Module I: Clinical Trials a Practical Guide to Design, Analysis, and Reporting 1. Fundamentals of Trial Design
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1 Module I: Clinical Trials a Practical Guide to Design, Analysis, and Reporting 1. Fundamentals of Trial Design Randomized the Clinical Trails About the Uncontrolled Trails The protocol Development The Endpoints Patient Selection The Source and the Control of Bias Randomization Blinding The Sample Sizes and Powers 2. Alternative Trial Designs What are Crossover Trails? The Factorial Designs Equivalence Trails About the Bioequivalence Trails Non-inferiority Trails The Cluster Randomized Trails Multicenter Trails 3. Basics of Statistical Analysis The Types of data and the Normal Distribution The Significance Tests and Confidence intervals The Comparison Means The Comparison of the Proportions Analysis of the Survival Data
2 4. Special Trial Issues in Data Analysis Analysis: Intention-to-Treat Analysis of the Subgroups Regression Analysis Adjustment for the Covariates About Confounding Interaction About the Repeated Measurements The Multiplicity The Missing Data What are Interim Monitoring and Stopping Rules? 5. Reporting of Trials An Overview of the Reporting What is Trail Profile? Presenting the Baseline Data Use of the Tables Use of the Figures The Critical Appraisal of a Report About Meta-Analysis Module II: SAS Programming in the Pharmaceutical Industry 1 Environment and Guiding Principles A) The Statistical Programmer s Working Environment Pharmaceutical Industry Vocabulary Statistical Programmer Work Description B) The Drug/Device Development Process Industry Regulations and Standards Your Clinical Trial Colleagues C) Guiding Principles for the Statistical Programmer Understanding of the Clinical Study
3 Programming of a Task Once and Reuse the Code Everywhere Do the Clinical Trial Data Are Dirty? How to Use SAS Macros Judiciously? A Good Programmer Is a Good Student The Strive to Make Your Programming Readable 2 Preparing and Classifying Clinical Trail Data A) Preparing a Clinical Trail Data Cleaning of the Data, if Necessary, for the Analysis Categorizing the Data According to the Necesity Avoid the Hardcoding data B) Classification of the Clinical Data Trail-Specific Baseline Data and the Demographics Concomitant or the Prior Medication Data About the Medical History Data What is the Investigational Therapy Drug Log? The Laboratory Data About the Adverse Event Data Endpoint/Event Assessment Data What is Clinical Endpoint Committee (CEC) Data? The Study Termination Data Treatment Randomization Data Quality-of-Life Data 3 Importing Data A) Importing the Rational databases and the Clinical data Management Systems SAS/ACCESS, SQL Pass-Through the Facilities SAS/ACCESS, LIBNAME Statement B) Importing the ASC II Text The PROC IMPORT and the Import Wizard About the SAS Data Step The SAS Enterprise Guide
4 C) Importing The Microsoft Office Files What is the LIBNAME Statement? Importing Wizard and the PROC IMPORT About the SAS/ACCESS, SQL Pass-through Facility The SAS Enterprise Guide D) Importing the XML XML LIBNAME Engine SAS XML Mapper E) Import the CDISC Model Content Files Importing the CDISC SAS Transport Format Files How to Import the Define.xml? Import the CDISC ODM Files 4 Transforming Data and Creating Analysis A) The Key Concepts for Creating the Analysis Data Sets Defining the variables once Describe the Populations Describing the Baseline Observations About LOCF (Last Observation Carried Forward) Define the Study day The Windowing Data Transposing the Data The Categorical Data and Why Zero? And Missing Results Differ Greatly Performing Many-to-Many Comparisons/Joins Using the Medical Directories Other Tricks and the Traps in the Data Manupulation B) The Common Analysis Data Sets The subject level Data Set The Change-from-baseline data set The Time-to-Event Data Set
