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Create industry-compliant graphs with this practical guide for professionals

Analysis of clinical trial results is easier when the data is presented in a visual form. However, clinical graphs must conform to specific guidelines in order to satisfy regulatory agency requirements. If you are a programmer working in the health care and life sciences industry and you want to create straightforward, visually appealing graphs using SAS, then this book is designed specifically for you. Written by two experienced practitioners, the book explains why certain graphs are requested, gives the necessary code to create the graphs, and shows you how to create graphs from ADaM data sets modeled on real-world CDISC pilot study data.

SAS Graphics for Clinical Trials by Example demonstrates step-by-step how to create both simple and complex graphs using Graph Template Language (GTL) and statistical graphics procedures, including the SGPLOT and SGPANEL procedures. You will learn how to generate commonly used plots such as Kaplan-Meier plots and multi-cell survival plots as well as special purpose graphs such as Venn diagrams and interactive graphs. Because your graph is only as good as the aesthetic appearance of the output, you will learn how to create a custom style, change attributes, and set output options. Whether you are just learning how to produce graphs or have been working with graphs for a while, this book is a must-have resource to solve even the most challenging clinical graph problems.

Table of Contents

  1. About This Book
  2. About These Authors
  3. Acknowledgments
  4. Chapter 1: Introduction to Clinical Graphics
  5. 1.1 Introduction to Output Delivery System Statistical Graphics
    1. 1.1.1 Understanding the Basic: Statistical Graphics Procedures
    2. 1.1.1.1 Overview of the SGPLOT Procedure
    3. 1.1.1.2 Overview of the SGPANEL Procedure
    4. 1.1.1.3 Overview of the SGSCATTER Procedure
    5. 1.1.2 Understanding the Basics: Graph Template Language
    6. 1.1.2.1 Draw Spaces for a Graph
    7. 1.1.2.2 Layouts for GTL
    8. 1.1.2.3 General Syntax for GTL
    9. 1.1.2.4 General Syntax for Layouts
    10. 1.1.2.5 Syntax for LATTICE Layout
  6. 1.2 Reason Why Clinical Graphs Are Needed and What They Should Convey
  7. 1.3 Chapter Summary
  8. References
  9. Chapter 2: Using SAS to Generate Graphs for Adverse Events
  10. 2.1 Introduction to Adverse Events
  11. 2.2 Reports for Adverse Events
  12. 2.3 Adverse Events MedDRA Coding
  13. 2.4 Toxicity Grade for Adverse Events
  14. 2.5 Report for Maximum Grade 1 Adverse Events by Treatment Group
    1. 2.5.1 Illustrating Snippet of Adverse Event Data
    2. 2.5.2 Producing Frequency Plot of Adverse Events for Each System Organ Class
    3. 2.5.3 Producing Frequency Plot of Treatment-Related Adverse Events by System Organ Class
    4. 2.5.4 Producing Plot for Both Adverse Events and Treatment-Related Adverse Events by System Organ Class
    5. 2.5.5 Producing Frequency Plot of Adverse Events Grouped by Maximum Grade for Each System Organ Class
  15. 2.6 Report for Time to Adverse Events by Treatment Group
    1. 2.6.1 Illustrating Snippet of Time to Event Analysis Data Set
    2. 2.6.2 Controlling the PROC LIFETEST Kaplan Meier Plot
    3. 2.6.2.1 Controlling the Kaplan Meier Plot by Specifying Procedure Options
    4. 2.6.2.2 Controlling the Kaplan Meier Plot by Modifying Graph Templates Using Macros
    5. 2.6.2.3 Controlling the Kaplan Meier Plot by Directly Modifying Graph Templates
  16. 2.7 Treatment Risk Difference for Adverse Events
  17. 2.8 Adverse Event Profile Plot
  18. 2.9 Chapter Summary
  19. References
  20. Chapter 3: Using SAS to Generate Graphs for Data Collected Over Time
  21. 3.1 Introduction on Findings Data
  22. 3.2 Laboratory Values Over Time for Each Laboratory Parameter
    1. 3.2.1 Illustrating a Snippet of Laboratory Data
    2. 3.2.2 Illustrating Summary Statistics Over Time Represented in Tabular Form
    3. 3.2.3 Illustrating Summary Statistics Over Time Represented in a Graph
  23. 3.3 Individual Patient Changes
  24. 3.4 Mean Change from Baseline Over Time
  25. 3.5 Laboratory Values Shift from Baseline to Post-Baseline Plot
    1. 3.5.1 Illustrating Shift from Baseline to Maximum Post-Baseline Normal Range Indicator in Tabular Form
    2. 3.5.2 Illustrating Shift from Baseline to Maximum Post-Baseline Result in Tabular Form
  26. 3.6 Chapter Summary
  27. References
  28. Chapter 4: Using SAS to Generate Graphs for Exposure and Patient Disposition
  29. 4.1 Introduction to the Napoleon Plot/Swimmer Plot
  30. 4.2 Creating a Napoleon Plot/Swimmer Plot
