Translational Plastic Surgery (Handbook for Designing and Conducting Clinical and Translational Research)

個数：

予約

Translational Plastic Surgery (Handbook for Designing and Conducting Clinical and Translational Research)

Eltorai, Adam E.M. (EDT)/ Bakal, Jeffrey A. (EDT)/ Liu, Paul (EDT)

ウェブストア価格 ¥34,614（本体¥31,468）
Academic Press Inc（2026/01発売）
外貨定価 US$ 165.00
ポイント 314pt

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製本 Paperback:紙装版/ペーパーバック版／ページ数 780 p.
言語 ENG
商品コード 9780323911689

Full Description

Translational Plastic Surgery provides a comprehensive overview reflecting the depth and breadth of the field of translational research focused on plastic surgery, with input from a distinguished team of basic and clinical investigators. The practical, straightforward approach helps the aspiring investigator navigate challenging considerations in study design and implementation. The book provides valuable discussions of the critical appraisal of published studies in translational plastic surgery research, allowing the reader to learn how to evaluate the quality of such studies with respect to measuring outcomes and to make effective use of all.

INTRODUCTION
1. Introduction
2. Translational Process
3. Scientific Method
4. Basic research

PRE-CLINCIAL
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. Other product types
15. Procedural technique development
16. Behavioral intervention

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

STATISTICAL PRINCIPLES
22. Common issues in analysis
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

CLINICAL: STUDY TYPES
34. Design principles: Hierarchy of study types
35. Case series: Design, measures, classic example
36. Case-control study: Design, measures, classic example
37. Cohort study: Design, measures, classic example
38. Cross-section study: Design, measures, classic example
39. Longitudinal study: Design, measures, classic example
40. Clinical trials: Design, measures, classic example
41. Meta-analysis: Design, measures, classic example
42. Cost-effectiveness study: Design, measures, classic example
43. Diagnostic test evaluation: Design, measures, classic example
44. Reliability study: Design, measures, classic example
45. Database studies: Design, measures, classic example
46. Surveys and questionnaires: Design, measures, classic example
47. Qualitative methods and mixed methods

CLINICAL TRIALS
48. Randomized control: Design, measures, classic example
49. Nonrandomized control: Design, measures, classic example
50. Historical control: Design, measures, classic example
51. Cross-over: Design, measures, classic example
52. Withdrawal studies: Design, measures, classic example
53. Factorial design: Design, measures, classic example
54. Group allocation: Design, measures, classic example
55. Hybrid design: Design, measures, classic example
56. Large, pragmatic: Design, measures, classic example
57. Equivalence and noninferiority: Design, measures, classic example
58. Adaptive: Design, measures, classic example
59. Randomization: Fixed or adaptive procedures
60. Blinding: Who and how?
61. Multicenter considerations
62. Registries
63. Phases of clinical trials
64. IDEAL Framework
65. Artificial Intelligence
66. Patient perspectives

CLINICAL: PREPARATION
67. Sample size
68. Budgeting
69. Ethics and review boards
70. Regulatory considerations for new drugs and devices
71. Funding approaches
72. Subject recruitment
73. Data management
74. Quality control
75. Statistical software
76. Report forms: Harm and Quality of Life
77. Subject adherence
78. Survival analysis
79. Monitoring committee in clinical trials

REGULATORY BASICS
80. FDA overview
81. IND
82. New drug application
83. Devices
84. Radiation-emitting electronic products
85. Orphan drugs
86. Biologics
87. Combination products
88. Foods
89. Cosmetics
90. CMC and GxP
91. Non-US regulatory
92. Post-Market Drug Safety Monitoring
93. Post-Market Device Safety Monitoring

CLINICAL IMPLEMENTATION
94. Implementation Research
95. Design and analysis
96. Mixed-methods research
97. Population- and setting-specific implementation

PUBLIC HEALTH
98. Public Health
99. Epidemiology
100. Factors
101. Good questions
102. Population- and environmental-specific considerations
103. Law, policy, and ethics
104. Healthcare institutions and systems
105. Public health institutions and systems
106. Presenting data
107. Manuscript preparation
108. Building a team
109. Patent basics
110. Venture pathways
111. SBIR/STTR
112. Sample forms and templates