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NESUG 2011 Publication

https://lexjansen.com/nesug/nesug11/ph/ph08.pdf

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SAS Interview Questions and Answers: CDISC, SDTM and ADAM etc

- September 23, 2008

1) What do you know about CDISC and its standards? CDISC stands for Clinical Data Interchange Standards Consortium and it is developed keeping in mind to bring great deal of efficiency in the entire drug development process. CDISC brings efficiency to the entire drug development process by improving the data quality and speed-up the whole drug development process and to do that CDISC developed a series of standards, which include Operation data Model (ODM), Study data Tabulation Model (SDTM) and the Analysis Data Model ADaM ). 2) Why people these days are more talking about CDSIC and what advantages it brings to the Pharmaceutical Industry? A) Generally speaking, Only about 30% of programming time is used to generate statistical results with SAS®, and the rest of programming time is used to familiarize data structure, check data accuracy, and tabulate/list raw data and statistical results into certain formats. This non-statistical programming time will be significantly reduced...

SAS interview questions: Macros

- September 02, 2008

SAS Macros Interview Questions and Answers SAS Macros Interview Questions and Answers This document provides a collection of interview questions and answers related to SAS Macros, which are a powerful feature in SAS for automating repetitive tasks and dynamically generating code. 1. What is a macro in SAS? A macro in SAS is a code that generates SAS statements dynamically. Macros allow for automation, reusability, and parameterization of code, making it more flexible and efficient. 2. How do you create a simple macro in SAS? You can create a macro in SAS using the %MACRO and %MEND statements. Here's an example: %macro simple_macro; data new_data; set old_data; /* Your SAS code here */ run; %mend simple_macro; %simple_macro; 3. What is the difference between a macro variable and a data step variable? Macro variables are defined and used in the macro language (outside of the DATA step) ...

SAS Clinical Interview QUESTIONS and ANSWERS

- November 03, 2008

SAS Clinical Interview Questions and Answers SAS Clinical Interview Questions and Answers Here is a list of common SAS clinical interview questions along with example answers and explanations to help you prepare for your next interview. 1. What is SAS? SAS stands for Statistical Analysis System. It is a software suite used for advanced analytics, business intelligence, data management, and predictive analytics. It is widely used in clinical trials for analyzing clinical data. 2. What are the phases of clinical trials? The phases of clinical trials include: Phase I: Tests safety and dosage with a small group of healthy volunteers. Phase II: Tests efficacy and side effects with a larger group of patients. Phase III: Confirms effectiveness, monitors side effects, and compares with other treatments in larger patient groups. Phase IV: Conducts post-marketing studies to gather additional inf...

SDTM Programming Interview Questions and Answers

- August 31, 2024

SDTM Programming Interview Questions and Answers 1. What is SDTM, and why is it important in clinical trials? Answer: SDTM (Study Data Tabulation Model) is a standardized format for organizing and submitting clinical trial data to regulatory authorities, such as the FDA. It is important because it ensures that data is structured consistently across studies, facilitating data review, analysis, and submission. 2. What are the key components of an SDTM dataset? Answer: The key components of an SDTM dataset include: Domains: Specific datasets like DM (Demographics), AE (Adverse Events), LB (Laboratory), etc. Variables: Each domain has standard variables such as USUBJID (Unique Subject Identifier), DOMAIN, VISIT, and others. Value-Level Metadata: Defines the structure and content of the variables. Controlled Terminology: Standard terms and codes used in SDTM datasets. 3. What is the purpose of the DM (Demographics) domain in SDTM? Answer: The DM domain in SDTM provi...

Understanding EC vs. EX Domains in SDTM: When to Use Each

- September 10, 2024

Understanding EC vs. EX Domains in SDTM: When to Use Each Understanding EC vs. EX Domains in SDTM: When to Use Each In SDTM, the EC (Exposure as Collected) and EX (Exposure) domains are both used to capture data related to drug or therapy exposure, but they serve different purposes depending on how the exposure data is collected and whether the study is blinded or unblinded. Key Updates from PharmaSUG Papers: PharmaSUG 2017 Paper DS08 introduces the historical context of the EC domain, which was established in SDTMIG v3.2 to support the EX domain by providing detailed traceability for exposure data. EC helps capture deviations, titrations, and other variations from planned dosing, especially when the collected data doesn't match protocol-specified dosing. PharmaSUG 2022 Paper DS121 emphasizes the importance of capturing dose modifications using the EC domain, which often occurs in oncology trials. By utilizing EC, sponsors can accurate...

