Translational Neurosurgery provides a comprehensive overview reflecting the depth and breadth of the field of translational research focused on neurosurgery, with input from a distinguished team of basic and clinical investigators. It covers the principles of evidence-based medicine and applies these principles to the design of translational investigations, helping researchers navigate challenging considerations in study design and implementation.
This book is a valuable resource for neurosurgeons and neurosurgery investigators who want to understand more about translational research, and also for basic scientists interested in translating their research into clinical practice.
1. Introduction - p. xv 2. Part I. Introduction - p. P1 3. Chapter 1. Translational research and the implementation process - p. 3 4. Chapter 2. Scientific methods: Problems and paradigms - p. 9 5. Part II. Preclinical - p. P2 6. Chapter 3. What problem are you solving? - p. 17 7. Chapter 4. Types of interventions - p. 21 8. Chapter 5. General principles of drug testing - p. 27 9. Chapter 6. Neural network-based neurosurgical device discovery and prototypes - p. 37 10. Chapter 7. Diagnostic method evaluation - p. 43 11. Chapter 8. Artificial intelligence in neurosurgery - p. 53 12. Part III. Statistical principles - p. P3 13. Chapter 9. Basic statistical principles - p. 59 14. Chapter 10. Distributions - p. 69 15. Chapter 11. Hypothesis testing and error - p. 77 16. Chapter 12. Concept of power in statistical testing of hypothesis - p. 83 17. Chapter 13. Continuous variable analyses: t-test, Mann–Whitney U test, and Wilcoxon signed-rank test - p. 87 18. Chapter 14. Categorical variable analyses: Chi-square, Fisher's exact, and Mantel–Haenszel - p. 91 19. Chapter 15. Comparing groups using analysis of variance - p. 95 20. Chapter 16. Correlation - p. 101 21. Chapter 17. Basic science statistics - p. 105 22. Chapter 18. Sample size calculation - p. 107 23. Chapter 19. Getting started with statistical software - p. 111 24. Part IV. Clinical: Study types - p. P4 25. Chapter 20. Outcome measures: The properties and process of measurement - p. 119 26. Chapter 21. Clinical: Study types—Case series: Design, measures, and classic example - p. 127 27. Chapter 22. Case–control studies - p. 135 28. Chapter 23. Cross-sectional study: Design, measures, classic example - p. 139 29. Chapter 24. Approaching longitudinal research to answer clinical questions over time - p. 143 30. Chapter 25. Meta-analysis: design measures, classic example - p. 149 31. Chapter 26. The use of qualitative data and methods - p. 155 32. Part V. Clinical trials - p. P5 33. Chapter 27. Randomization, blinding, and multicentric considerations in clinical trials - p. 161 34. Chapter 28. Nonrandomized control: understanding study design, benefits, and limitation - p. 165 35. Chapter 29. Historical control: Design, measures, classic example - p. 171 36. Chapter 30. Major study types with designs, measures, and examples - p. 175 37. Chapter 31. Blinding: who and how? - p. 197 38. Chapter 32. Adaptive design, measures, and classic examples - p. 201 39. Chapter 33. Phase zero clinical trials - p. 207 40. Chapter 34. Clinical trial registries, phases of clinical trials, IDEAL framework - p. 213 41. Part VI. Regulatory basics - p. P6 42. Chapter 35. FDA overview—What the FDA does. FDA branches and divisions. Is your product regulated? - p. 221 43. Chapter 36. The Investigatory New Drug application - p. 225 44. Chapter 37. Investigational device exemption (IDE) - p. 229 45. Chapter 38. Dedicated radiosurgery device development - p. 235 46. Chapter 39. An introduction to FDA approval for biologics - p. 241 47. Chapter 40. Combination products - p. 245 48. Chapter 41. A brief overview of the FDA's involvement in the regulation of dietary supplements - p. 249 49. Chapter 42. Cosmetics - p. 253 50. Chapter 43. Chemistry, manufacturing, and controls and good “x” practices - p. 259 51. Chapter 44. Non-US regulatory - p. 263 52. Chapter 45. Postmarket drug monitoring - p. 269 53. Chapter 46. Postmarket device safety monitoring - p. 273 54. Part VII. Public health - p. P7 55. Chapter 47. Public health - p. 279 56. Chapter 48. Applying epidemiological methods to translational neurosurgery research - p. 283 57. Chapter 49. Factors—Determinants of health - p. 287 58. Chapter 50. Asking the right public health research questions - p. 291 59. Chapter 51. Population- and environmental-specific considerations - p. 295 60. Chapter 52. Public health and health systems - p. 301 61. Chapter 53. Public health institutions and systems - p. 307 62. Chapter 54. Principles of persuasive data presentation - p. 311 63. Glossary - p. 321 64. Index - p. 329
Translational Neurosurgery provides a comprehensive overview reflecting the depth and breadth of the field of translational research focused on neurosurgery, with input from a distinguished team of basic and clinical investigators. It covers the principles of evidence-based medicine and applies these principles to the design of translational investigations, helping researchers navigate challenging considerations in study design and implementation.
