The Automated Metadata-driven Table Generation
Contents
1. 65 years gt 65 years 13 61 9 8 36 1 21 55 2 22 5 56 0 37 0 69 0 21 88 14 66 7 7 33 3 8 61 5 3 36 5 6 75 0 2 25 0 12 48 0 13 52 0 25 53 6 16 8 53 0 44 0 63 0 20 87 20 80 0 5 20 0 11 91 7 1 6 3 9 69 2 4 30 8 10 41 7 14 58 3 24 56 1 19 0 55 5 43 0 71 5 19 87 15 62 5 9 37 5 13 54 2 11 45 8 24 52 5 20 4 50 0 40 0 65 5 21 90 18 75 0 6 25 0 10 76 9 3 23 1 6 72 7 3 27 3 Page 1 of 1 N number of subjects randomized and dosedin the safety analysis set Percentages based on number of subjects of each sex Program home nlyon ifigen_training exercise tables program t dm sum pas sas Output t74 02 001 001 dm sum pas rtf Date Generated 25AUG15 07 45 42 Source adam adae 11 PhUSE 2015 TFLGEN PROCESS FLOW Run the TFLGen application specifying the PI to use Terminate TFLGen and No PI pass Program issue message to validation Index Pl console Yes Create a SAS datasets for he Se gt anha metadata in the PI heti are Create short SAS program for every output requiring generation Run all programs concurrently on SAS Grid Template for maximum efficiency ite Templa metadata Compiled metadata dataset Validate metadata dataset Vietadata Save metadata dataset Is metadata Yes dataset already No to analysis level dataset valid k exist permanent libra2. a drop down list of all table template locations in the Template Locations worksheet Template names the table template providing the statistics metadata Sort Section lists the sections within the table template that require sorting based on counts Sort Source Treatment lists the treatment columns to supply counts to sort sections within the table template Body Font Height specifies the font size to use Orientation of the page for the output Allow Code Generation prevents SAS program being inadvertently overwritten Safety Analysis Set Female Subjects Only trtemfl Y safety therapeutic_area t ae pt 1 321 10 Portrait Yes All Randomized Subjects aus Ea primary EETA H Yes Primary Analysis Set Male subjects Only safety product Portrait Safety Analysis Set Subjects with Anemia at Baseiin protocol 10 TABLE TEMPLATE The table template is the name given to the new Excel workbook containing the metadata that describes the Statistics in the main body of the table The metadata is split into 3 sections 1 General metadata that is applicable to the whole table described by the table template 2 Column label metadata that describes what information will be displayed in leftmost and treatment columns 3 Main body metadata that describes the statistics and their formatting As mentioned earlier there are 2 types of table tiered and base Below are examples of both they have the same General metadata items sps_generate_module cont
3. PhUSE 2015 Paper TS08 The Automated Metadata driven Table Generation Process TFLGen at Amgen Inc Neil Lyon Amgen Inc Uxbridge UK ABSTRACT Every day near identical programs are written by countless programmers to create similar tables They have been created in this manner for the last 20 years sometimes with macros sometimes re using code but always by manually editing SAS programs Amgen recently developed a suite of single purpose modular SAS macros and wondered if there was a better way to use them rather than having users learn what they do and then manually inserting them into code The solution is the metadata driven automated table generation process TFLGen By breaking tables down into their components areas of repetition were identified and metadata then used to describe each component in a single place simplifying the process and optimizing re use Using familiar intuitive user interfaces to supply this metadata the time to create and update table producing SAS programs was reduced INTRODUCTION Amgen has a suite of standard end to end macros to produce our most common outputs They were written over a decade ago and have been modified in the intervening years to add more functionality These macros have grown rather large and have become hard to maintain The macro that produces tiered summary tables has 9554 lines of code a 60 page user manual requires a user to specify up to 76 input parameters and produces a lo