Macro Debugging Options:MPRINT, MLOGIC, SYMBOLGEN, MACROGEN, MFILE

- August 13, 2009

Macro Debugging Options: Debugging a macro code isn’t easy process. It is difficult to identify the problem in the SAS code just by seeing the ERROR message in the LOG file. It is lot easier to debug a macro if we use the following SAS options. There are four system options that are helpful in debugging SAS Macros: SYMBOLGEN, MPRINT, MLOGIC, and MFILE. Each option adds different information to the SAS LOG File. Like any other SYSTEM OPTIONS, you turn these on using the OPTIONS statement: Options macrogen symbolgen mlogic mprint mfile; You can turn them off by specifying the following OPTIONS statement: Options nomacrogen NoSymbolgen nomlogic nomprint nomfile; Both statements are needed in side SAS. Once you set any option and it will remain in effect throught the SAS session. So if you want to debug the macro use first OPTIONs Statemnt else use 2nd one. Let’s look at each option, and the output they produce in more detail… MPRINT: As we know that when we execute...

Developing the DC (Demographics as Collected) SDTM Domain

- September 01, 2024

Developing the DC (Demographics as Collected) SDTM Domain Developing the DC (Demographics as Collected) SDTM Domain: Tips, Techniques, Challenges, and Best Practices Introduction The DC (Demographics as Collected) domain is a specialized SDTM (Study Data Tabulation Model) domain designed to capture demographic data as it was originally collected in clinical trials. This domain is particularly valuable in studies that involve multiple screenings or re-enrollments, where maintaining the integrity of the collected data is crucial. Unlike the DM (Demographics) domain, which provides a standardized summary of demographic data, the DC domain preserves the raw, unstandardized data, ensuring accurate data representation. This article delves into the key aspects of developing the DC domain, including the challenges, best practices, and the critical differences between the DC and DM domains. We also integrate insights from industry pa...

Common P21 SDTM Compliance Issues and How to Resolve Them

- December 06, 2024

Common P21 SDTM Compliance Issues and How to Resolve Them Common P21 SDTM Compliance Issues and How to Resolve Them By Sarath Annapareddy Introduction Pinnacle 21 (P21) is a cornerstone for validating SDTM datasets against CDISC standards. Its checks ensure compliance with regulatory requirements set by the FDA, PMDA, and other authorities. However, resolving the issues flagged by P21 can be challenging, especially for beginners. This post dives into common P21 compliance issues and provides actionable solutions with examples. 1. Missing or Invalid Controlled Terminology Issue: P21 flags variables like LBTESTCD or SEX as non-compliant with CDISC Controlled Terminology (CT). This happens when values in your datasets are o...

7 Mistakes in LB Unit Conversion That Still Show Up in SDTM

- April 09, 2026

7 Mistakes in LB Unit Conversion That Still Show Up in SDTM | StudySAS LB unit conversion is not hard to understand. The variable definitions are clear. The model is well-documented. And yet unit-related problems remain among the most common issues in SDTM submissions — not because teams do not know the rules, but because the failures are quiet. Nothing crashes. The dataset looks valid. Pinnacle 21 returns a clean report. Then a reviewer runs a simple cross-tabulation and finds creatinine flagged HIGH at a value that belongs well within the normal range — because the reference range was never converted to match the standard unit. This post is a close look at seven implementation mistakes, each with enough context and worked examples to make the failure mode visible before it reaches a submission. LBORRES is what was collected. Verbatim. Untouched. LBSTRES* is the standardized representation. One unit per test. LBSTNR* must follow the same unit system as LBSTRES*. T...

Clinical SAS Programming Interview Questions and Answers

- August 31, 2024

Clinical SAS Programming Interview Questions and Answers Clinical SAS programming is a specialized field within SAS programming, focusing on the use of SAS software in clinical trials and healthcare data analysis. Below are some common Clinical SAS programming interview questions along with suggested answers to help you prepare for your interview. 1. What is Clinical SAS, and why is it important in clinical trials? Answer: Clinical SAS refers to the use of SAS software in the analysis and reporting of clinical trial data. It is important because it enables the transformation of raw clinical data into meaningful insights that can be used for regulatory submissions, safety reporting, and decision-making in drug development. Clinical SAS ensures compliance with industry standards like CDISC and helps in generating accurate and reproducible results. 2. What are the CDISC standards, and why are they important in Clinical SAS programming? Answer: CDISC (Clinical Data Interchange St...