book

Clinical Graphs Using SAS

Name: Clinical Graphs Using SAS
Author: Sanjay Matange
ISBN: 9781629602059

by Sanjay Matange

March 2016

Intermediate to advanced

270 pages

6h 26m

English

SAS Institute

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About This Book
About The Author
Acknowledgements
Preface
Chapter 1: Introduction to ODS Graphics
1.1 A Brief History of ODS Graphics1.2 Automatic Graphs from SAS Analytical Procedures1.3 Create Custom Graphs Using the Graph Template Language (GTL)1.4 Create Custom Graphs Using the Statistical Graphics (SG) Procedures1.5 Create Custom Graphs Using the ODS Graphics Designer Application1.6 Data Sets and ODS Styles1.7 Color and Grayscale Graphs1.8 Summary
Chapter 2: A Brief Overview of the SG Procedures
2.1 Single-Cell Graph Using the SGPLOT Procedure2.2 Multi-Cell Classification Panels Using the SGPANEL Procedure2.3 Multi-Cell Comparative Scatter Plots Using the SGCATTER Procedure2.4 Automatic Features2.5 The SGPLOT Procedure2.5.1 Required Roles2.5.2 Optional Data Roles2.5.3 Plot Options2.6 Plot Layering2.7 SGPANEL Procedure2.7.1 Layout PANEL2.7.2 Layout LATTICE2.7.3 Layout COLUMNLATTICE2.7.4 Layout ROWLATTICE2.8 Combining Statements2.9 Annotation2.10 Styles and Their Usage2.11 Summary
Chapter 3: Clinical Graphs Using the SAS 9.3 SGPLOT Procedure
3.1 Box Plot of QTc Change from Baseline3.1.1 Box Plot of QTc Change from Baseline with Outer Risk Table3.1.2 Box Plot of QTc Change from Baseline with Inner Risk Table3.1.3 Box Plot of QTc Change from Baseline in Grayscale3.2 Mean Change in QTc by Week and Treatment3.2.1 Mean Change of QTc by Week and Treatment with Outer Table3.2.2 Mean Change of QTc by Week and Treatment with Inner Table3.2.3 Mean Change in QTc by Visit in Grayscale3.3 Distribution of ASAT by Time and Treatment3.4 Median of Lipid Profile by Visit and Treatment3.4.1 Median of Lipid Profile by Visit and Treatment on Discrete Axis3.4.2 Median of Lipid Profile by Visit and Treatment on Linear Axis in Grayscale3.5 Survival Plot3.5.1 Survival Plot with External "Subjects At-Risk" Table3.5.2 Survival Plot with Internal "Subjects At-Risk" Table3.5.3 Survival Plot with Internal "Subjects At-Risk" Table in Grayscale3.6 Simple Forest Plot3.6.1 Simple Forest Plot3.6.2 Simple Forest Plot with Study Weights3.6.3 Simple Forest Plot with Study Weights in Grayscale3.7 Subgrouped Forest Plot3.8 Adverse Event Timeline by Severity3.9 Change in Tumor Size3.10 Injection Site Reaction3.11 Distribution of Maximum LFT by Treatment3.11.1 Distribution of Maximum LFT by Treatment with Multi-Column Data3.11.2 Distribution of Maximum LFT by Treatment Grayscale with Group Data3.12 Clark Error Grid3.12.1 Clark Error Grid3.12.2 Clark Error Grid in Grayscale3.13 The Swimmer Plot3.13.1 The Swimmer Plot for Tumor Response over Time3.13.2 The Swimmer Plot for Tumor Response in Grayscale3.14 CDC Chart for Length and Weight Percentiles3.15 Summary
Chapter 4: Clinical Graphs Using the SAS 9.4 SGPLOT Procedure
4.1 Box Plot of QTc Change from Baseline4.1.1 Box Plot of QTc Change from Baseline4.1.2 Box Plot of QTc Change from Baseline with Inner Risk Table and Bands4.1.3 Box Plot of QTc Change from Baseline in Grayscale4.2 Mean Change in QTc by Visit and Treatment4.2.1 Mean Change in QTc by Visit and Treatment4.2.2 Mean Change in QTc by Visit and Treatment with Inner Table of Subjects4.2.3 Mean Change in QTc by Visit and Treatment in Grayscale4.3 Distribution of ASAT by Time and Treatment4.3.1 Distribution of ASAT by Time and Treatment4.3.2 Distribution of ASAT by Time and Treatment in Grayscale4.4 Median of Lipid Profile by Visit and Treatment4.4.1 Median of Lipid Profile by Visit and Treatment on Discrete Axis4.4.2 Median of Lipid Profile by Visit and Treatment on Linear Axis in Grayscale4.5 Survival Plot4.5.1 Survival Plot with External "Subjects At-Risk" Table4.5.2 Survival Plot with Internal "Subjects At-Risk" Table4.5.3 Survival Plot with Internal "Subjects At-Risk" Table in Grayscale4.6 Simple Forest Plot4.6.1 Simple Forest Plot4.6.2 Simple Forest Plot with Study Weights4.6.3 Simple Forest Plot with Study Weights in Grayscale4.7 Subgrouped Forest Plot4.8 Adverse Event Timeline by Severity4.9 Change in Tumor Size4.10 Injection Site Reaction4.10.1 Injection Site Reaction4.10.2 Injection Site Reaction in Grayscale4.11 Distribution of Maximum LFT by Treatment4.11.1 Distribution of Maximum LFT by Treatment with Multi-Column Data4.11.2 Distribution of Maximum LFT by Treatment Grayscale with Group Data4.12 Clark Error Grid4.12.1 Clark Error Grid4.12.2 Clark Error Grid in Grayscale4.13 The Swimmer Plot4.13.1 The Swimmer Plot for Tumor Response over Time4.13.2 The Swimmer Plot for Tumor Response over Time in Grayscale4.14 CDC Chart for Length and Weight Percentiles4.15 Summary
Chapter 5: Clinical Graphs Using the SGPANEL Procedure
5.1 Panel of LFT Shifts from Baseline to Maximum by Treatment5.1.1 Panel of LFT Shifts with Common Clinical Concern Levels5.1.2 Panel of LFT Shifts with Individual Clinical Concern Levels5.2 Immunology Profile by Treatment5.2.1 Immunology Panel5.2.2 Immunology Panel in Grayscale5.3 LFT Safety Panel, Baseline vs Study5.3.1 LFT Safety Panel, Baseline vs Study5.3.2 LFT Safety Panel, Baseline vs Study5.4 Lab Test Panel5.4.1 Lab Test Panel with Clinical Concern Limits5.4.2 Lab Test Panel with Box Plot, Band, and Inset Line Name5.5 Lab Test for Patient over Time5.5.1 Lab Test Values by Subject over Study Days5.5.2 Lab Test Values by Subject with Study Days Band5.6 Vital Statistics for Patient over Time5.6.1 Vital Statistics for Patient over Time5.6.2 Vital Statistics for Patient over Time5.7 Eye Irritation over Time by Severity and Treatment5.7.1 Eye Irritation over Time by Severity and Treatment5.7.2 Vital Statistics for Patient over Time in Grayscale5.8 Summary
Chapter 6: A Brief Review of the Graph Template Language
6.1 Getting Started6.2 A Simple GTL Graph6.3 GTL Graphs and Terminology6.4 GTL Plot Statements6.4.1 Basic Plots6.4.2 Categorical Plots6.4.3 Distribution Plots6.4.4 Fit Plots6.4.5 Parametric Plots6.4.6 3-D Plots6.4.7 Other Plots6.5 GTL Layout Statements6.5.1 The Graph Container6.5.2 Single-Cell Layouts6.5.3 Multi-cell Ad Hoc Layouts6.5.4 Multi-Cell Classification Panels6.6 GTL Title, Footnote, and Entry Statements6.7 GTL Legend Statements6.8 GTL Attribute Maps6.9 GTL Dynamic Variables and Macro Variables6.10 GTL Expressions and Conditionals6.11 GTL Draw Statements6.12 GTL Annotate6.13 Summary