4. able Template Formatting Metadata PhUSE 2015 IMPLEMENTATION EXTENDING THE PROGRAM INDEX To store the analysis level metadata the following new worksheets were added alongside the main worksheet that lists all outputs These new worksheets are described below Populations Contains metadata that describes all populations used in the analysis Population name Safety Analysis Set saffl Y Where Clause describing the population with a SAS expression Primary Analysis Set pasfl Y All Randomized Subjects n randdt Subsets Contains metadata that describes all subsets of populations used in the analysis Subjects with Anemia at Baseline lt blhgb lt 10 Subset name Male subjects Only sexn 1 Where Clause describing the subset with a SAS expression Female Subjects Only sexn 2 Treatment Column Headers Contains metadata that describes the different sets of treatment colunms used within the tables in an analysis Header name attributed to a row to describe which treatment header set it belongs to Span Labels are labels that span multiple treatment columns Treatment order that columns are to appear in Column Label to apply above the statistics in the treatment columns Data Set that can be used to describe the treatment columns Variable present on the dataset whose values are used to describe the treatment columns Quantifying value of the variable that describes the treatment columns Where Clause to describe treatm
5. adam adae 10 Treatment Emergent Adverse Events by System Organ Class and Preferred Term Total N 99 n 84 84 8 36 36 4 T 71 5 5 1 5 5 1 4 40 33 33 3 3 3 0 30 30 3 9 9 1 4 40 4 40 3 3 0 29 29 3 8 8 1 Page 1 of4 000 PhUSE 2015 BASELINE DEMOGRAPHICS Analysis level metadata header primary Comparator 1 10 mg adam ads tt01an 1 1 C primary Comparator 2 20 mg adam ads tt01an 2 1 C primary AMG Active 3 5mg adam ads trt01an a 1 C primary AMG Active 4 10 mg adam ads _trt01an 4 1 C Table shell metadata METADATA TREATMENTS STATISTIC INDENT DATA SET VARIABLE QUANT WHERE CLAUSE DENOMINATOR BY DISPLAY VARIABLE a x xx npercent 1 adamadsi sexan 1 o oo x x x _jnpercent 1 adamadsi sexn_ 2 EA o x nt fadamadsi age J Joo xx xx meanstdev 1 adam adsi age J xx median 1 fadam adsi age J Joo ooo xxxx gigs 1 fadam adsi age J Jooo xx minmax 1 adamaadsi age J J ZA xxx npercent_ 1 fadam adsi lt ages65 x x x npercent_ 1 adam adsi _ age gt 65 J O adam adsi _sexn ee ae x xx npercent 2 adam adsi lt age lt 65 sexn gt x x x npercent_ 2 adam adsi _ age gt 65 sexn gt Table 14 2 1 1 Baseline Demographics Primary Analysis Set Mean SD Median Q1 Q3 Min Max Male subjects n lt 65 years gt 65 years Female subjects n
6. age of its concise and robust XML processing capabilities a Groovy application was written that reads the Program Index metadata file creating a short program for each output that TFLGen is required to run for These programs run concurrently and for each output will generate a dataset of the compiled metadata The metadata dataset is then validated for appropriateness and if passed is used to generate the SAS program that once run will produce the required output The application has several options so that users can target specific outputs all outputs created using a single table template or all outputs within the Program Index When TFLGen has finished running it provides the user with a message in the UNIX console that informs the user whether it was successful or if there were errors Error messages PhUSE 2015 are designed to pinpoint the exact location of any problems helping the user to correct any mistakes The screenshot below shows a typical report with a successful generation followed and another that has issues with some metadata TFLGen Metadata Generation Report PI nhome niyon tfigen_training exercise docs pi PHUSE PI working xism Mode CREATE Date 26 Aug 2015 01 24 20 Requested Template ALL Requested TFLs ALL TFL Details 14 6 2 1 t ae soc pref saf rtf Allow Code Generation Yes Template hom NOTICE Metadata data set does not currently exist NOTICE Metadata data set requires generation NOTICE SAS prog
7. ains the keyword for this type of table template section_wrap_flag describes whether sections will be allowed to wrap over multiple pages Column label metadata items col_width specifies the width in inches of the leftmost column in the table col_align specifies the alignment left center right of the leftmost column in the table col_big_n_label specifies whether or not the big N are to be displayed in the treatment columns col_n_pct_label specifies the label underneath the big N that shows what statistics are being presented Tiered Table Template METADATA TREATMENTS STATISTIC INDENT DATA SET VARIABLE SORT SECTION SORT DIRECTION table tiered 001 System Organ Class line Preferred Term 0 adam adae descending n percent descending Main body metadata METADATA uses keywords from a drop down menu to describe the metadata present within the row In this example the evel_n specifies the tier level for the hierarchical statistics blank_row shows where a blank row will be inserted in the table T1 is the text that is to be displayed in the leftmost column in the table In tiered tables the values for rows where METADATA is evel_7 or greater will be replaced with the actual values from the variables specified in VARIABLE O1 PhUSE 2015 TREATMENTS describes how statistics are displayed the trailing x after a showing the decimal precision STATISTIC uses keywords from a drop down list to specify the statistics that
