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E-grāmata: Clinical Data Quality Checks for CDISC Compliance Using SAS

(Gupta Programming, California, USA)
  • Formāts: 163 pages
  • Izdošanas datums: 23-Sep-2019
  • Izdevniecība: Chapman & Hall/CRC
  • Valoda: eng
  • ISBN-13: 9781000699043
  • Formāts - EPUB+DRM
  • Cena: 52,59 €*
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  • Formāts: 163 pages
  • Izdošanas datums: 23-Sep-2019
  • Izdevniecība: Chapman & Hall/CRC
  • Valoda: eng
  • ISBN-13: 9781000699043

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Clinical Data Quality Checks for CDISC Compliance using SAS is the first book focused on identifying and correcting data quality and CDISC compliance issues with real-world innovative SAS programming techniques such as Proc SQL, metadata and macro programming. Learn to master Proc SQLs subqueries and summary functions for multi-tasking process. Drawing on his more than 25 years experience in the pharmaceutical industry, the author provides a unique approach that empowers SAS programmers to take control of data quality and CDISC compliance.

This book helps you create a system of SDTM and ADaM checks that can be tracked for continuous improvement. How often have you encountered issues such as missing required variables, duplicate records, invalid derived variables and invalid sequence of two dates? With the SAS programming techniques introduced in this book, you can start to monitor these and more complex data and CDISC compliance issues. With increased standardization in SDTM and ADaM specifications and data values, codelist dictionaries can be created for better organization, planning and maintenance. This book includes a SAS program to create excel files containing unique values from all SDTM and ADaM variables as columns. In addition, another SAS program compares SDTM and ADaM codelist dictionaries with codelists from define.xml specifications. Having tools to automate this process greatly saves time from doing it manually.

Features



















SDTMs and ADaMs Vitals





SDTMs and ADaMs Data





CDISC Specifications Compliance





CDISC Data Compliance





Protocol Compliance





Codelist Dictionary Compliance

Recenzijas

"This book is is indespensible for anyone implementing CDISC compliance and data quality checking. The practical examples will save a great deal of time and effort. Furthermore, the methods of the code are explained in detail to help the user understand how to create new checks as needed. Reader will improve understanding of CDISC principles and SQL . There are many highly developed diagrams to help organize and visualize." Chris Weiner, Sr. Statistical Programmer, GCE Solutions

"A must-read and reference for all clinical programmers. Data quality is fundamental for good clinical practice and this book is laser-focused on specific and critical programming techniques assuring compliant SDTM and ADAM data and reporting. It is a comprehensive desk reference which will become a standard for the industry. The included and well documented SAS code provides programmers with state of the art algorithms for validating and verifying STAM and ADAM datasets." - Roger DeAngelis, CEO CompuCraft Ltd

"As I was reading this book, I instantly realized that the author has expert level knowledge in the clinical SAS programming arena. With the acceptance of CDISC as the standard for FDA submissions, it is imperative that companies submit air-tight data with complete compliance of clinical data standards. This is no easy task, but Sunil Gupta has done an outstanding job of providing a framework for creating standardized data. The SAS code is easy to use and generates compliant data without a hint of hardcoding. The book has a nice flow and diagrams are strategically interspersed to assist the reader in understanding the entire process. Another nice feature is that the book has sufficient detail without being tedious. This publication is very well organized allowing one to quickly find the requisite code by scanning the table of contents. I highly recommend this book for anyone in the clinical SAS environment, especially those involved in programming, validation, or project management." -Paul Gill, Clinical SAS Expert, BioClinicalData

"This book is a must-read for programmers working with clinical trials data. It is a hands-on book with a wealth of examples that can be applied directly or with slight modification to your existing processes. What makes Mr. Guptas innovative SQL coding especially attractive is the way it yields concise, easy to interpret summary reports at each step from data capture through SDTM and AdAM data sets. His techniques for CDISC, protocol and codelist dictionary compliance are especially valuable for revealing errors at the coding stage, rather than later when rework would be costly and time-consuming. The programs in this book would make a valuable addition to any coders toolbox." -Vincent Rabatin, Founder, Rabatin Pharma Services

