Paper-less Reporting: On-line Data Review and Analysis Using SAS/PH-Clinical Software Eileen Ching, SmithKline Beecham Pharmaceuticals, Collegeville, PA Rosemary Oakes, SmithKline Beecham Pharmaceuticals, Collegeville, PA ABSTRACT The paper presents the applications of SAS/PH- Clinical in clinical trials reporting and analysis, and describes how clinical researchers can utilize its capabilities to analyze and explore the information with timeliness and efficiency during the drug development process. Since it is essential to extract useful information from the vast amount of data collected, statistical report generation is a representative and usually time-consuming activity in the world of clinical research and development. SAS/PH-Clinical, a data review and analysis tool developed by SAS Institute, provides the functionalities of a data browser, a query builder, as well as a flexible reporting system that is capable of creating templates which users can invoke and customize in a visual interface environment. Instead of receiving and reviewing reports printed on stacks of paper, the clinical scientists can view them on-line within the same system that is used for the generation of those displays. In addition, the paper discusses how a subset of an organization's internal reporting system can readily be developed into a Computer-assisted New Drug Application (CANDA). Coupled with concepts of data warehousing, practical and beneficial data querying and report generation tools can greatly shorten the development time and improve the quality of a drug submission. INTRODUCTION In the world of clinical research and development, vast amounts of data are collected for the support of clinical development plans. Currently, this is mostly a paper-based process. New tools are being developed by sponsor companies, as well as software companies, to provide on-line clinical data review and analysis in a user-friendly environment. These tools alleviate the cumbersome task of printing and eliminate the delay in the delivery of clinical trial analysis results. REPORTING OF CLINICAL TRIALS The reporting of clinical trials involves collection, review, and analysis of immense amount of data. Most of the data is captured on paper case report forms which is then entered into a database. Usually when the clinical scientist wants to examine data while the trial is ongoing, he/she must obtain either case report form copies or data listings from another group. Any queries or summarization of data must be performed by the programming and statistical staff. If new study populations or parameters are called for, then the programming staff must modify existing or develop new programs which cause delays in the review of result. Ordinarily, the study results are printed out and delivered as stacks of paper. Reports are not readily accessible from a user's desktop. Integrated reporting frequently requires the development of new programs because the existing software can not be easily used with the combined data. SAS/PH-CLINICAL Among the many efforts in the development of online reporting tools, SAS Institute has released SAS/PH-Clinical software (most recently version 2.03) which specializes in clinical reporting. The developers of this product are currently working with sponsor companies to enhance the functionality of this product. SAS/PH-Clinical provides the capabilities of a data browser, a query builder, as well as a flexible reporting system that is capable of creating templates which users can invoke and customize in a graphical interface environment. STUDY DEFINITION (DATA WAREHOUSING) A study in SAS/PH-Clinical is defined as a collection of SAS data sets. These data sets are not direct copies of the input database (e.g., Oracle). They contain data that are usually manipulated to expedite reporting. The methods of manipulation may include transposing, collapsing, and complex mapping of variables. In addition, the resulting data sets often contain derived and value-added variables such as age and days relative to start of 1
treatment. The variables from the input database that are not necessary for reporting are omitted. This reporting database is created based on data warehousing principles. Data warehouse takes the by-product transaction data and organize and store this data so the end-user can access and use it. Derived data points and summary data is of great importance to a clinical reviewer or report writer. Including this data in the reporting database also reduces complex calculation and data processing in generating the reports. DATA BROWSER Many times clinical has the need to review the raw data at any time during the clinical trial. SAS/PH- Clinical provides spreadsheet-like format for easily viewing raw data. The data is presented with variables as columns and observations as rows. Variables from individual data sets can be organized into variable groups of related data. Variable groups are created when the study is defined in SAS/PH-Clinical. Figure 1 displays an example of variables and variable groups for selection when using the data browser. Raw data can be selected from a group or across multiple groups. For example, if the user needs to view adverse experience (AE) data, he/she might also want to select certain demographic variables to provide a more complete picture. Figure 2 shows demography data displayed with AE data in the data browser. Figure 2 The software provides many useful options in the data browser that can be customized to individual preferences. For example, a user can hold or freeze certain columns so that they always appear on the screen when scrolling through the remainder of the columns or one can re-arrange the display order of the variables. The end-user is also able to create newly derived variables based on currently selected data. The browser also provides the ability to export data to other applications such as EXCEL and WORD. Another feature of the browser is the ability to execute simple summarization in tabular or graphical form. Figure 3 shows an example of a simple summary created for race. This can be accomplished effortlessly by press of a button without any programming support. Once a table of summary statistics is generated, the user can "drilldown" on a specific cell to see a list of observations which defines the cell. For example, in a race distribution table, one can double-click on the "# Patients" cell to display a list of patients for the selected race (see Figure 4). Figure 1 Figure 3 2