8. allows the creation of work datasets that would have the data needed for reporting 7 PhUSE 2015 Base Output Name on main Program Index worksheet that custom code is to be used with allows wildcards Custom Init Code to Include at Start of Program is field where SAS code can be entered which can include calls to external user developed macros t ae Get MedDRA version number data null set adam adae keep aemeddra obs 1 call symputx meddrav aemeddra G run HOW TO QC PROGRAMS GENERATED BY TFLGEN TFLGen is a fully validated software suite whose results can be trusted to reliably generate the numbers as per the metadata compiled in the metadata dataset Initially we allowed programmers to review the metadata dataset and the RTF output This was a cumbersome task as the SAS datasets are not always the easiest files to review To simplify this process TFLGen now creates a pseudo table in the same folder that contains an output s metadata data set Below is a screenshot of a typical file TFLGen adds the red text that shows what metadata is used and the that shows what metadata has changed since the metadata dataset was last created Table 14 7 1 1 Baseline Demographics Primary Analysis Set Population pasfl Y Comparator 10 mg 20 mg adam adsl adam adsl trt01an 1 trt01an 2 N xx N xx 10 mg adam adsl trtO1an 4 N xx 5 mg adam adsl trt01an 3 N xx drop_zero_row_flag N
9. are to be displayed INDENT shows how many times the T1 field is to be indented DATA_SET specifies the dataset that will provide the variable from which the statistics will be derived VARIABLE specifies the variable that statistics will be derived from SORT_SECTION identifies parts of the table that can be sorted based on counts in the treatment columns SORT_DIRECTION specifies the direction the sort should use Base Table Template METADATA TREATMENTS STATISTIC INDENT DATA SET VARIABLE QUANT WHERE CLAUSE DENOMINATOR BY DISPLAY VARIABLE 0 x xx npercent_ 1 adam adsi sexn 1 J o y x x x npercent_ 1 adamadsi _sexn J 2 o ooo 0 o ox n tt fadamadsi age J Joo xx xx meanstdev 1 adam adsi age J o y xx median 1 fadam adsi age xxxx gigs 1 fadam adsi age Jo o y xx minmax 1 adam adsi age S lt age lt 65 E EE x xx npercent 1 adam adsi lt age lt 65 x xx npercent age gt 65 lt age lt 65 lt age lt 65 sexn gt age gt 65 sexn gt jadam adsl _sexn Main body metadata METADATA uses keywords from a drop down menu to describe the metadata present within the row In this example the label specifies the row will have a text label but no statistics blank_row shows where a blank row will be inserted in the table statistic shows that the row will display statistics by start and by_end identify the start and end point f
10. eloping a product that creates these reports we required a detailed understanding of the structure of various tables The first step was to break down a selection of tables into their components THE ANATOMY OF A TABLE Each table component was analyzed and categorized into distinct types that could be described using metadata The figure below highlights some commonly occurring components and the categories they were assigned to Table 14 2 1 1 Baseline Demographics Primary Analysis Set Titles U O Comparator AMG Active 10 mg 20 mg 5mg 10 mg Footnotes 2 Cc N 21 N 25 N 24 N 24 J File names O m 13 61 9 12 48 0 10 41 7 13 54 2 Font size 8 38 1 13 52 0 14 58 3 11 45 8 Page orientation 21 25 24 24 gt Mean SD 55 2 22 5 53 6 16 8 56 1 19 0 52 5 20 4 n pr a Ap itp Population and subsets 5 37 0 69 0 440 630 43 0 71 5 40 0 65 5 ane eg See Treatment column headers S Input file locations T r lt 65 years 14 66 7 20 80 0 15 62 5 18 75 0 Output file locations 2 65 years 7 33 3 5 20 0 9 37 5 6 25 0 v 65 ot 8 61 5 11 91 7 6 60 0 10 76 9 Statistics gt 65 years 5 38 5 1 8 3 4 40 0 3 23 1 Decimal precision Pp gt Female subjects n La bels y Oo lt 65 years 6 75 0 9 69 2 9 64 3 8 72 7 0 gt 65 years 2 25 0 4 30 8 5 35 7 3 27 3 By processing D Page 1 of 1 Blank rows N number of subjects randomized and d
