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WO1998012669A1 - Procede et dispositif pour traiter des bases de donnees d'essais cliniques - Google Patents

Procede et dispositif pour traiter des bases de donnees d'essais cliniques Download PDF

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Publication number
WO1998012669A1
WO1998012669A1 PCT/US1997/016629 US9716629W WO9812669A1 WO 1998012669 A1 WO1998012669 A1 WO 1998012669A1 US 9716629 W US9716629 W US 9716629W WO 9812669 A1 WO9812669 A1 WO 9812669A1
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WIPO (PCT)
Prior art keywords
data
user
module
create
submodule
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Ceased
Application number
PCT/US1997/016629
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English (en)
Inventor
Donald R. Kanter
Andrew L. Finn
William T. Sawyer
Hsieh Chao-Ying
Vincent P. Houser
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PHARM-DATA Inc
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PHARM-DATA Inc
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Application filed by PHARM-DATA Inc filed Critical PHARM-DATA Inc
Priority to AU44254/97A priority Critical patent/AU4425497A/en
Publication of WO1998012669A1 publication Critical patent/WO1998012669A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T11/00—2D [Two Dimensional] image generation
    • G06T11/60—Editing figures and text; Combining figures or text

Definitions

  • the present invention relates to databases and, more specifically, to a method of processing clinical trial databases for users without a background in statistics.
  • the present invention which in one aspect is a method for exploring, examining, and summarizing information contained in an electronic database. Furthermore, because the invention provides an interface between the non-statistician, non-programmer user and the database, the invention provides for real time examination of databases. The invention provides the user with the ability to create subgroups and subsets of the data, merge these identified subgroups, reclassify data contained in the database, and create summary reports, including tables and graphs, of the data
  • the invention includes a window-driven application designed for clinical data review.
  • This system is highly intuitive and user-friendly and provides a point-and-click menu-driven approach for reviewing, analyzing, and graphing clinical data
  • Potential users include FDA clinical reviewers of computer aided new drug applications and clinical staff at pharmaceutical companies
  • the invention permits clinicians to obtain information in a timely manner
  • the invention is designed to accommodate different database structures. It automatically recognizes character and numeric variables to create different inquiry statements, which are important for programmers and biostatisticians, but not for users
  • the invention shows formatted values and labels, instead of raw values, which have limited meaning to users It allows users to change variable and data set names into more descriptive names and to label the data sets and variables It validates the database structure to be used in different modules to avoid user mistakes It accommodates different types and names of key variables automatically for data merging once they are set up by an administrator
  • An administrator controls the information to be reviewed, including study protocol, drug name, and indication levels, establishes user identification, password, and working directories for each user, arranges data set and variable names to be used in the Adverse Event Module, and arranges a key variable for data merging and subgrouping This setup ensures system security and integrity
  • the user can perform complicated inquiries without writing any code with the SAS ® programming language. Traditionally, the user needed to know SAS programming, data format conventions, and database terminology in order to subset a data set in SAS With the Subgrouping Module, the user can extract data with criteria he sets up online. The user can also create a subgroup with only the subject identification list and can use the data joining function later
  • the Graph Module of the invention provides a way to create simple but informative graphs, which allows the user to graphically present data trends, to drill down for detail data listings or spot information, and to export the graphs into a lot of popular graphic formats such as bmp, ,gif, .pcx, etc.
  • the Table Module in the invention can be used to generate three types of summary tables. It provides descriptive statistics such as means, standard deviations, and number of observations.
  • the third style table module provides the option to count the number of patients or the number of observations in the output table.
  • Adverse Event Module allows the user to view adverse events by unique patient count instead of observation count. It also separates treatments, body systems, and preferred terms, and provides percent information by treatment for comparison between different treatments. Features like these that usually require extensive data manipulation and table programming are simple when using the invention.
  • the Reclassify Module provides a way of viewing the data from a different perspective. It translates data into a new grouping convention while maintaining format type. It automatically provides data range information such as maximum and minimum for numeric data and data values information for character data.
  • time wasted because of the necessity of involving a computer programmer to generate code for exploration of databases is avoided.
