CDISCCD01. A Cost-Effective SDTM Conversion for NDA Electronic Submission
Xiangchen (Bob) Cui, Vertex Pharmaceuticals, Cambridge, MA
Scott Moseley, Vertex Pharmaceuticals, Cambridge, MA
Min Chen, Vertex Pharmaceuticals, Cambridge, MA

CD02. Automating the Process of Preparing Data Definition Document for NDA Electronic Submission from Programming Specification in Word Format
Min Chen, Vertex Pharmaceuticals, Cambridge, MA
Xiangchen (Bob) Cui, Vertex Pharmaceuticals, Cambridge, MA
Scott Moseley, Vertex Pharmaceuticals, Cambridge, MA

CD04. Evolution of SDTMIG 3.1.1 to 3.1.2: A mapping specialist must reference on these changes
Rachit Desai, eClinical Solutions, New London, CT
Anirudh Gautam, MaxisIT, Metuchen, NJ
Vikash Jain, eClinical Solutions, New London, CT

CD05. Methods of Building Traceability for ADaM Data
Songhui Zhu, K & L Consultant Services, Fort Washington, PA
Lin Yan, Celgene Corp, Basking Ridge, NJ

CD06. Validating Controlled Terminology in SDTM Domains
John R. Gerlach, SAS / CDISC Analyst; Hamilton, NJ

CD07. Resolving OpenCDISC Error Messages Using SAS®
Virginia Redner, Merck & Company, Inc., Upper Gwynedd, PA
John R. Gerlach, SAS / CDISC Analyst; Hamilton, NJ

CD08. A Special SDTM Domain RELREC and its Application
Changhong Shi, Merck Sharpe & Dohme Corp., Rahway, NJ
Beilei Xu, Merck Sharpe & Dohme Corp., Rahway, NJ

CD09. Basic Understanding on SE Domain for Beginners
Gayatri Karkera, i3 Statprobe (Ingenix Pharmaceutical Services), Mumbai, India

CD10. Efficiencies Realized in Building and Utilizing ADaM from SDTM
Shirish Nalavade, eClinical Solutions, a Division of Eliassen Group, Mansfield, MA
Parag Shiralkar, eClinical Solutions, a Division of Eliassen Group, New London, CT

CD11. CDISC Variable Mapping and Control Terminology Implementation Made Easy
Balaji Ayyappan, Ockham Group, Cary, NC
Manohar Sure, Ockham Group, Cary, NC

CD12. ADaM Standard Naming Conventions are Good to Have
Christine Teng, Merck Sharp & Dohme Corp, Rahway, NJ

CD13. Trials and Tribulations of SDTM Trial Design
*** BEST PAPER ***
Fred Wood, Octagon Research Solutions, Wayne, PA
Mary Lenzen, Octagon Research Solutions, Wayne, PA

CD14. The Standard for the Exchange of Nonclinical Data (SEND): History and Basics
Fred Wood, Octagon Research Solutions, Wayne, PA
Lou Ann Kramer, Eli Lilly and Company, Indianapolis, IN

CD15. Validating define.xml: Tools, trials, and tribulations
Sandra VanPelt Nguyen, i3 Statprobe

CD17. Making a List, Checking it Twice (Part 1): Techniques for Specifying and Validating Analysis Datasets
Elizabeth Li, PharmaStat LLC, Newark, California
Linda Collins, PharmaStat LLC, Newark, California

CD18. A Regular Language: The Annotated Case Report Form
*** BEST PAPER ***
Ryan Wilkins, PPD, Inc., Wilmington, NC
Joel Campbell, PPD, Inc., Wilmington, NC

CD19. Challenges in Implementing ADaM datasets: Balancing the Analysis-Ready and Traceability Concepts
Pushpa Saranadasa, Merck & Co., Inc.

CD20. Find / Track / Check and Close, Using SAS to Streamline SDTM Validation Including the Hyperlinks
David Tillery, Smith Hanley Consulting, Lake Mary, Florida USA
Qiang Zhai, Purdue Pharma L.P., Stamford, Connecticut USA
Lily Peng, Purdue Pharma L.P., Stamford, Connecticut USA

CD21. Ensuring Consistent Data Mapping Across SDTM-based Studies – a Data Warehouse Approach
Annie Guo, ICON Clinical Research, North Wales, PA