11. ent groups using more complex SAS expressions Column Width in inches Column Alignment is left center or right safety 1 Comparator adam adsl trt01an in 1 2 1 C safety 2 AMG Active adam adsl trt01an in 3 4 1 C safety 3 Total adam adsl tt01an in 1 2 3 4 1 C primary Comparator 1 10 mg adam ads tt01an 1 1 C primary Comparator 2 20 mg adam ads tt01an 2 1 C primary AMG Active 3 5mg adam ads tt01an 3 1 C primary AMG Active 4 10 mg adam adsi tt01an 4 1 C Template Locations Contains metadata that describes where the sources of the table shell specific information table templates are located Template Location name UNIX Directory for each of template location therapeutic_area nome therapeutic_area docs templates product nome stherapeutic_area product docs templates protocol nome therapeutic_area product protocol docs templates General Information Contains the remaining metadata that has not been captured in any other location It describes the file locations needed by the generated SAS program the subject variable used in the analysis locations for any macros that may be requried by the programmer and file locations for any dataset libraries that are needed Item is a keyword that describes the metadata stored in the row Description of the metadata item Value to be assigned to the metadata item table_program_dir File location for table programs home therapeutic_area product protocol analysis tables program table_metadata_d
12. ep the output specific information separate from the SAS program so is a widely understood tool Analysis level As each analysis already has its own Program Index it seemed logical to extend the workbook to include the analysis level information Table shell The remaining table shell information comes from components that describe the statistics and their presentation This information is supplied from the statistician to the programmer by a TFL shell Word document The inset below shows a typical demography table shell it uses a grid structure to hold all the information To simplify the transcription of table shell information into metadata we wanted to mimic the shell structure in the metadata storage solution The requirements for the storing and editing of the table shell information are e Grid structure Baseline Demographics e Edit cells e Move copy delete insert rows e Provide pre filled drop down lists e Apply conditional statements to cells e Export the contents to XML Female Age years Excel provides the vast majority of these requirements so it was used to n develop the working prototype Paired with Visual Basic it has the capability Mean SD to cover all the requirements pea Min Max It was decided to use XML as the transport format for the metadata It is a insisted bles much more flexible format than the plaintext that was originally used by the 2 e5 yaara i Program Index By decoupling the user inter
13. face from the underlying 265 years TFLGen application changes can be made to either part much more easily 275 years USING THE METADATA All the metadata are compiled from each source into a single SAS dataset that reflects the structure and content of the table being produced and describes how the output will be displayed The metadata dataset is then passed through a series of macros that read the contents and write SAS code to generate the statistics apply the formatting and then produce the report This metadata dataset has several advantages 1 The metadata dataset can be reviewed to validate the table 2 The metadata dataset can be merged onto the statistics that get derived in the generated program to access the formatting information This saves hardcoding the information into the generated SAS program 3 By separating the formatting and labelling elements from the SAS program changes can be made just to the SAS dataset that will not require a change to the SAS program However fundamental changes to the output such as new statistics will require both the SAS dataset and SAS program to be updated 4 The metadata dataset can be fed through a macro that will validate the contents for appropriateness e g a mean can only be calculated on a numeric variable The process flow now looks like that in the diagram below x ie Sy J Program Index ie SAS Program Ros W aan en g S Xa pe TFLGen N A RTF Table T
14. g that can grow to over 100 000 lines In response to this problem all processes required to produce a table were identified and refactored until the lowest common actions were found SAS macros were written to perform these actions The macros are then combined and built upon to form a suite of modular macros that can be used to build any table This generated many macros that would require users to understand and use correctly not the easiest of tasks To simplify the use of these macros a WYSIWYG interface was conceived that would allow users to describe the statistics they required using metadata and SAS terminology This paper will describe how Amgen approached the problem and how the solution was designed and implemented together with examples of some commonly produced tables EXISTING TABLE GENERATION PROCESS Every analysis at Amgen has a master list of all TFLs that are required called the Program Index The Program Index is an Excel spreadsheet that has one row for every output storing information such as the output number titles footnotes output and program names alongside details of the programmer tester and the testing status When saved the Program Index makes a plaintext version of itself Program Index Plaintext RTF Table SAS Programmer SAS Program The SAS programmer writes a SAS program to generate format and report the necessary statistics utilizing macros where applicable to generate the output When t