  • the invention does not require significant training of end users in biostatistics or computer programming.
  • FIG. 1 is a flow chart showing the organization of the user-accessible modules of one embodiment of the invention.
  • FIG. 2 is a block diagram of a hardware configuration upon which a disclosed embodiment of the invention may run.
  • the invention may be embodied in a software program running in a digital computer.
  • the complete source code for this embodiment is disclosed in the microfiche appendix, along with a user's guide that instructs the user how to operate all of the features of the embodiment.
  • the invention includes a series of program modules 10, or subroutines, each of which performs specific functions. These include a user login 20, and a select protocol module 22.
  • the user is allowed to select between a data explorer module 24, a patient information module 26 and an adverse events charting module 28.
  • the data explorer module 24 allows the user to select between a report and analysis module 30, a browse data module 32, a find variable module 34, a view files module 36, a subgroup and join module 38, and a reclassify module 40.
  • the report and analysis module 30 allows the user to select between a tables module 42, a listings module 50, a lab module 52, a statistics module 54, an INSIGHT module 56 and a graph module 58
  • the tables module 42 allows the user to select tables to be generated in one of three styles: a first style 44, as second style 46, and a third style 48.
  • the graph module 58 allows the user to select between a mean module 60, a frequency module 62 and a plot module 64.
  • the view files module 36 allows the user to select between a view files & tables module 70 and a view WordPerfect ® files module 72.
  • the subgroup and join module 38 allows the user to select between a create subgroup module 74, a join subgroup module 76 and a join data module 78.
  • the reclassify module 40 allows the user to select between a reclassify numeric variable module 80 and a reclassify character variable module 82 The functions associated with each of these modules is described below
  • the user login module 20 controls access to protocol data. Before a user can log into the system, an administrator must set up the user identification and password, and specify the authorized protocol data
  • the select protocol module 22 allows access to authorized protocols Clinical research in the pharmaceutical industry is usually separated into drug, indication, and protocol levels, and the invention is designed to follow these conventions An administrator must set up data access rights for each user for each specific drug, indication, and protocol. Only authorized protocols can be accessed by the users. The users do not have the right to delete or modify any raw or analysis data provided by the administrator, but the user can create any in-process data sets or export data into other formats for further data manipulations.
  • the data explorer module 24 provides the interface to the various modules that allow the user to manipulate clinical data. Of these, the report and analysis module 30 allows access to the primary clinical data display modules.
  • the tables submodule 42 is designed to create a variety of tables summarizing the data. Continuous variables can be summarized by a variety of statistics and can be grouped by class variables.
  • the user can create 2-way cross-classification tables and can choose whether or not to include missing levels of a class variable in a table.
  • Output from the tables submodule 42 can be customized by adding titles and/or footnotes.
  • the user has the option to change the table font, and can choose to present the date and time of the output, the page number, and the page size (portrait or landscape).
  • the tables can be saved and printed. There are three table styles to choose from labeled as first style 44, second style 46, and third style 48.
  • the first style table 44 is appropriate for summarizing continuous variables such as age, weight, and height. This style can be used to present up to 20 continuous variables with as many of the following statistics as the user wishes to present, number of non-missing, number of missing, range, sum, mean, variance, maximum, minimum, standard deviation, standard error of the mean, coefficient of variation, student's t for testing the null hypothesis that the mean is zero and the corresponding p-value, and corrected and uncorrected sums of squares. As an option the user can choose up to four grouping variables. This will create a separate table for each grouping variable combination.
  • the second style table 46 is appropriate for summarizing continuous variables such as age, weight, or height by classification variables such as race, sex, and treatment
  • This style can be used to present up to four continuous variables by two classification variables in a single table.
  • a classification variable is required for second style and a single table is created, rather than a separate table for each combination of classification variables as in the first style table.
  • the third style table 48 is appropriate for creating a 2-way cross-classification table such as treatment by race.
  • the table gives the frequency and percent of each combination of the classification variables. Percents can be presented as overall, row, or column percents. The user can choose up to two column classification variables and up to two row classification variables to be presented in a single table.