"Nowadays, data quality and data checks are very important for agency submissions. If you don't have much knowledge of these issues and solution then this book is for you! Without this book, you may find it difficult and time consuming to create compliant SDTMs and ADaMs. This book covers lots of information that can be utilized to mitigate the issues at an early stage and also helps to increase data fitness scores. This book is very helpful for the Clinical and Statistical SAS programmers." - Ratheesh Gunda, Principal Statistical Programmer, Cytel "This book is is indespensible for anyone implementing CDISC compliance and data quality checking. The practical examples will save a great deal of time and effort. Furthermore, the methods of the code are explained in detail to help the user understand how to create new checks as needed. Reader will improve understanding of CDISC principles and SQL . There are many highly developed diagrams to help organize and visualize." Chris Weiner, Sr. Statistical Programmer, GCE Solutions

"A must-read and reference for all clinical programmers. Data quality is fundamental for good clinical practice and this book is laser-focused on specific and critical programming techniques assuring compliant SDTM and ADAM data and reporting. It is a comprehensive desk reference which will become a standard for the industry. The included and well documented SAS code provides programmers with state of the art algorithms for validating and verifying STAM and ADAM datasets." - Roger DeAngelis, CEO CompuCraft Ltd

"As I was reading this book, I instantly realized that the author has expert level knowledge in the clinical SAS programming arena. With the acceptance of CDISC as the standard for FDA submissions, it is imperative that companies submit air-tight data with complete compliance of clinical data standards. This is no easy task, but Sunil Gupta has done an outstanding job of providing a framework for creating standardized data. The SAS code is easy to use and generates compliant data without a hint of hardcoding. The book has a nice flow and diagrams are strategically interspersed to assist the reader in understanding the entire process. Another nice feature is that the book has sufficient detail without being tedious. This publication is very well organized allowing one to quickly find the requisite code by scanning the table of contents. I highly recommend this book for anyone in the clinical SAS environment, especially those involved in programming, validation, or project management." -Paul Gill, Clinical SAS Expert, BioClinicalData

"This book is a must-read for programmers working with clinical trials data. It is a hands-on book with a wealth of examples that can be applied directly or with slight modification to your existing processes. What makes Mr. Guptas innovative SQL coding especially attractive is the way it yields concise, easy to interpret summary reports at each step from data capture through SDTM and AdAM data sets. His techniques for CDISC, protocol and codelist dictionary compliance are especially valuable for revealing errors at the coding stage, rather than later when rework would be costly and time-consuming. The programs in this book would make a valuable addition to any coders toolbox." -Vincent Rabatin, Founder, Rabatin Pharma Services

"Nowadays, data quality and data checks are very important for agency submissions. If you don't have much knowledge of these issues and solution then this book is for you! Without this book, you may find it difficult and time consuming to create compliant SDTMs and ADaMs. This book covers lots of information that can be utilized to mitigate the issues at an early stage and also helps to increase data fitness scores. This book is very helpful for the Clinical and Statistical SAS programmers." - Ratheesh Gunda, Principal Statistical Programmer, Cytel

"CDISC provides a standard framework for describing data collected from clinical and preclinical studies. Now data submitted to FDA and some other regulatory agencies are required to be in CDISC compliant format. For many biometrics professionals (biostatisticians, programmers, and data managers), CDISCs Foundational Standards, Data Exchange Standards, and Controlled Terminology Standards may be felt overwhelmed. In this book, Sunil explains these standards in plain language, and walks you through the roadmap of building a system of macros for in-house compliance check using many easy to understand SAS examples." - Jeff Cao, CEO, VIITAI