15. he SAS program is run it reads in the plaintext version of the Program Index and extracts the information from the row that has been identified within the program This information is added prior to the reporting stage PhUSE 2015 The screenshot below shows the typical output specific information that is currently stored within the Program Index a e gt R E A 14 2 1 1 Baseline Demographics line Primary N number of subjects randomized and dosed in the t14 02 001 001 dm sum pas rtf t dm sum pas sas Analysis Set safety analysis set line Percentages based on number of subjects of each sex 14 6 2 1 Treatment Emergent Adverse Events N number of subjects randomized and dosed inthe t14 06 002 001 ae soc pref saf rif t ae soc pref saf sas by System Organ Class and Preferred safety analysis set_ line Coded using MedDRa Term line Safety Analysis Set version amp meddrav REQUIREMENTS Prior to starting work on a solution the high level requirements that would drive the design of the solution were identified 1 Leverage the new modular macro library that was created to replace the ageing standard macros 2 Maximize the re use of information reducing duplication of effort 3 Minimize the information that is supplied 4 Create a tool that is flexible enough to produce as many commonly produced tables as possible 5 Have a simple to use intuitive interface DESIGN The end product of TFLGen is a tabular RTF report Before dev
16. ir File location for table metadata sets home therapeutic_area product protocol analysis tables metadata table_bpdf_dir File location for table BPDFs home therapeutic_area product protocol analysis tables validation table_output_dir File location for table outputs home therapeutic_area product protocol analysis tables output subject_var Name of the subject patient variable usubjid custom _init_macro_dir1 First location searched for custom macros home therapeutic_area product protocol analysis utilities custom_init_macro_dir2 Second location searched for custom macros home therapeutic_area product utilities adam_dir Fiel location for ADaM data sets nome therapeutic_area product protocol analysis statdata adam PhUSE 2015 Linking the Metadata to an Output The metadata described in the extended Program Index needs to be linked to each output The primary page that lists all outputs and contains the titles footnotes etc was extended so the new metadata can be selected Where possible the fields use drop down lists that are dynamically generated from metadata names in the new worksheets Population has a drop down list of all populations described in the Populations worksheet Subset has a drop down list of all subsets described in the Subsets worksheet Numerator Where SAS expressions limit all data reported in the table does not affect big N Header has a drop down list of all headers described in the Headers worksheet Template Location has
17. or a section that contains by processing T1 is the text that is to be displayed in the leftmost column in the table The keyword BY_DISPLAY_VARIABLE will be replaced at run time by the values present in the variable specified in the BY_DISPLAY_VARIABLE allowing dynamic text generation TREATMENTS describes how statistics are displayed the trailing x after a showing the decimal precision STATISTIC uses keywords from a drop down list to specify the statistics that are to be displayed INDENT shows how many times the T1 field is to be indented DATA_SET specifies the dataset that will provide the variable from which the statistics will be derived VARIABLE specifies the variable from which statistics will be derived or if SPS_META by_start then it provides the variable that the by processing will use for sorting QUANT specifies the particular value of VARIABLE for which to calculate the categorical statistics WHERE_CLAUSE takes a SAS expression that is used for complex descriptions of data to present categorical statistics for or to limit the data being reported in univariate type statistics DENOMINATOR takes a SAS expression describing alternative denominators to the big N for percentages BY DISPLAY_VARIABLE when SPS_META by start it provides a variable that the by processing can use for displaying in the label on the leftmost column of the table RUNNING TFLGEN Amgen uses SAS Grid installed on a UNIX server To take advant