Chapter 7: Clinical Graphs Using SAS 9.3 GTL
7.1 Distribution of ASAT by Time and Treatment7.2 Most Frequent On-Therapy Adverse Events Sorted by Relative Risk7.3 Treatment Emergent Adverse Events with Largest Risk Difference with NNT7.4 Butterfly Plot of Cancer Deaths by Cause and Gender7.5 Forest Plot of Impact of Treatment on Mortality by Study7.6 Forest Plot of Hazard Ratios by Patient Subgroups7.7 Product-Limit Survival Estimates7.8 Bivariate Distribution Plot7.9 Summary
Chapter 8: Clinical Graphs Using SAS 9.4 GTL
8.1 Distribution of ASAT by Time and Treatment8.2 Most Frequent On-Therapy Adverse Events Sorted by Relative Risk8.3 Treatment Emergent Adverse Events with Largest Risk Difference with NNT8.4 Butterfly Plot of Cancer Deaths by Cause and Gender8.5 Forest Plot of Impact of Treatment on Mortality by Study8.6 Forest Plot of Hazard Ratios by Patient Subgroups8.7 Product-Limit Survival Estimates8.8 Bivariate Distribution Plot8.9 Summary
Index

Overview

SAS users in the Health and Life Sciences industry need to create complex graphs to analyze biostatistics data and clinical data, and they need to submit drugs for approval to the FDA. Graphs used in the HLS industry are complex in nature and require innovative usage of the graphics features. Clinical Graphs Using SAS® provides the knowledge, the code, and real-world examples that enable you to create common clinical graphs using SAS graphics tools, such as the Statistical Graphics procedures and the Graph Template Language.

This book describes detailed processes to create many commonly used graphs in the Health and Life Sciences industry. For SAS® 9.3 and SAS® 9.4 it covers many improvements in the graphics features that are supported by the Statistical Graphics procedures and the Graph Template Language, many of which are a direct result of the needs of the Health and Life Sciences community. With the addition of new features in SAS® 9.4, these graphs become positively easy to create.

Topics covered include the usage of SGPLOT procedure, the SGPANEL procedure and the Graph Template Language for the creation of graphs like forest plots, swimmer plots, and survival plots.

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