Preface ix
Acknowledgments xiii
Author xv
Chapter 1 Overview of Data Quality and Compliance Checks
1(16)
Introduction
1(2)
1.1 Level of Checks to Apply
3(9)
1.1.1 SDTMs And ADaMs Vitals
4(1)
1.1.2 SDTMs and ADaM Data
5(4)
1.1.3 CDISC Specifications Compliance
9(1)
1.1.4 CDISC Data Compliance
9(1)
1.1.5 Protocol Compliance
10(1)
1.1.6 Codelist Dictionary Compliance
10(2)
1.2 WHEN TO APPLY CHECKS
12(1)
1.2.1 Database Acceptance and Lock
12(1)
1.2.2 SDTMs and ADaMs Refresh
12(1)
1.2.3 Snapshot Analysis
12(1)
1.3 CUSTOMIZED CHECKS FOR EACH CLIENT
13(1)
1.3.1 Site Management
13(1)
1.3.2 Data Management
13(1)
1.3.3 SAS Programmers
14(1)
1.3.4 Statisticians
14(1)
Summary
14(3)
Chapter 2 SDTMs and ADaMs Vital Checks
17(22)
Introduction
17(1)
2.1 Dataset Vitals
17(6)
2.2 Data Transfers
23(7)
2.3 Group Descriptive Statistics
30(4)
2.4 Zero Dataset Records
34(1)
2.5 Disposition Population Trees (Saffl, Ittfl)
35(2)
2.6 SDTM Oncology Domain
37(1)
Summary
37(2)
Chapter 3 SDTMs and ADaMs Data Checks
39(40)
Introduction
39(1)
3.1 Duplicate Records
39(4)
3.2 Missing Values In Required Variables
43(4)
3.3 Variable Unique Counts
47(1)
3.4 Iso8601 Datetime And Time
48(4)
3.5 Duration
52(2)
3.6 Data Range
54(1)
3.7 Negative Values
55(1)
3.8 Numeric Outliers
56(3)
3.9 Compare Related Variables
59(13)
3.10 Calculations And Derived Variable
72(3)
3.11 Lab Data
75(3)
Summary
78(1)
Chapter 4 Cdisc Specification Compliance Checks
79(14)
Introduction
79(1)
4.1 Consistency Between Dm Specifications And Attributes (Type, Name, Length, Label)
80(5)
4.2 Non-Missing Dataset Label
85(1)
4.3 No Permanent Format In Dm
86(1)
4.4 Dm Correct Order Of Variables
87(2)
4.5 Variable Length Is Maximum Of Values Or 200
89(3)
Summary
92(1)
Chapter 5 CDISC Data Compliance Checks
93(10)
Introduction
93(1)
5.1 Sdtm Consistency
93(7)
5.1.1 Aenum And Cenum
93(1)
5.1.2 Ae.Aeseq And Suppae.Idvarval
94(1)
5.1.3 Orphan Records In Suppxx
95(2)
5.1.4 Domain Variable And Name
97(1)
5.1.5 Required Sdtm Domains (Ta, Dm, Ex And Ds) Do Not Exist
97(2)
5.1.6 Required Adams (Adsl) Do Not Exist
99(1)
5.1.7 Se Start And End Dates Sequence Requirement
99(1)
5.2 Adam Consistency
100(2)
Summary
102(1)
Chapter 6 Protocol Compliance Checks
103(12)
Introduction
103(1)
6.1 Usubjid Missing In Dm/Adsl
103(2)
6.2 Missing Exposure Record In Ex For Dm Usubjid
105(3)
6.3 Lab Data Baseline
108(4)
6.3.1 Incorrect Adblfl Baseline Flag Record
108(1)
6.3.2 No Baseline Result For Vs, Lb, Eg, Da
109(3)
6.4 Disposition Tree Check -- One-Proc Away
112(1)
Summary
113(2)
Chapter 7 Codelist Dictionary Compliance Checks
115(12)
Introduction
115(1)
7.1 Codelist, Value-Level Checks And Lookup Tables
116(9)
7.2 Codelist And Value-Level Uppercase
125(1)
Summary
126(1)
Appendix 127(14)
References 141(4)
Index 145
Sunil Gupta is an international speaker, best-selling SAS author, and a global corporate trainer. Sunil is a Principal SAS/CDISC Consultant. Most recently, he taught both of his CDISC online classes with the University of California at San Diego and SAS Institute India. New in 2019, Sunil is developing a new class on Data Science using SAS class. In 2011, Sunil launched his unique SAS resource blog, SASSavvy.com, for smarter SAS searches. Currently, SAS Savvys membership consists mostly of SAS programmers, university students and pharmaceutical corporate accounts