CD22. Truncation, Variable Association, Controlled Terminology, and Some Other Pitfalls in the SDTM Mapping Process
Na Li, XenoPort, Inc., Santa Clara, CA
Gary de Jesus, Infovision, Inc., Richardson, TX
Daniel Bonzo, XenoPort, Inc., Santa Clara, CA

CD23. Good Versus Better SDTM -- Date and Time Variables
Mario Widel, Roche Molecular Systems, Inc., Pleasanton, CA
Henry B. Winsor, WinsorWorks, Limited, San Mateo, CA

Data ManagementDM01. Building a Hosted Statistical Computing Environment: Is it Possible?
*** BEST PAPER ***
John Leveille, d-Wise Technologies, Raleigh, NC, USA

DM02. The Illusion of Good Data, or How Not to Think of a Blue Elephant
Kim Truett, KCT Data, Inc., Alpharetta, GA

DM03. Data Edit-checks Integration using ODS Tagset
Niraj J. Pandya, Element Technologies Inc., NJ
Vinodh Paida, Impressive Systems Inc., TX

DM04. Data Quality Review for Missing Values and Outliers
Ying Guo, i3 Statprobe, Indianapolis, IN
Bradford J. Danner, i3 Statprobe, Lincoln, NE



Hands-On WorkshopsHW01. A Pragmatic Programmers Introduction to Data Integration Studio: Hands on Workshop (updated for DI Studio 4.2)
Gregory S. Nelson, ThotWave Technologies, Cary, North Carolina

HW02. SAS/GRAPH® Elements You Should Know – Even If You Don’t Use SAS/GRAPH
Arthur L. Carpenter, California Occidental Consultants, Anchorage, AK

HW03. Creating SDTM Datasets from Legacy Data
Fred Wood, Octagon Research Solutions, Wayne, PA

HW04. Powerful and “Sometimes” Hard-to-find PROC SQL® Features
Kirk Paul Lafler, Software Intelligence Corporation, Spring Valley, California

HW05. From SAP to BDS: The Nuts and Bolts
Nancy Brucken, i3 Statprobe, Ann Arbor, MI
Paul Slagle, United BioSource Corp., Ann Arbor, MI

HW07. An Introduction to SAS/GRAPH or Quick Tricks with the GPLOT and GCHART Procedures And the Annotate Facility
Ben Cochran, The Bedford Group, Raleigh, NC

HW08. SDTM, ADaM and define.xml with OpenCDISC®
Matt Becker, PharmaNet, Cary, NC
Angela Ringelberg, PharmaNet, Cary, NC



Health Science, Epidemiology, and Post-Market ResearchHS01. Effectiveness Of Disease Management Care In The Case Of Heart Failure
Beatrice Ugiliweneza, Department of Mathematics, University of Louisville, Louisville, KY

HS03. Using SAS Predictive Modeling to Investigate the Asthma’s Patient Future Hospitalization Risk
Yehia H. Khalil, University of Louisville, Louisville, KY, US

HS04. Cost-Effectiveness Of Primary PCI At Hospitals Without Onsite CaABG
Pedro Ramos, University of Louisville, Louisville, KY

HS06. Classification of frequent snoring from routine medical examinations using the NHANES Database
Barry W. Row, University of Louisville, Louisville, KY, USA

HS07. Adjusting Analyses of Survey Results using a Predicted Probability of Response
*** BEST PAPER ***
Rob Gately, INNOVUS: Epidemiology, Waltham, MA

HS08. Visualizing Healthcare Provider Network using SAS® Tools
John Zheng, Columbia, MD

HS09. Clinical Trials Versus Health Outcomes Research: SAS/STAT Versus SAS Enterprise Miner
Patricia B. Cerrito, University of Louisville, Louisville, KY

HS10. Epidemiology in Drug Development
Catherine Sigler, DVM MPH PhD, United BioSource Corporation, Ann Arbor, MI
Annette Stemhagen, DrPH, FISPE, United BioSource Corporation, Blue Bell, PA

HS11. Analytical Methods for Post-Marketing Safety Surveillance
Annette Stemhagen, DrPH, FISPE, United BioSource Corporation, Blue Bell, PA
Juliane K. Mills, United BioSource Corporation, Blue Bell, PA

Industry BasicsIB01. Success As a Pharmaceutical Statistical Programmer
Sandra Minjoe, Octagon Research
Mario Widel, Roche Molecular Systems

IB03. Oncology Trials 101 - The Basics and Then Some
Dave Polus, COMSYS Clinical, Portage, MI