QUERY BUILDER Figure 4 In addition to browsing raw data, one may also wish to perform queries which result in data meeting certain criteria of interest. These queries can be easily built without knowledge of any programming languages. The criteria are defined by the user's selection of values that are made available by the system. For example, if the user wanted to view all adverse experiences for patients 18 years of age and over, then this query can be specified by selecting age from a list of variables, a '>=' (greater than or equal to) from a list of available operators, and finally entering '18' as the value of comparison (see Figure 5). Queries can be saved for later use, especially the more frequently used ones. delivered to clinical report writers in printed hardcopy. SAS/PH-Clinical provides the ability to generate and review reports all in the same environment. Reports are developed as PH- Templates which consist of writing SAS code and designing windows with graphical interface. The code section of a PH-Template contains macro-type methods of SAS programming. The graphical window is the front-end for the user to specify the parameters needed to run the reports. These windows contain widgets, such as text boxes, pulldown lists, radio buttons, checkboxes, and command buttons. All of these widgets enable the end-users to create their reports in a "point-andclick" fashion with minimal effort. Using PH- Templates, the statistical and programming staff can now write a single program that is flexible enough to create multiple reports of the same format. For example, one AE template can be used to produce summary tables by relationship to study medication or by AE severity. The same template can also produce tables containing different subsets of AEs (e.g., all AEs, those that led to withdrawal, serious AEs, etc.). An example of a template for AE summaries is provided in Figure 6. Figure 6 LIBRARIES Figure 5 The PH-Templates and the generated reports can be saved into libraries. Each library serves as a central repository for storage and on-line review of output for a particular reporting effort. Printed hardcopies are no longer needed for delivery. Figure 7 shows a library of template objects, and Figure 8 depicts a library of saved outputs. TEMPLATE DEVELOPMENT Traditionally, data summaries and analyses are generated by programming and statistical staff and 3
versatility of PH-Templates enables easy report creation on integrated data. As a result, less programming effort is required for an NDA which shortens the time it takes to prepare a submission. Moreover, this could lead to overall reduction of drug approval time. AREAS FOR IMPROVEMENT Although SAS/PH-Clinical is equipped with many powerful features, the pilot programs done at SmithKline Beecham have discovered some major areas which require further enhancement in addition to minor issues. These include: Figure 7 Figure 8 ELECTRONIC SUBMISSIONS Presently, many NDAs (New Drug Applications) are submitted to the FDA (Food and Drug Administration) in an electronic form. One important component of a CANDA (Computer Assisted New Drug Application) is the data review and analysis tool. SAS/PH-Clinical has many of the functionalities required of such a tool and it has been used by sponsor companies for submissions to the FDA. Most submissions involve integration across studies. Typically, combining multiple studies means development of new programs and/or mapping of data into a standard structure. In SAS/PH-Clinical however, since study definitions only allow one form of data structure, there is no longer a need to do additional mapping of data for an integrated effort. PH-Templates written for a single study report can be conveniently used for an integrated report without additional modifications. In order to generate a report using combined data, one only needs to open multiple studies. Therefore, the - Product administrative tasks need to be streamlined. In the current version, users cannot select a collection of objects and perform the same operation on them. For example, to create new version of report objects, each report must be deleted individually before the replacement report can be saved. The ability to group objects to perform tasks such as delete, copy to another library, and set property privileges is necessary for efficient reporting. - Detached batch processing is essential for a production system. The number and size of reports required for interim and final reporting necessitates detached processing capabilities. - Report template view and print functionality needs to be improved. In SAS/PH-Clinical version 2.03, page breaking is both display- and printer- specific. To view and print report output with the proper page breaking, the individual report page layout, the display monitor, and the specific printer all must be synchronized. This is a time consuming and repetitive task. - More user-friendly features are needed in the browser and template building environments. Certain user preferences set in one session cannot be saved for another session. Also, the current settings of toggled switches are not obvious to the user. - The software should allow for study-specifc formats (e.g., via format search). Often there are needs to have a study level format that contains values specific to that study. This currently is not allowed in the product. 4
All of the issues found from the SmithKline Beecham experiences have been communicated to SAS Institute and many of the enhancements requested will be implemented in the next release of the software, version 2.10. CONCLUSION SAS/PH-Clinical has many of the capabilities for paper-less reporting. Currently, with the help and feedback of sponsor companies, SAS Institute is continuing to make improvements to this product. Although there are limitations to the current version, the system has the potential to be an extremely useful tool for clinical trials reporting. List of Figures Figure 1 Variable Groups for a Study Figure 2 Browser Displaying a Selected Group of Variables Figure 3 A Summary of Race Variable Figure 4 Drill-down of One Race Value Figure 5 Query Window Figure 6 PH-Template Custom Window Figure 7 Folder Containing PH-Templates Figure 8 Folder Containing Save Output Objects TRADEMARK SAS and SAS/PH-Clinical are registered trademarks or trademarks of SAS Institute Inc. in the USA and other countries. indicates USA registration. Other brand and product names are registered trademarks or trademarks of their respective companies. AUTHORS CONTACT INFORMATION Eileen Ching SmithKline Beecham Pharmaceuticals 1250 South Collegeville Road PO Box 5089 Collegeville, PA 19426 Phone: 610-917-5056 E-mail: Eileen_L_Ching@sbphrd.com Rosemary Oakes SmithKline Beecham Pharmaceuticals 1250 South Collegeville Road PO Box 5089 Collegeville, PA 19426 Phone: 610-917-5057 E-mail: Rosemary_Oakes@sbphrd.com BIOGRAPHY Eileen Ching is a Clinical Applications Programmer/Analyst at SmithKline Beecham Pharmaceuticals responsible for clinical applications programming in clinical trials research and development. Her five years of industry experience includes SAS-based clinical and statistical reporting, applications design and development, and various drug submission support including CANDA project development. Rosemary Oakes, a Biostatistician at SmithKline Beecham Pharmaceuticals, is responsible for input into clinical study design, statistical programming and analysis, and interpretation of results for clinical drug development. Her six years of statistical experience includes statistical reporting methodology, SAS macro and report programming, SAS graphical data presentation, and statistical support of drug submissions to international regulatory agencies. 5