  • the graph submodule 58 is designed to create a variety of graphs summarizing the data. Output from the graph submodule 58 can be customized by adding a title and/or a footnote. Options such as title font are available in the menu bar. Available submodules included in the graph submodule 58 are mean 60, frequency 62, and plot 64.
  • the mean submodule 60 is designed to create horizontal and vertical bar charts, and 3D horizontal and vertical bar charts for one continuous variable, grouped by a classification variable. Subgrouping is also available. This submodule can be used to compare, for instance, the mean age between treatment groups, the mean age between genders, or the mean age between gender broken down by treatment groups. The output also includes the standard deviation of the response variable, as well as group frequency counts.
  • the frequency submodule 62 is designed to create horizontal and vertical bar charts, 3D horizontal and vertical bar charts, pie charts, and 3D pie charts.
  • the response and grouping variables must be classification variables. Subgrouping is also available.
  • the user can choose between patient counts or event counts.
  • event counts can be used.
  • the user can chose to present the graph as frequency counts or as percents.
  • the frequency submodule 62 can be used, for instance, to view the race distribution of subjects in a study, the gender distribution, or to view the race distribution among the treatment groups. One can compare the number of adverse events that occurred per treatment group, or the number of subjects who experienced an adverse event per treatment group
  • the plot submodule 64 is designed to create line, scatter, or needle plots
  • the plot submodule 64 can be used, for example, to create a scatter plot of baseline versus final lab values to visually show a trend or to reveal outliers
  • the user can click on the outlier point to reveal such information as the patient number corresponding to the outlier, the treatment group that the patient is in, the patient's sex, age, and the x and y coordinates of the point
  • the user can first create mean efficacy values by treatment and time using the statistics module 54
  • the plot submodule 64 can then be accessed from the statistics submodule 54 to create a line graph of efficacy values over time for each treatment group
  • the listings submodule 50 is used to create data listings in a desirable format and layout.
  • the variables listed in the output are limited and sorted by user specified variables The user has the option to subset the data before creating a list
  • Output from the listings submodule 50 can be customized by adding titles and/or footnotes, or choosing from other available options
  • the lab module 52 is used to view the laboratory data set This module provides a gateway to explore the functionality in LAB ® optionally implemented in some SAS ® products
  • the statistics submodule 54 is used to produce statistics for continuous data such as age, height, and weight Available statistics are number of non-missing, number of missing, range, sum, mean, variance, minimum, maximum, standard deviation, standard error of the mean, coefficient of variation, skewness, and kurtosis. Grouping is available in the statistics submodule 54.
  • the graph submodule 58 can be accessed from the statistics submodule 54 so that the user can produce, for instance, a bar chart comparing mean age among treatment groups or mean change from baseline in efficacy variables among treatment groups.
  • the user can also run the statistics submodule 54 to get mean efficacy values by treatment and time and then access the graph submodule 58 to create a line plot of mean efficacy values per treatment over time.
  • Output from the statistics submodule 54 can be customized by adding titles and/or footnotes. The user can choose to present the date and time of the output, the page number, and the page size (portrait or landscape).
  • the insight submodule 56 is used to view the data set under the INSIGHT ® module optionally implemented in some SAS products.
  • the browse data submodule 32 in the invention is designed to perform such functions as viewing, searching, sorting, saving , and printing data sets, and exporting data sets to an external file.
  • the user can create new data sets from existing data sets with such options as select variables to keep, select variables to drop, and rename variable.
  • the delete function allows the user to delete data sets he has created. Original data sets can not be deleted.
  • the find variable submodule 34 is used to identify the data sets that contain a particular variable.
  • the find variable submodule 34 includes the ability to view data sets, to sort data sets, to save sorted data sets, to print data sets, and to export data sets to another file format.
  • This module is linked to report & analysis submodule 30 and to the Browse Data Screen.
  • the Browse Data Screen is similar to the browse data module 32 but lacks the Delete function.
  • the view files submodule 36 is used to view output files and tables created in the invention, to view other ASCII files, and to view WordPerfect files
  • Two submodules are available in the view files submodule 36 view files & tables 70, and view WordPerfect ® files 72
  • From the view files & tables submodule 70 the user may view and print files and tables created in the invention and can choose options such as view font and page size (portrait or landscape)
  • the subgroup & join submodule 38 is organized into three groups create subgroup 74, join & subgroup 76, and join data 78 These modules are linked to the report & analysis submodule 30 and the patient information module 26 so that functions available in these modules can be performed directly from the subgroup & join submodule 38