IB04. Brave New World: How to Adapt to the CDISC Statistical Computing Environment
Jeff Abolafia, Rho, Inc., Chapel Hill NC
Frank DiIorio, CodeCrafters, Inc., Philadelphia PA

IB05. Similarities and Differences in SAS Programming Among CRO and Pharmaceutical Industries
*** BEST PAPER ***
Sandra Minjoe, Octagon Research Solutions, Wayne, PA
Mark Matthews, i3Statprobe, Indianapolis, IN

IB06. Your Dataset Looks Fine – But Does It Comply with ’99?
Meenal Sinha, Octagon Research Solutions, Inc., Wayne, PA

IB07. Using Six Sigma Methodologies to Find a Solution for Increasing Training Completions
Eunice Ndungu, Merck, North Wales PA
Shazia Khawaja, Merck, North Wales PA
Janet Low, Merck, North Wales PA
Steve Miola, Merck, North Wales PA



ManagementMA01. Lessons Learned From Managing a New Statistical Programming Group
Yong Zhao, inVentiv Clinical Solutions, Somerset, NJ

MA02. Managing the Validation and Migration from SAS® 9.13 to 9.2 on a New Server
Carey Smoak, Roche Molecular Systems, Inc., Pleasanton, CA
Sy Truong, Meta-Xceed, Inc. (MXI), Fremont, CA

MA03. A Six-Sigma/DMAIC Approach to Defining a SAS Macro Repository Strategy
*** BEST PAPER ***
Sandy Paternotte, PPD, Inc., Wilmington, NC
Tom Fritchey, PPD, Inc., Wilmington, NC

MA04. Developing Resourcefulness in SAS® Programmers
Brian Varney, COMSYS, Kalamazoo, MI

MA05. Helping Students Become Effective Industry Statisticians: Supplementing Science with Data Savvy
Aleksandra Stein, Celerion, Lincoln, Nebraska
Steven Kirby, Celerion, Lincoln, Nebraska

MA06. Using LinkedIn and sasCommunity.org as Human Resource Tools for Managing a Network of SAS® Professionals
Kirk Paul Lafler, Software Intelligence Corporation, Spring Valley, California
Charles Edwin Shipp, JMP 2 Consulting, Inc., San Pedro, California



PostersPO01. BAT Files: Run all Your Programs with One Click in PC SAS
William Conover, Advanced Clinical, Bannockburn, IL

PO02. Generate Informative Clinical Laboratory Results Listing
Sai Ma, Everest Clinical Research Services Inc., Markham, Ontario, Canada

PO03. A Practical Approach to Process Improvement Using Parallel Processing
Viraj Kumbhakarna, Cognizant Technology Solutions Corporation, Lake Hiawatha, NJ

PO04. Assumptions and Consequences of Comparative Effectiveness Analysis Using Data Mining
Patricia B. Cerrito, University of Louisville, John Cerrito, Kroger Pharmacy

PO05. Cumulative Incidence Ratio Plots
Sai Ma, Everest Clinical Research Services Inc., Markham, Ontario, Canada

PO06. Get Dynamic Multi-sheet Excel Workbook with STYLE using ODS
Niraj J. Pandya, Element Technologies Inc., NJ

PO08. FAQ: Issues with Efficacy Analysis of Clinical Trial Data Using SAS
Sandeep Sawant, i3 Statprobe (INGENIX Pharmaceutical Services), India
Neha Mohan, i3 Statprobe (INGENIX Pharmaceutical Services), India

PO09. Method to Derive Reproducible SDTM Relationship Datasets
Suwen Li, Everest Research Services Inc., Markham, ON
Sai Ma, Everest Research Services Inc., Markham, ON
Regan Li, Everest Research Services Inc., Markham, ON
Bob Lan, Everest Research Services Inc., Markham, ON

PO11. Automated Generation of Clinical Study Reports
*** BEST PAPER ***
Suhas R. Sanjee, Merck Sharp & Dohme Corp., Upper Gwynedd, PA
Rajavel Ganesan, Merck Sharp & Dohme Corp., Upper Gwynedd, PA
Jason Clark, Merck Sharp & Dohme Corp., Upper Gwynedd, PA

PO12. Processing the RefSeq and CCDS Annotation Datasets Using the SAS System: Creation of Gene Reference
Kevin Viel, Saint Joseph’s Translational Research Institute, Atlanta, GA
Shannon Grabich, Kennesaw State University, Kennesaw, GA

PO13. Array of hope: Using SAS Arrays to produce data-driven analysis and reports
Aida Likaj, PPD Inc., Austin, TX

