{"title":"Developing SAS® standard macros with variable argument techniques","authors":"Lei Zhang","doi":"10.1179/175709206X373019","DOIUrl":"https://doi.org/10.1179/175709206X373019","url":null,"abstract":"AbstractA macro that can take more or fewer arguments when it is called than formally declared is often referred to as a variable argument (or varargs) macro. The SAS® macro facility provides a basic mechanism for constructing a varargs macro. When properly developed, a single varargs macro can be used to solve arrays of problems of the same form all together in an orderly and uniform way, which can be especially valuable to the development of standard macros used in pharmaceutical programming. This article first describes the way to define a typical varargs macro using the option PBUFF in the %Macro statement, as well as two simulated methods. It then explores common calling conventions for varargs macros and various approaches to implementing varargs macros based on how individual arguments can be retrieved from varargs lists passed at runtime. In addition, the advantages and disadvantages of using varargs macros are briefly discussed, and the techniques are illustrated with various examples.","PeriodicalId":253012,"journal":{"name":"Pharmaceutical Programming","volume":"116 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129062953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Clinical-Data Acceptance Testing Procedure","authors":"S. Gupta","doi":"10.1179/175709206X372272","DOIUrl":"https://doi.org/10.1179/175709206X372272","url":null,"abstract":"AbstractWith the recent news from FDA to push tighter safety reviews due to increased patient deaths caused by Viox, pharmaceutical companies need to develop systems for early detection of safety and clinical data issues. In the pharmaceutical industry, there is a regulatory responsibility, 21 CFR Part 11, to analyze only the clinical data that have passed data acceptance testing or is considered 'clean data' after a database lock. Clinical data acceptance testing procedure involves confirming the validity of critical data variables as well as early identification of health risk issues. These critical data variables might need to be non-missing, consist only of valid values, be within a range, or be consistent with other variables. If incorrect clinical data are analyzed, then invalid study conclusions can be drawn about the drug's safety and efficacy.","PeriodicalId":253012,"journal":{"name":"Pharmaceutical Programming","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123696506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Implementing CFR 21 part 11 for SAS® without tears or joins","authors":"David J. Garbutt","doi":"10.1179/175709208X387003","DOIUrl":"https://doi.org/10.1179/175709208X387003","url":null,"abstract":"Abstract This paper argues that the best way to construct an easy-to-program in and CFR 21 part 11 compliant environment for SAS® programming is by using a version control system, specifically the IBM Rational product ClearCase®. It concentrates on architectural issues to do with protecting data and outputs as well as programs, and stresses the importance of linking an output with its constituent parts. The main reasons for using ClearCase® are explained and illustrated with examples from a successful implementation. Enough information about ClearCase® is included to show why it is uniquely suited, among all Source Code Management Systems, for this task. Although this paper focuses on SAS®, the environment can also be used for other programs with little or no changes.","PeriodicalId":253012,"journal":{"name":"Pharmaceutical Programming","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126534058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Workflow: defining, designing and building a programming process and version control system. Part II – requirements to production","authors":"G. Silva","doi":"10.1179/175709206X372308","DOIUrl":"https://doi.org/10.1179/175709206X372308","url":null,"abstract":"AbstractThere are a number of papers discussing the need for version control in the development of programs in the pharmaceutical industry. From version control packages with simple command line interfaces, such as CVS or RCS, to the more complex and graphical tools like Rational Rose®, programmers are told: there is a system out there to version your software, so do it! This is an important step in software development, but it is not the 'be all end all' for programmers. Since the industry insists on a review or 'QC' (quality control) step to ensure that the specifications of the statisticians are met by the code of the programmers, there needs to be the same system to allow for the flow of validated code from the programmer to the statistician to the 'final' or validated version of the code. This paper discusses the process that was originally used, a paper based system, and the evolution of our workflow from this paper based system, through a commercial application and into an internally built system. ...","PeriodicalId":253012,"journal":{"name":"Pharmaceutical Programming","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121614722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Case report form auto-annotation in PDF files using SAS® ODS XML tagsets","authors":"David M. Escobar","doi":"10.1179/175709206X372254","DOIUrl":"https://doi.org/10.1179/175709206X372254","url":null,"abstract":"AbstractCase report forms (CRF) are essential tools in clinical research, used to gather