Translational Surgery
Published on 23. March 2023
Book
Paperback/Softback
768 pages
978-0-323-90300-4 (ISBN)
Description
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.
More details
Series
Language
English
Place of publication
Oxford
United Kingdom
Publishing group
Elsevier Science & Technology
Target group
Professional and scholarly
Illustrations
Approx. 100 illustrations (100 in full color); Illustrations
Dimensions
Height: 276 mm
Width: 216 mm
Weight
2130 gr
ISBN-13
978-0-323-90300-4 (9780323903004)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Persons
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.
Dr Jeff Bakal PhD, P.Stat. 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 and Health Service Statistical & Analytics Methods teams. He has over 10 years of experience working with Health Services data and Randomized Clinical Trials. He completed his PhD jointly with the Department of Mathematics and Statistics and the School of Physical Health and Education at Queen's University. He has worked on the methodology and analysis of several international studies in business strategy, ophthalmology, cardiology, geriatric medicine and the analysis of kinematic data resulting in several peer reviewed articles and conference presentations. His current interests are in developing statistical methodology for time-to-event data and the development of classification tools to assist in patient decision making processes. Paige Newell MD received her Bachelor of Arts in History of Art and Architecture from Harvard University, and subsequently received her Doctor of Medicine from Lewis Katz School of Medicine at Temple University. She started general surgery residency at Brigham and Women's Hospital in Boston, MA in 2018, and spent her two years of dedicated research time from June 2020 - June 2022 as the Vicky and Joseph Safra Cardiac Surgery Clinical Outcomes Research Fellow within the Division of Cardiac Surgery at Brigham and Women's Hospital and as a research fellow for the Center for Surgery and Public Health. Her research interests include socioeconomic disparities in cardiac surgery outcomes and barriers to access to high quality care. After completing general surgery residency she plans to complete a fellowship in cardiothoracic surgery. Adena Osband, MD is a graduate of the University of Pennsylvania and New Jersey Medical School. She is currently a transplant surgeon and director of the living donor program at Rhode Island Hospital, with over 15 years in practice. She also holds the positions of associate professor of surgery and director of surgical intern education at the Warren Alpert Medical School of Brown University.
Dr Jeff Bakal PhD, P.Stat. 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 and Health Service Statistical & Analytics Methods teams. He has over 10 years of experience working with Health Services data and Randomized Clinical Trials. He completed his PhD jointly with the Department of Mathematics and Statistics and the School of Physical Health and Education at Queen's University. He has worked on the methodology and analysis of several international studies in business strategy, ophthalmology, cardiology, geriatric medicine and the analysis of kinematic data resulting in several peer reviewed articles and conference presentations. His current interests are in developing statistical methodology for time-to-event data and the development of classification tools to assist in patient decision making processes. Paige Newell MD received her Bachelor of Arts in History of Art and Architecture from Harvard University, and subsequently received her Doctor of Medicine from Lewis Katz School of Medicine at Temple University. She started general surgery residency at Brigham and Women's Hospital in Boston, MA in 2018, and spent her two years of dedicated research time from June 2020 - June 2022 as the Vicky and Joseph Safra Cardiac Surgery Clinical Outcomes Research Fellow within the Division of Cardiac Surgery at Brigham and Women's Hospital and as a research fellow for the Center for Surgery and Public Health. Her research interests include socioeconomic disparities in cardiac surgery outcomes and barriers to access to high quality care. After completing general surgery residency she plans to complete a fellowship in cardiothoracic surgery. Adena Osband, MD is a graduate of the University of Pennsylvania and New Jersey Medical School. She is currently a transplant surgeon and director of the living donor program at Rhode Island Hospital, with over 15 years in practice. She also holds the positions of associate professor of surgery and director of surgical intern education at the Warren Alpert Medical School of Brown University.
Editor
Harvard Medical School, Boston, MA, USA
Volume editor
Division General Internal Medicine, Faculty of Medicine and Dentistry, University of Alberta, Edmonton Alberta, Canada
Brigham and Women's Hospital, Boston, MA, USA
Department of Surgery, Warren Alpert Medical School of Brown University, Providence, RI, USA
Content
1. Introduction; 2. Translational Process; 3. Scientific Method; 4. Basic Research
Pre-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
Pre-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