    1. 4.2.1 Creating the Bar Charts and Dose Legend
    2. 4.2.2 Creating Reason for Treatment Discontinuation Markers and Legend
    3. 4.2.3 Adding Reason for Treatment Discontinuation Initial to the Plot
    4. 4.2.4 Adding Cohort information to the Plot
  31. 4.3 Creating a Napoleon Plot for Many Patients That Highlights Dose Interruptions
  32. 4.4 Chapter Summary
  33. References
  34. Chapter 5: Using SAS to Generate Graphs for Time-to-Event Endpoints
  35. 5.1 Introduction to Time-to-Event Endpoints
    1. 5.1.1 Using ODS Output Objects for Time-to-Event Endpoints
    2. 5.1.2 Understanding Overall Survival Endpoint
    3. 5.1.3 Understanding Progression-Free Survival Endpoint
    4. 5.1.4 Understanding the Usefulness of Kaplan-Meier Plots
  36. 5.2 Survival Curves for Time-to-Event Endpoints
    1. 5.2.1 Generating a Survival Plot with SGPLOT
    2. 5.2.2 Generating Single-Cell Survival Plot with Graph Template Language
    3. 5.2.3 Generating Multi-Cell Survival Plots with Graph Template Language
    4. 5.2.3.1 Generating Survival Plot with Median Survival Next to the Survival Curve
    5. 5.2.3.2 Generating Survival Plot with Median Survival and Event Statistics Table
    6. 5.2.3.3 Generating Survival Plots for Subgroup Analysis
  37. 5.3 Forest Plots from Overall Survival Hazard Ratios
    1. 5.3.1 Generating Forest Plot that Exhibit Number of Observations
    2. 5.3.2 Generating Multiple Forest Plots that Exhibit Number of Observations
  38. 5.4 Chapter Summary
  39. References
  40. Chapter 6: Using SAS to Generate Graphs for Tumor Response
  41. 6.1 Introduction on Tumor Response
  42. 6.2 Assessment of Tumor Burden
  43. 6.3 Measurement of Longest Diameter Over Time Per Patient
  44. 6.4 Waterfall Plot of Best Overall Response with Best Percentage Change in Tumor Burden
  45. 6.5 Spider Plot of Percentage Change from Baseline for Each Patient Over Time
  46. 6.6 Swimmer Plot for Overall Response During Course of Study
  47. 6.7 Other Types of Plots for Oncology Data
  48. 6.8 Chapter Summary
  49. References
  50. Chapter 7: Using SAS to Generate Special Purpose Graphs
  51. 7.1 Introduction to Special Purpose Graphs
  52. 7.2 Interactive Graphs
    1. 7.2.1 Illustrating Adverse Event Drill Down
    2. 7.2.1.1 Producing Graphs of Adverse Event Counts for each Treatment and Severity Group
    3. 7.2.1.2 Producing Main Interactive Bar Chart
    4. 7.2.1.3 Creating a Drop-Down Selection Menu
  53. 7.3 Venn Diagrams
    1. 7.3.1 Creating a Two-Way Venn Diagram
    2. 7.3.2 Creating a Three-Way Venn Diagram
    3. 7.3.3 Creating a Four-Way Venn Diagram
  54. 7.4 Chapter Summary
  55. References
  56. Appendix
    1. JavaScript
    2. CSS
  57. Chapter 8: Building the Seemingly Impossible
  58. 8.1 Introduction to Patient Profile Plot
    1. 8.1.1 Walking Through a Diabetic Patient Profile Plot
    2. 8.1.1.1 Creation of Data Set with All Necessary Data to Build a Diabetic Patient Profile Plot
    3. 8.1.1.2 Creation of Series Plots for Glucose and HbA1c Lab Results
    4. 8.1.1.3 Creation of Scatter Plot for Hypoglycemic and Hyperglycemic Events
    5. 8.1.1.4 Creation of Highlow Plot for Duration of Medication by Type of Medication
    6. 8.1.1.5 Creation of Diabetic Patient Profile Plot
    7. 8.1.2 Using An Alternate Approach to Producing the Profile Plot
  59. 8.2 Chapter Summary
  60. References
  61. Chapter 9: Selecting the Ideal Style, Output Format, and Graphical Options
  62. 9.1 Introduction to Styles, Output Format, and Graphical Options
  63. 9.2 Custom Styles
    1. 9.2.1 Creating a Custom Style
    2. 9.2.1.1 Data Snippet of Subject Level Data Used to Illustrate Styles
    3. 9.2.1.2 CustomSapphire Style with No Modifications
    4. 9.2.1.3 Modified CustomSapphire Style
    5. 9.2.2 Saving the Custom Style Template
  64. 9.3 Output Delivery System Destination and Image Format
    1. 9.3.1 Selecting the Output Delivery System Destination
    2. 9.3.2 Selecting the Image Format
  65. 9.4 Options for Specific Types of Documents
    1. 9.4.1 Setting Options for Documents Used for Presentations
    2. 9.4.1.1 Survival Plot Using Default Dimensions and DPI of 300
    3. 9.4.1.2 Survival Plot Using Smaller Dimensions and DPI of 300
    4. 9.4.1.3 Survival Plot Using Smaller Dimensions, DPI of 300, and Custom Style
    5. 9.4.1.4 Using ODS PowerPoint to Output Graphs Directly into PowerPoint
    6. 9.4.2 Setting Options for Documents Used for Publications
    7. 9.4.3 Setting Options for Documents Used for Medical Writer
  66. 9.5 Options for Different Countries
  67. 9.6 Chapter Summary
  68. References
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