18. osed in the safety analysis set Percentages based on number of subjects of each sex Program home niyon tigen_training exercise tables programs dm Sum pas Sas 4 02 001 U01 dm sum pas fit Date ed enera J 15 07 45 42 Source adam adae Three distinct component types and their metadata were identified e Output specific components many of which are already stored within the Program Index e Analysis level components that can be repeatedly used by many tables within an analysis e Table shell components that can be used by several outputs in an analysis or even across analyses but are combined with different analysis level and output specific metadata e g a demography table repeated for multiple populations Two distinct table types were identified tiered tables such as adverse events and concomitant medications and what Amgen call base tables containing non tiered categorical and univariate type descriptive statistics such as baseline demography and safety summaries by visit These table types will be referred to as tiered and base tables respectively PhUSE 2015 METADATA STORAGE SOLUTIONS Once the types of components were identified the metadata that would describe each component was designed and the optimal location for storing each metadata item decided Output specific It was decided to leverage the output specific information that already exists in the Program Index It is already used by all programmers at Amgen to ke
19. ram requires generation NOTICE Metadata data set has been generated NOTICE SAS program has been generated 14 2 1 1 t dm sum pas rtf Allow Code Generation Yes Template home niyon tfigen training exercise docs templsates phuse dm real xism Location Name protocol ERROR File ADAM ADXL DATA does not exist ERROR Template Row 31 DENOMINATOR sexn 1 is not valid when applied to the DATA_SET adam adxl ERROR Template Row 20 VARIABLE agex does not exist in the specified DATA_SET adam adsl ERROR Template Row 23 STATISTIC mn max contains the invalid value mn ERROR Template Row 31 DATA_SET adam adxl does not exist in the specified library ERROR Previous errors prevent metadata data set generation Please fix these errors and rerun TFLGen ERROR Previous errors prevent program generation Please fix these errors and rerun TFLGen Report created on 26 Aug 2015 01 24 20 by TFLGen version 01 02 00 DESIGN PROBLEMS AND SOLUTIONS TOO MANY NEAR IDENTICAL TABLE TEMPLATES BEING GENERATED It was found that many table templates were very similar to each other only differing by a couple of metadata items In a normal SAS program this would warrant the development of a macro to produce all similar tables with macro parameters allowing changeable values In order to reduce the number of table templates being developed the idea of changeable parameters was extended to the table templates If an item could be replaced across ver
20. roduction of simpler descriptive statistics NEXT STEPS TFLGen is not yet an optimized solution for Amgen There are some outputs that cannot yet be created with the application but should be possible with some minor changes We are looking to increase coverage and simplify the process with new features within the Program Index and table templates e There are multiple copies of the Excel table template file across the company We intend to simplify this by creating a single template editor that will import and export the XML version of the table template to and from itself This will enable users to always use the latest version of table template without needing to upgrade the table template and will make rolling out of new table templates simpler and more controlled e The functions of the base and tiered templates can be combined into a single table template enabling more complex tables to be created e Update table template to allow users to declare a variable that will contain the decimal precision such as can exist on the ADaM LB domain e Update table template to generate exposure adjusted event rates and exposure adjusted subject rates e Update table template to allow formats to be defined removing the need to specify the values to be displayed in the output PhUSE EXAMPLES ADVERSE EVENTS BY SYSTEM ORGAN CLASS AND PREFERRED TERM Analysis level metadata header safety 1 Comparator adam adsl trtO01an in 1 2 safety 2 AMG Ac