5 5 Creating Tables and Listings A) Creating the Table A General Approach to Creating Tables About the Typical Clinical Trail Table Using the PROC TABULATE to Create Clinical Trail Tables Using the PROC REPORT in creating the clinical trail tables Creating the typical continuous or the Categorical summary tables Creation of the adverse event summaries Creating the concomitant or the prior medication tables Creating the Laboratory Shift Tables Creating the Kaplan-Meier Survival Estimates Tables B) Creating the Listings C) The Output Appearance Options and the Issues Creating the ASCII Text Output Creating the RTF Output (Rich Text Format) Creation of the PDF Files (Portable Document Format) The pagination Solutions: Page X of N Footnote Indicating the SAS Program and the Date ODS the Report Writing Interface About the Power of the ODS STYLE D) SAS Macro-based Reporting Systems 6 Creating Clinical Trial Graphs A) The Common Clinical Trail Graph The Scatter Plot The Line Plot About the Bar Chart Box Plot Forest Plot The Kaplan-Meier Survival Estimates Plot
6 B) The SAS tools for creating the Clinical Trial Graph C) Sample of the Graphs Creating the Scatter Plot Creating the Line Plot Creation of the Bar Chart Creation of the Forest Plot Creating the Kaplan-Meier Survival Estimates Plot D) Using the SAS Graphics Assistance Graph-n-Go The SAS Enterprise Guide The ODS Graphic Designer The ODS Graphics Editors E) When the SAS Graphics should be used 7 Performing Common Analyses and Obtaining A) Obtaining the Descriptive Statistics How to Export the Descriptive Statistics using the PROC FREQ Exporting the Descriptive Statistics using the PROC UNIVARIATE B) Obtaining the Inferential Statistics From Categorial Data Analysis For the Association: Performing 2x2 Test For the Association: Performing an NxP Test For the Association: Performing a Stratified NxP Test Performing Logistic Regression C) Obtaining the Inferential Statistics from the continuous Data Analysis Performing the One-sample Test of Mean Performing Two-Sample Test of Means Performing an N-Sample test of the Means D) Obtaining Time-to-Event Analysis Stastistics Obtaining the correlation Coefficients General Approach to obtaining Statistics
7 8 Exporting the Data A) Exporting the Data to FDA Use of the SAS XPORT Transport Format in exporting Data Creating the ODM XML and define.xml B) Exporting the Data not destined for the FDA Exporting the data with PROC CPORT Exporting the ASCII Text Exporting the data to the MS Office Files Exporting Other Proprietary Data Formats C) Encryption and the files transportation Options 9 Exporting Data: The Future of SAS Programming in Clinical Trials The change in the business atmosphere Change in the Technology Change in the Regulations Change in the Standards The use of the SAS software in the Clinical Trial Industry 10 The Future Resources A) The regulatory Resources About the SAS Programing Validation What are the FDA Resources B) Standards and the Industry Organizations C) The SAS Help The Google Search Lexjansen.com The SAS-L Technical Support of SAS The User Group of SAS
8 SAS Manual and the online documentation The SAS Press The SAS Focus Areas The Thrid-Party SAS Web pages D) Other Useful technical Skills Scripting About version control software About VBScript/JAVAScript for the Applications The Methodology for System Development About Modeling Tools The Markup languages What is File Transportation? And the Data Encryption Technologies About other languages used in Application Development Module III: Analysis of Clinical Trials Using SAS 1 Analysis of Stratified Data Introduction to the Stratified Data Analysis About the Continuous Endpoints The Categorial Endpoints About Time-to-Event Endpoints Test for qualitative interactions 2 Multiple Comparisons and Multiple Endpoints An Introduction The Single-step tests What are the close testing methods? The Fixed-Sequesce Testing Methods Testing methods based on Resampling Multiple Endpoints Testing procedures
9 The Gatekeeping Strategies 3 Analysis of Safety and Diagnostic Data An Introduction to the Analysis of Safety and Diagnostic Data The References Intervals for the Safety and the Diagonistic Measures Analysis of the Shift Tables 4 Interim Data Monitoring An Introduction to the Interim Data Monitoring The Repeated Significance Tests About Stochastic Curtailment Tests 5 Analysis of Incomplete Data Introduction The Case Study The Data Setting and the Modeling Framework The Complete growth data Analysis What are the Simple Methods and the MCAR? The Available Case Methods Likelihood-based Ignorable Analysis The Multiple imputation The Categorical data About EM Algorithms The MNAR and the Sensitivity Analysis
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