109. Team Science and Building a Team
110. Patent Basics
111. Venture Pathways
112. SBIR/STTR
113. Sample Forms and Templates