PO14. Automatization of Patient Characteristics Report
Mirjana Stojanovic, Cancer Center Biostatistics, Duke University Medical Center, Durham, NC

PO16. Computing Percentage Using PROC TABULATE – from Simple to More Complex
Wende (Ted) Tian, Merck Sharpe & Dohme Corp., Rahway, NJ
Hong (Lily) Zhang, Merck Sharpe & Dohme Corp., Rahway, NJ

SAS PresentsSAS-AD01. Tips and Tricks for Clinical Graphs using ODS Graphics
Sanjay Matange, SAS Institute Inc., Cary, NC

SAS-AD02. Beyond the Basics: Advanced REPORT Procedure Tips and Tricks Updated for SAS® 9.2
Allison McMahill Booth, SAS Institute Inc., Cary, NC, USA

SAS-AD03. SAS Drug Development Program Portability
Ben Bocchicchio, SAS Institute, Cary NC, US
Nancy Cole, SAS Institute, Cary NC, US

SAS-CC27. SAS Abbreviations are your friends, use the template method to code!
Elizabeth Ceranowski, SAS Institute, Cary, NC

SAS-CD01. Confessions of a Clinical Programmer: Dragging and Dropping Means Never Having to Say You’re Sorry When Creating SDTM Domains
Janet Stuelpner, SAS Institute, Inc.
Jack Shostak, Duke Clinical Research Institute

SAS-DM01. Choosing the Road Less Traveled: Performing Similar Tasks with either SAS® DATA Step Processing or with Base SAS® Procedures
Kathryn McLawhorn, SAS Institute Inc., Cary, NC

SAS-HW01. Creating Stylish Multi-Sheet Microsoft Excel Workbooks the Easy Way with SAS®
Vincent DelGobbo, SAS Institute Inc., Cary, NC

SAS-HW02. Using the SAS® Clinical Standards Toolkit for define.xml creation
Lex Jansen, SAS Institute Inc., Cary, NC

SAS-SP01. CONTRAST and ESTIMATE Statements Made Easy: The LSMESTIMATE Statement
Kathleen Kiernan, SAS Institute Inc., Cary, NC
Randy Tobias, SAS Institute Inc., Cary, NC
Phil Gibbs, SAS Institute Inc., Cary, NC
Jill Tao, SAS Institute Inc., Cary, NC

SAS-TT01. Don’t Gamble with Your Output: How to Use Microsoft Formats with ODS
Cynthia L. Zender, SAS Institute, Inc., Cary, NC, USA

SAS-TT02. The Perfect Marriage: The SAS® Output Delivery System (ODS) and Microsoft Office
Chevell Parker, SAS Institute



Statistics and PharmacokineticsSP02. Incorporating Graphics into Summary Report Tables using ODS and GTL
Qinghua (Kathy) Chen, Genentech Inc., South San Francisco, CA

SP03. Formulas Calculating Risk Estimates and Testing for Effect Modification and Confounding
Manojkumar B Agravat, Tampa, Florida

SP04. Implementation of Pattern-Mixture Models Using Standard SAS/STAT Procedures
*** BEST PAPER ***
Bohdana Ratitch, Quintiles, Montreal, Quebec, Canada
Michael O’Kelly, Quintiles, Dublin, Ireland

SP05. A Modular Approach of Reporting Meta Analysis Statistics Using Forest Plots
Vikash Jain, eClinical Solutions, A Division of Eliassen Group, New London, CT

SP06. Caution: Hazards Crossing! Using the Renyi Test Statistic in Survival Analysis
Matthew Davis, M.S., University of Pennsylvania, Philadelphia, PA
Sharon X. Xie, Ph.D., University of Pennsylvania, Philadelphia, PA

SP07. Statistical Analysis of Adverse Events in Randomized Clinical Trials Using SAS
Dongsun Cao, ICON Clinical Research, Durham, NC
Xiaomin He, ICON Clinical Research, North Wales, PA

SP08. Estimating Sample Size through Simulations
Wuchen Zhao, University of Southern California, Los Angeles, CA
Arthur X. Li, City of Hope National Cancer Center, Duarte, CA

SP09. Implementation of Pairwise Fitting Technique for Analyzing Multivariate Longitudinal Data in SAS
Madan Gopal Kundu, Indiana University Purdue University at Indianapolis, Indianapolis, IN