This book is a valuable resource for neurosurgeons and neurosurgery investigators who want to understand more about translational research, and also for basic scientists interested in translating their research into clinical practice.
1. Introduction - p. xv 2. Part I. Introduction - p. P1 3. Chapter 1. Translational research and the implementation process - p. 3 4. Chapter 2. Scientific methods: Problems and paradigms - p. 9 5. Part II. Preclinical - p. P2 6. Chapter 3. What problem are you solving? - p. 17 7. Chapter 4. Types of interventions - p. 21 8. Chapter 5. General principles of drug testing - p. 27 9. Chapter 6. Neural network-based neurosurgical device discovery and prototypes - p. 37 10. Chapter 7. Diagnostic method evaluation - p. 43 11. Chapter 8. Artificial intelligence in neurosurgery - p. 53 12. Part III. Statistical principles - p. P3 13. Chapter 9. Basic statistical principles - p. 59 14. Chapter 10. Distributions - p. 69 15. Chapter 11. Hypothesis testing and error - p. 77 16. Chapter 12. Concept of power in statistical testing of hypothesis - p. 83 17. Chapter 13. Continuous variable analyses: t-test, Mann–Whitney U test, and Wilcoxon signed-rank test - p. 87 18. Chapter 14. Categorical variable analyses: Chi-square, Fisher's exact, and Mantel–Haenszel - p. 91 19. Chapter 15. Comparing groups using analysis of variance - p. 95 20. Chapter 16. Correlation - p. 101 21. Chapter 17. Basic science statistics - p. 105 22. Chapter 18. Sample size calculation - p. 107 23. Chapter 19. Getting started with statistical software - p. 111 24. Part IV. Clinical: Study types - p. P4 25. Chapter 20. Outcome measures: The properties and process of measurement - p. 119 26. Chapter 21. Clinical: Study types—Case series: Design, measures, and classic example - p. 127 27. Chapter 22. Case–control studies - p. 135 28. Chapter 23. Cross-sectional study: Design, measures, classic example - p. 139 29. Chapter 24. Approaching longitudinal research to answer clinical questions over time - p. 143 30. Chapter 25. Meta-analysis: design measures, classic example - p. 149 31. Chapter 26. The use of qualitative data and methods - p. 155 32. Part V. Clinical trials - p. P5 33. Chapter 27. Randomization, blinding, and multicentric considerations in clinical trials - p. 161 34. Chapter 28. Nonrandomized control: understanding study design, benefits, and limitation - p. 165 35. Chapter 29. Historical control: Design, measures, classic example - p. 171 36. Chapter 30. Major study types with designs, measures, and examples - p. 175 37. Chapter 31. Blinding: who and how? - p. 197 38. Chapter 32. Adaptive design, measures, and classic examples - p. 201 39. Chapter 33. Phase zero clinical trials - p. 207 40. Chapter 34. Clinical trial registries, phases of clinical trials, IDEAL framework - p. 213 41. Part VI. Regulatory basics - p. P6 42. Chapter 35. FDA overview—What the FDA does. FDA branches and divisions. Is your product regulated? - p. 221 43. Chapter 36. The Investigatory New Drug application - p. 225 44. Chapter 37. Investigational device exemption (IDE) - p. 229 45. Chapter 38. Dedicated radiosurgery device development - p. 235 46. Chapter 39. An introduction to FDA approval for biologics - p. 241 47. Chapter 40. Combination products - p. 245 48. Chapter 41. A brief overview of the FDA's involvement in the regulation of dietary supplements - p. 249 49. Chapter 42. Cosmetics - p. 253 50. Chapter 43. Chemistry, manufacturing, and controls and good “x” practices - p. 259 51. Chapter 44. Non-US regulatory - p. 263 52. Chapter 45. Postmarket drug monitoring - p. 269 53. Chapter 46. Postmarket device safety monitoring - p. 273 54. Part VII. Public health - p. P7 55. Chapter 47. Public health - p. 279 56. Chapter 48. Applying epidemiological methods to translational neurosurgery research - p. 283 57. Chapter 49. Factors—Determinants of health - p. 287 58. Chapter 50. Asking the right public health research questions - p. 291 59. Chapter 51. Population- and environmental-specific considerations - p. 295 60. Chapter 52. Public health and health systems - p. 301 61. Chapter 53. Public health institutions and systems - p. 307 62. Chapter 54. Principles of persuasive data presentation - p. 311 63. Glossary - p. 321 64. Index - p. 329