  • the create subgroup module 74 allows the user to create a subset from an existing data set and save the subset for later usage For example, the user can create data sets containing all patients with adverse event equal to 'headache', containing only males, containing only those patients between 30 and 45 years of age, or a data set containing only males between the ages of 30 and 45
  • the join subgroup submodule 76 is designed to join a subgroup created using the create subgroup module 74 with another data set with the same key variable This allows the user to create a data set including only the subjects which were identified in the create subgroup module 74
  • the join data module 78 allows the user to join two data sets together, by a key variable The
  • the reclassify submodule 40 is used to create new variables from existing variables
  • the data set containing the new variables can be saved for later usage
  • the reclassify submodule 40 is linked to the report & analysis submodule 30 and the patient information module 26 so that functions available in these modules can be directly accessed from the reclassify submodule 40
  • Two submodules are available under the reclassify submodule 40 the reclassify numeric variable submodule 80 and the reclassify character variable submodule 82.
  • the reclassify numeric variable module 80 allows the user to reclassify numeric variables As an example, the user can create a new classification variable 'newage' by grouping the numeric variable 'age' into levels such as ⁇ 30, 30-45, and >45
  • the reclassify character variable module 82 allows the user to reclassify the variable according to the user's own grouping criteria The user can select a data set and variables from the screen. All the existing values of the variable will be displayed for the user. The user can group different values of the variable to create a new variable
  • the patient information module 26 allows the reviewer to browse the patient profiles
  • the Patient Information module also allows the user to view a subset of any data in the protocol, grouped by the subject identifier It can also be invoked from other modules to view only the patient information in the current file that the user wishes to work with
  • the adverse event module 28 allows the user to determine the frequency and percentage of patients with adverse events, grouped according to treatment, body system, and preferred term. It gets the information from an adverse event data set which was set up by the administrator, and displays the frequency and percentage values in an organizational chart format The chart has three levels treatment, body system, and preferred term. The module also provides the function to 'drill down' to a subset data set or to individual patient information
  • a minimum of 100 to 150 MB of free hard disk space are recommended. As the possibility of running multiple applications increases, the recommended minimum free hard drive space will increase commensurately too.
  • One representative hardware configuration that works well with the above-disclosed embodiment includes an Intel ® Pentium 90 MHZ CPU, a 256 KB cache, 64 MB RAM, 150 MB free hard drive space, and a super VGA 17" color monitor.
  • One embodiment of the system was developed under SAS ® System 6.11, and utilizes newly developed features like object oriented programming, data table object functions, and 'drag and drop' on-screen editing.
  • the SAS ® modules required for this application are SAS/BASE ® , SAS/CORE ® , SAS/AF ® , SAS/FSP ® , SAS/ACCESS ® , SAS/STAT ® , and SAS/GRAPH ® .
  • the invention provides the gateways to access SAS/INSIGHT ® and SAS LAB ® modules. Competing programs that use other programming languages require conversion of SAS ® data, which can cause errors. The invention eliminates this time-consuming and problematic step.
  • the SAS ® data sets are defined for the most effective and efficient use. Although users can do extensive manipulation on the data sets, analysis data sets with the appropriate structure and sufficient information are provided. This prevents the user from spending unnecessary time manipulating data instead of reviewing data.
  • Both of these data sets contain the same information, but each subject in the second table contains only one record, whereas several records may be assigned to each subject in the first table.
  • Some data displays, such as graphs, require data in the vertical layout, while others will require the horizontal layout. When both layouts are provided, then the user can select the one that is required and quickly create the table or graph of interest.
  • Every data set contains variables that are frequently needed to create tables, graphs or lists. Demographic variables, such as sex, race and age, as well as the treatment code, are included in every data set. This saves the user time because he or she will not need to merge data sets together to get the needed variables into one data set. Likewise, efficacy data sets and lab data sets contain the change from baseline value at each time point.
  • the type of patient sample used to create graphs or tables can vary.
  • safety tables such as adverse events, labs and vital signs may be created from the intent-to-treat safety sample.
  • Efficacy tables may be created from the intent-to-treat efficacy sample.
  • Indicator variables are included in every data set and can be used to extract the appropriate patient sample for the graph or table that the user wants to create.