21. ry Yes No Save metadata dataset Are there No Ye to analysis level differences k permanent library Significant No Macros generate code to Yes Insert custom code Create population dataset Merge onto source data Use metadata dataset Derive denominators and big N to run the SAS Derive univariate statistics program generation Derive statistics macros Combine all statistics Apply formatting metadata Generate RTF table Create SAS dataset of the table template metadata Terminate individual program Compile relevant items from each metadata source into single metadata dataset Once completed all log files are searched for messages of interest TFLGen report CONCLUSION TFLGen increases standard macro code consistency maintainability reusability and extensibility through modularization It eliminates redundancy and its inherent risk in specifying input parameters by using centralized metadata Table templates can be re used both within and across analyses studies TAs QC requirements have been minimized metadata QC vs dual programming It increases resource portability between teams by providing a consistent framework for TFL production It is expected that TFLGen can be used to produce gt 65 of tables for a typical analysis In a test a single TFLGen user managed to generate 462 out 697 66 tables on a very large study in only 3 days These tables were prod
22. s of commonality were determined To avoid tramping macro parameters throughout the application to where they are utilized data sets were used to pass information across macros The different areas were distributed amongst the team to finish PhUSE 2015 e Changes to the Program Index and the new table template e Groovy application that sets up the area performs preliminary validation of the Program Index runs concurrent SAS jobs and generates report of successes and error messages e Metadata dataset generation e Metadata dataset validation e SAS program generation Data preparation Statistic derivation Applying formatting metadata to derived statistics Reporting O O O 0 Close contact was required amongst all developers to ensure that any changes that could affect another area were disclosed in a timely and efficient manner TESTING TFGLEN FOR ROBUSTNESS RELIABILITY AND VALIDITY When creating an application such as TFLGen it is essential that it runs without problems and generates the expected numbers every time To ensure that the software suite performs as expected every module undergoes an extensive unit test to ensure that its behavior follows the individual requirements and returns the expected results Once the whole software package was complete integration testing was performed to prove that the individual elements worked as a whole This involved creating Program Index and table templates that would test all the function
23. s that are available within TFLGen The results were dual programmed for validity Prior to full production roll out a limited production roll out tested TFLGen with a few handpicked studies to iron out any issues The outputs were dual programmed to further prove that the generated numbers were correct TFLGEN COVERAGE Currently TFLGen is expected to produce at least 65 of the tables in an analysis Demography Complex statistics Patient Disposition o Analysis of variance covariance Analysis Set Inclusion and Exclusion o Regression Baseline Characteristics o Binomial statistics Medical History o Kaplan Meier Protocol Deviations Treatment differences Safety Summaries by Visit Labs Vitals ECG Rates o Exposure adjusted event rates Adverse Events n ui o Exposure adjusted subject rates Concomitant Medications most tables with n or univariate statistics The next release of TFLGen will include these additional analysis types TFLGen is not expected to be able to produce all tables SAS is a highly flexible tool and as soon as any simplification of its use is attempted this flexibility is naturally reduced If TFLGen were designed to produce complex tables such as analysis of covariance it would require a much more complex and crowded table template which defeats the requirement of having a simple and intuitive interface To keep the application easy to use and maintain TFLGen has been deliberately limited to only attempt p