data during the course of a clinical study. A common and useful task of data management personnel is to annotate the CRFs with appropriate variable names from the study data dictionary. Various authors have written on the topic of using SAS® to automate the annotation of CRFs, but with different approaches. We utilize a metadata database and XML tagsets to create an XML forms data format (XFDF) file for use with Adobe® Acrobat® Standard 7·0. The XFDF file is built utilizing a SAS® macro with user-defined content; the XFDF file is then imported into a portable data format file (PDF) containing the CRFs and the annotations are manually placed in the appropriate locations on the page. This process significantly increases the efficiency of our data management activities during study start-up. We have decreased our annotation work effort from several days to a 3 hour period.","PeriodicalId":253012,"journal":{"name":"Pharmaceutical Programming","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125647102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Creating Macros for Survival Data in Oncology Study","authors":"Jagannath Ghosh","doi":"10.1179/175709206X372218","DOIUrl":"https://doi.org/10.1179/175709206X372218","url":null,"abstract":"AbstractIn this paper, we introduce some system functions and macros to create study specific survival variables for oncology clinical trials. We present five variables which show overall survival time, time to disease progression, duration of response, progression free survival and time to treatment failure for one particular study. We will be using survival analysis based on overall survival and censoring information. The purpose of this paper is to show the power and usefulness of SAS in clinical research, specifically studies which require time to event analysis based on death and survival information, such as cancer and HIV.","PeriodicalId":253012,"journal":{"name":"Pharmaceutical Programming","volume":"64 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114018264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Numeric length in SAS®: a case study in decision making","authors":"P. Gorrell","doi":"10.1179/175709208X334678","DOIUrl":"https://doi.org/10.1179/175709208X334678","url":null,"abstract":"Abstract This paper discusses various factors to be considered when making decisions regarding the properties of stored data. These factors extend beyond properties of the data files to include the context within which the data are used. Decisions about the stored length of numeric variables in SAS® data sets are used as an example of the decision-making process. Although the LENGTH statement in SAS is simple to use, what's going on behind the scenes is more complex, especially with respect to numeric variables. Understanding what happens when you specify the length of a numeric variable is essential for making informed decisions. SAS stores the value of all numeric variables in floating-point representation. This paper begins with a brief, practical, overview of floating-point representation and how it relates to programming questions regarding length, precision, and efficient use of disk space. We will discuss situations where numeric length should not be reduced, even if the range of integer values on ...","PeriodicalId":253012,"journal":{"name":"Pharmaceutical Programming","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132482368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A CDISC SDTM model for the medical device and diagnostic industry","authors":"Carey G. Smoak","doi":"10.1179/175709208X334632","DOIUrl":"https://doi.org/10.1179/175709208X334632","url":null,"abstract":"Abstract In May 2006, a CDISC SDTM Device sub-team was formed. This sub-team is made of industry experts, CDISC representatives and FDA representatives. This sub-team has been working on a model to fill-in the gaps in SDTM for medical device and diagnostic companies. The initial focus has been on developing a domain that would contain information (metadata) about devices and not on results from devices. The sub-team has come up with a model that is currently being reviewed by industry experts. The proposed model is based on a custom Finding Observation Class domain. The advantage of this proposed model is that it is simple and extensible.","PeriodicalId":253012,"journal":{"name":"Pharmaceutical Programming","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124043578","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Evolution and Implementation of the CDISC Study Data Tabulation Model (SDTM)","authors":"F. Wood, Tom Guinter","doi":"10.1179/175709208X334623","DOIUrl":"https://doi.org/10.1179/175709208X334623","url":null,"abstract":"AbstractThe Clinical Data Interchange Standards Consortium (CDISC) Study Data Tabulation Model (SDTM) is a standard for submitting data tabulations to the FDA in support of marketing applications. In July 2004, this standard became part of the FDA Study Data Specification referenced in the electronic Common Technical Document (eCTD) Guidance. This article will provide an overview of evolution and status of the SDTM and the associated Implementation Guides, commonly referred to as the Study Data Tabulation Model Implementation Guide for Human Clinical Trials (SDTMIG) and the Standard for Exchange of Nonclinical Data (SEND).","PeriodicalId":253012,"journal":{"name":"Pharmaceutical Programming","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130245862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}