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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Medical Treatment And Welfare Office Work (AREA)

Abstract

Un procédé et un dispositif facilitant l'étude de données cliniques fournissent une approche par pointer/cliquer et par menus, qui permet d'étudier, d'analyser et de représenter par des graphiques des données cliniques (30, 32, 34, 36, 38, 40). L'accès en temps réel aux informations cliniques contenues dans des bases de données électroniques permet aux cliniciens d'obtenir des informations en temps utile. L'utilisateur a la possibilité de parcourir les profils des patients (32), de faire des recherches de données, de reclassifier des variables numériques et de type caractère, de créer et d'analyser des sous-ensembles de variables (74), de créer des tables de résumés de base (42) et des affichages graphiques de données (58). L'invention élimine l'étape de conversion, problématique et coûteuse en temps. Elle permet d'exporter des bases de données statistiques dans des formats de données existants bien connus. Aucune expérience de la programmation n'est nécessaire pour utiliser ce système.
PCT/US1997/016629 1996-09-18 1997-09-18 Procede et dispositif pour traiter des bases de donnees d'essais cliniques Ceased WO1998012669A1 (fr)

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Application Number Priority Date Filing Date Title
AU44254/97A AU4425497A (en) 1996-09-18 1997-09-18 Method and apparatus for processing clinical trial databases

Applications Claiming Priority (2)

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US2632296P 1996-09-18 1996-09-18
US60/026,322 1996-09-18

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WO1998012669A1 true WO1998012669A1 (fr) 1998-03-26

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Cited By (6)

* Cited by examiner, † Cited by third party
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WO2002006826A1 (fr) * 2000-07-17 2002-01-24 Opt-E-Scrip, Inc. Essais de medicaments sur patient unique associes a une base de donnees cumulees
US6579888B2 (en) 1994-10-31 2003-06-17 Opt-E-Scrip, Inc. Method and kit for treating illnesses
WO2002021326A3 (fr) * 2000-09-05 2003-10-02 Algoplus Consulting Ltd Systeme de renseignements et procede utilisant des analyses fondees sur des donnees longitudinales orientees objet
US6820235B1 (en) 1998-06-05 2004-11-16 Phase Forward Inc. Clinical trial data management system and method
US7103603B2 (en) 2003-03-28 2006-09-05 International Business Machines Corporation Method, apparatus, and system for improved duplicate record processing in a sort utility
US7206789B2 (en) 2003-11-13 2007-04-17 St. Jude Children's Research Hospital, Inc. System and method for defining and collecting data in an information management system having a shared database

Citations (5)

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US5345544A (en) * 1990-04-28 1994-09-06 Sharp Kabushiki Kaisha Data base system
US5461708A (en) * 1993-08-06 1995-10-24 Borland International, Inc. Systems and methods for automated graphing of spreadsheet information
US5515488A (en) * 1994-08-30 1996-05-07 Xerox Corporation Method and apparatus for concurrent graphical visualization of a database search and its search history
US5550964A (en) * 1992-12-18 1996-08-27 Borland International, Inc. System and methods for intelligent analytical graphing
US5611035A (en) * 1992-10-16 1997-03-11 International Business Machines Corporation Relational data base system for conveniently constructing graphical images

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5345544A (en) * 1990-04-28 1994-09-06 Sharp Kabushiki Kaisha Data base system
US5611035A (en) * 1992-10-16 1997-03-11 International Business Machines Corporation Relational data base system for conveniently constructing graphical images
US5550964A (en) * 1992-12-18 1996-08-27 Borland International, Inc. System and methods for intelligent analytical graphing
US5461708A (en) * 1993-08-06 1995-10-24 Borland International, Inc. Systems and methods for automated graphing of spreadsheet information
US5515488A (en) * 1994-08-30 1996-05-07 Xerox Corporation Method and apparatus for concurrent graphical visualization of a database search and its search history

Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6579888B2 (en) 1994-10-31 2003-06-17 Opt-E-Scrip, Inc. Method and kit for treating illnesses
US6820235B1 (en) 1998-06-05 2004-11-16 Phase Forward Inc. Clinical trial data management system and method
WO2002006826A1 (fr) * 2000-07-17 2002-01-24 Opt-E-Scrip, Inc. Essais de medicaments sur patient unique associes a une base de donnees cumulees
WO2002021326A3 (fr) * 2000-09-05 2003-10-02 Algoplus Consulting Ltd Systeme de renseignements et procede utilisant des analyses fondees sur des donnees longitudinales orientees objet
US6631384B1 (en) 2000-09-05 2003-10-07 Algoplus Consulting Limited Information system and method using analysis based on object-centric longitudinal data
US7103603B2 (en) 2003-03-28 2006-09-05 International Business Machines Corporation Method, apparatus, and system for improved duplicate record processing in a sort utility
US7206789B2 (en) 2003-11-13 2007-04-17 St. Jude Children's Research Hospital, Inc. System and method for defining and collecting data in an information management system having a shared database

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