24. sions of a table then the changeable item would be replaced with a keyword prefixed with an ampersand amp similar to SAS macro variables A new worksheet was added to the Program Index that would allow the values to be specified When TFLGen runs it replaces all values that it finds in the metadata dataset that match the parameters specified in the Program Index Base Output Name on main Program Index worksheet that changeable parameter is for Parameter name specified in the table template e g amp level_O text Value to replace the parameter with Description of the parameter s purpose tae soc pref fas rif level O text an adverse event Text for top row of AE table t ae soc pref ser saf itf level 0 text a serious adverse event Text for top row of AE table t ae soc pref disc saf itf level 0 text an adverse event leading to discontinuation Text for top row of AE table USERS LIMITED TO USING DATASETS DIRECTLY FROM A LIBRARY TFLGen was originally conceived to use ADaM datasets that are normally considered as being one procedure away from the necessary statistics i e no processing or manipulation of data prior to deriving statistics In reality several ADaM datasets fall short of this goal and require processing prior to use or the creation of data driven macro variables To solve this problem another worksheet was added to the Program Index that would allow user specified code to be run at the start of the generated SAS program This
25. subject_var usubjid Sex n Male adam adsl sexn 1 Female adam adsl sexn 2 Age years n adam adslage Mean 3D adam adslage adam adsl age 01 03 adam adslage Min Max adam adslage Age n 5 65 years adam adsl lt age 65 2 65 years adam adsl age 65 Age by sex ladam adsl sexn subjects m lt 65 years adam adsl lt age lt 65 265 years adam adsl age 35 xX X X n percent x XX n percent x n X X X X mean stdeyv XX XX NX qi q x X min max X X X n percent X xx n percent x xx n percentisexn xX X X n percentisexn Page 1 of 1 N number of subjects randomized and dosed inthesafety analysis set Percentages based on numberof subjects of each sex Program t 0in surml pas sas Output t_dim_sum_pas nf Date Generated 254AUG6 175 07 44 30 Source adam adae DEVELOPING MANY INTERCONNECTED MACROS Due to the interconnectedness of the underlying macros used by TFLGen it was hard for multiple developers to work on modules and make decisions as they could easily have ramifications for parts that other developers were working on To get a handle on all the moving pieces one programmer oversaw the primary development putting initial versions of all the macros in place with all basic functionality present The connections where data is passed between macros and the XML files that come from the Program Index and the table template were identified and area
26. tive adam adsl trt01an in 3 4 safety 3 Total adam adsl trt01an in 1 2 3 4 Table shell metadata METADATA Ti table tiered 001 Sd System Organ Class line Preferred Term al x xx npercent 0 blank row leveld i level2 i TREATMENTS STATISTIC INDENT DATA SET VARIABLE SORT SECTION SORT DIRECTION __x xx npercent O adam adae aebodsys 1 descending __x xx _ npercent 1 Jadam adae aedecod 2 descending Table 14 6 2 1 Safety Analysis Set Comparator System Organ Class N 50 Preferred Term n Subjects experiencing an adverse event 41 82 0 Gastrointestinal disorders 17 34 0 Dyspepsia 4 8 0 Abdominal pain 0 0 0 Abdominal discomfort 4 8 0 Flatulence 1 2 0 Infections and infestations 19 38 0 Pharyngitis 3 6 0 Musculoskeletal and connective tissue disorders 15 30 0 Arthralgia 6 12 0 Myalgia 1 2 0 Muscle spasms 3 6 0 Rotator cuff syndrome 3 6 0 16 32 0 5 10 0 Cardiac disorders Angina pectoris N number of subjects randomized and dosed in the safety analysis set Coded using MedDRa version 16 1 Program Mome niyon figen_training exercise tables program t ae soc pref saf sas AMG Active N 49 n 43 87 8 19 38 8 3 6 1 5 10 2 1 2 0 3 6 1 14 28 6 0 0 0 15 306 3 6 1 3 6 1 1 2 0 0 0 0 13 26 5 3 6 1 Output t1 4 06 002 001 ae soc pref saf rtf Date Generated 25AUG15 08 55 24 Source
27. uced using 37 table templates The tables that could not be produced were efficacy tables that TFLGen was not designed to generate This was the first time these table templates were created For further analyses on the same product it is anticipated that many of them can be re used with no or little amendment further reducing the time to create the tables Feedback for TFLGen has been overwhelmingly positive with many teams reporting quicker table production and QC with further gains expected on future analyses as teams have more experience and a larger pool of pre constructed table templates ACKNOWLEDGMENTS would like to thank my colleagues Neville Cope Jack Fuller Benno Kurch and Chris St Peter for their invaluable help in designing and coding TFLGen would also like to thank David Edwards and Mark Stetz for their patience and support in bringing TFLGen to fruition CONTACT INFORMATION Your comments and questions are valued and encouraged Contact the author at Neil Lyon Amgen Inc Uxbridge Business Park Uxbridge UB8 1DH UK Work Phone 44 0 1895 525424 Email nlyon amgen com Brand and product names are trademarks of their respective companies 12
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