SP10. Using SAS® for Modeling and Simulation in Drug Development – A Review and Assessment of Some Available Tools
Melvin Munsaka, TGRD, Deerfield, Illinois
Michael Carniello, TGRD, Deerfield, Illinois

SP11. Evaluating Safety Signals in Clinical Trials: the Dirichlet-NBD Model Implementation with SAS
Yuqin Li, inVentiv Clinical Solutions, Indianapolis, IN
Xiaohai Wan, Eli Lilly and Company, Indianapolis, IN

Technical TechniquesTT01. Scatter Charts of Serial Observations with Proc SGPLOT and Graphics Template Language
Anthony L. Feliu, Genzyme Corporation, Cambridge, Massachusetts

TT02. Create a Format from a SAS® Data Set
Ruth Marisol Rivera, i3 Statprobe, Mexico City, Mexico

TT03. Creating Customized Patient Profiles using SAS ODS RTF and PROC TEMPLATE
*** BEST PAPER ***
Andrea Ritter, Biostatistics, Quintiles Inc., Morrisville, NC

TT04. Using a HASH Table to Reference Variables in an Array by Name
John Henry King, Hopper, Arkansas

TT05. Good Programming Practices in Healthcare Creating Robust Programs
Gregory S. Nelson, ThotWave Technologies
Jay Zhou, Q-Squared Business Intelligence, Inc.

TT06. You Want that Program to Run on the PC in New Jersey and the Unix in Basel, without Modification??
David Franklin, TheProgrammersCabin.com, Litchfield, NH

TT07. Keeping Patients on Schedule, The Art of Visit Windows and Cycle Slotting
Paul Slagle, United Biosource Corp., Ann Arbor, MI

TT08. Alternative Approaches to Creating Disposition Flow Diagrams
Brian Fairfield-Carter, ICON Clinical Research, Redwood City, CA
Suzanne Humphreys, ICON Clinical Research, Redwood City, CA

TT10. Creating a Customized Graph for Adverse Event Incidence and Duration
Sanjiv Ramalingam, Octagon Research Solutions Inc.

TT11. Type Less, Do More: Have SAS® do the typing for you
Jeanina Worden, PPD, Austin TX

TT12. Creating Forest Plots Using SAS/GRAPH and the Annotate Facility
Amanda Tweed, Millennium: The Takeda Oncology Company, Cambridge, MA

TT13. ExcelXP on Steroids: Adding Custom Options To The ExcelXP Tagset
Mike Molter, D-Wise Technologies, Raleigh, NC

TT14. Run your reports through that last loop to standardize the presentation attributes
Niraj J. Pandya, Element Technologies Inc., NJ

TT15. An Introduction to SAS® Hash Programming Techniques
Kirk Paul Lafler, Software Intelligence Corporation, Spring Valley, California



TutorialsTU01. Creating Hyperlinked PDF Graphical Patient Profiles with PROC REPORT
William Conover, Advanced Clinical, Bannockburn, IL

TU02. New Tips and Tricks for Creating a Harmonized, Report-Friendly SDTM and ADaM Lab Data for a Clinical Study Report
Xiangchen (Bob) Cui, Vertex Pharmaceuticals, Cambridge, MA
Min Chen, Vertex Pharmaceuticals, Cambridge, MA
Scott Moseley, Vertex Pharmaceuticals, Cambridge, MA

TU03. Excel Traffic Lighting and Street Paving Simplified
Steven Black, W. L. Gore & Associates, Inc., Flagstaff, AZ

TU04. Leave Your Bad Code Behind: 50 Ways to Make Your SAS Code Execute More Efficiently
William E Benjamin Jr, Owl Computer Consultancy, LLC, Phoenix, AZ

TU05. A Many to Many Merge, Without SQL?
David Franklin, TheProgrammersCabin.com, Litchfield, NH

TU06. The Many Ways To Effectively Utilize Array Processing
Arthur Li, City of Hope Comprehensive Cancer Center, Duarte, CA

TU07. A Cup of Coffee and Proc FCMP: I Cannot Function Without Them
Peter Eberhardt, Fernwood Consulting Group Inc, Toronto ON

TU08. Perl Regular Expressions: Out of the Oyster, Into Your Code
Eric Larson, Madison, Wisconsin

TU09. Using the ADaM Basic Data Structure for Survival Analysis
*** BEST PAPER ***
Nancy Brucken, i3 Statprobe, Ann Arbor, MI
Sandra Minjoe, Octagon Research, Wayne, PA
Mario Widel, Roche Molecular Systems, Pleasanton, CA