Translational Surgery covers the principles of evidence-based medicine and applies these principles to the design of translational investigations. The reader will come to fully understand important concepts including case-control studies, prospective cohort studies, randomized trials, and reliability studies. Investigators will benefit from greater confidence in their ability to initiate and execute their own investigations, avoid common pitfalls in surgical research, and know what is needed for collaboration. Further, this title is an indispensable tool in grant writing and funding efforts. The practical, straightforward approach helps the translational research navigate challenging considerations in study design and implementation. The book provides valuable discussions of the critical appraisal of published studies in surgery, allowing the reader to learn how to evaluate the quality of such studies. Thus, they will improve at measuring outcomes; making effective use of all types of evidence in patient care. In short, this practical guidebook will be of interest to every surgeon or surgical researcher who has ever had a good clinical idea, but not the knowledge of how to test it.
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Table of Contents
1. Introduction; 2. Translational Process; 3. Scientific Method; 4. Basic ResearchPre-Clinical 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. Medical 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. Basic Statistical Principles; 23. Distributions; 24. Hypotheses and Error Types; 25. Power; 26. Regression; 27. Continuous Variable Analyses: T-test, Man Whitney, Wilcoxon Rank; 28. Categorical Variable Analyses: Chi-Square, fisher exact, Mantel Hanzel; 29. Analysis of Variance; 30. Correlation; 31. Biases; 32. Basic Science Statistics
Clinical: Study Types 33. Design Principles: Hierarchy of Study Types; 34. Case Series: Design, Measures, Classic Example; 35. Case-Control: Design, Measures, Classic Example; 36. Cohort Study: Design, Measures, Classic Example; 37. Cross-Section Study: Design, Measures, Classic Example; 38. Longitudinal Study: Design, Measures, Classic Example; 39. Clinical Trials: Design, Measures, Classic Example; 40. Meta-Analysis: Design, Measures, Classic Example; 41. Cost-Effectiveness Study: Design, Measures, Classic Example; 42. Diagnostic Test Evaluation: Design, Measures, Classic Example; 43. Reliability Study: Design, Measures, Classic Example; 44. Database Studies: Design, Measures, Classic Example; 45. Surveys and Questionnaires: Design, Measures, Classic Example; 46. Qualitative Methods and Mixed Methods
Clinical Trials 47. Randomized Control: Design, Measures, Classic Example; 48. Nonrandomized Control: Design, Measures, Classic Example; 49. Historical Control: Design, Measures, Classic Example; 50. Cross-Over: Design, Measures, Classic Example; 51. Withdrawal Studies: Design, Measures, Classic Example; 52. Factorial Design: Design, Measures, Classic Example; 53. Group Allocation: Design, Measures, Classic Example; 54. Hybrid 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. Registries; 62. Phases of Clinical Trials; 63. IDEAL Framework; 64. Artificial Intelligence; 65. Patient Perspectives
Clinical: Preparation 66. Sample Size; 67. Budgeting; 68. Medical Ethics and Review Boards; 69. Regulatory Considerations for New Drugs and Devices; 70. Funding Approaches; 71. Subject Recruitment; 72. Data Management; 73. Quality Control; 74. Statistical Software; 75. Report Forms: Harm and Quality of Life; 76. Subject Adherence; 77. Survival Analysis; 78. Monitoring Committee in Clinical Trials
Regulatory Basics 79. FDA Overview; 80. IND; 81. New Drug Application; 82. Devices; 83. Radiation-emitting Electronic Products; 84. Orphan Drugs; 85. Biologics; 86. Combination Products; 87. Foods; 88. Cosmetics; 89. Non-US Regulatory
Clinical Implementation 90. Implementation Research; 91. Design and Analysis; 92. Population and Setting Specific Implementation
Public Health 93. Public Health; 94. Epidemiology; 95. Factors in Surgical Public Health and Health Disparities Research; 96. Good Questions; 97. Population and Environmental Specific Considerations; 98. Law, Policy, and Ethics; 99. Healthcare Institutions and Systems; 100. Public Health Institutions and Systems
Practical Resources 101. Presenting Data; 102. Manuscript Preparation; 103. Building a Team; 104. Patent Basics; 105. Venture Pathways; 106. SBIR/STTR; 107. Sample Forms and Templates
Authors
Adam E.M. Eltorai Harvard Medical School, Boston, MA, USA.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.
