Available Reports

Reports are grouped into functional categories, as listed below:

Subject Level

Reports using data from across multiple domains are described in the table below:.

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Study Flow Diagram Generates a flow diagram to summarize the overall clinical trial data flow.
Patient Profiles Profiling subjects is a powerful way to view all of the data for one or more subjects, enabling you to view their entire history and determine potential causes for unexpected events or findings.

Demographics Distribution

Compares distributions of demographic variables across treatment arms via a one-way ANOVA or contingency analysis.

Study Visits

Generating a graphical display and tabulation of study visit attendance.

Create Cross Domain Data

Adding data for various domains to the ADSL table corresponding to incidence of variables in the AE, CM, LB, and MH domains and a summary statistic for LB, EG, and VS domain values

Adverse Events

Reports examining patient study events are described in the table below:

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Adverse Events Distribution

Comparing Distributions of adverse events and demographic variables across treatment arms for single occurrences of the events.

Adverse Events Multiple Occurrences Distribution

Comparing Distributions of adverse events and demographic variables across treatment armsfor multiple occurrences of the events.

Adverse Events Incidence Rates Tabulating the number of occurrences of each event and calculating their incidence rates.

Adverse Events Narrative

Generating adverse event narratives for clinical study reports

Adverse Events Time to Event Screens all adverse eventsby performing log-rank and Wilcoxon tests between treatment groups. The time to first occurrence of the adverse event is used as the response.

Adverse Events Risk Report

Screening all adverse eventsand calculates and generates forest plots of risk differences, relative risks or odds ratios

Medical Query Risk Report Screens medical query terms by performing Cochran-Mantel-Haenszel (CMH) tests on all 2 x 2 tables constructed from event incidence and treatment arm. Output is a two-sided plot with a dot plot showing percent occurrence and forest plot showing risk measurement.
Algorithmic FDA Medical Query Risk Report This process uses FMQs with associated algorithms together with data from DMSEX to query AE, LB, and CM for subjects meeting the specified qualifications and the performs Cochran-Mantel-Haenszel (CMH) tests on all 2 x 2 tables constructed from event incidence and treatment arm. Output is a two-sided plot with a dot plot showing percent occurrence and forest plot showing risk measurement along with a table listing number (and percentage) of subjects exhibiting each FMQ by specific qualification.
Custom Medical Query Risk Report Calculates risk measurements for custom medical queries defined in the adverse events dataset.

Treatment Emergent Adverse Events Summary

Creating a tabular and graphical overview of treatment emergent adverse events for the safety population by actual treatment arm

Other Events

Reports examining patient study events are described in the table below:

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Clinical Events Distribution Capturing clinical events specially tracked as being of interest to the particular study and reported in the CE domain.

Events Distribution

Comparing Distributions of events from a domain and demographic variables across treatment arms for single occurrences of the events.

Note: This report should be considered as two: DS Distribution and MH Distribution, depending on which domain is specified in the dialog.

Events Multiple Occurrences Distribution

Comparing Distributions of events from a domain and demographic variables across treatment arms for multiple occurrences of the events.

Note: This report should be considered as two: DS Distribution and MH Distribution, depending on which domain is specified in the dialog.

Events Risk Report

Screening all events from the specified domain and calculates and generates forest plots of risk differences, relative risks or odds ratios

Note: This report should be considered as two: DS Risk Report and MH Risk Report, depending on which domain is specified in the dialog.

Mortality Time to Event

Grouping clinical mortality results by treatment arm and generating Kaplan-MeierSurvival Curves with associated statistics

Discontinuation Time to Event

Creating Kaplan-MeierSurvival Curves for time to study discontinuation and associated statistics, grouped by treatment arm

Interventions

Reports describing interventions are described in the table below:

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Exposure Summary

Generating an exposure summary and plot for all subjects in a study of an investigational product, by dose and exposure time for the safety population, by treatment

Interventions Distribution

Comparing Distributions of interventions and demographic variables across treatment arms for single occurrences.

Interventions Multiple Occurrences Distribution

Comparing Distributions of interventions and demographic variables across treatment arms for multiple occurrences.

Interventions Risk Report

Screening all interventions and calculates and generates forest plots of risk differences, relative risks or odds ratios

Findings

Reports examining patient findings are described in the table below:.

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Drug-induced Liver Injury

This report assesses the results of multiple lab tests enabling you to determine whether trial subjects have sustained drug-induced liver damage. Analysis results are presented and summarized in multiple graphs and tables.

Findings Box Plots

Displaying Box Plots by treatment group representing the change from baseline in measurements for each test for a specified findings domain across various time windows or points in a study

Findings Distribution

Comparing Distributions of findings and demographic variables across treatment arms

Findings Mean Change from Baseline Tables Listing the number (and percentage) of patients in each treatment arm at each visit for each specified test and then calculating the mean change from baseline for all patients in each group.

Findings Shift Plots

Displaying Shift Plots to compare test measurements for a specified findings domain at baseline versus on-therapy values, and performing a matched pairs analysis on average score during baseline and a summary score during the trial

Findings Shift Tables Collecting all of the specified findings test results and constructing a table listing the number (and percentage) of subjects in each treatment arm that are considered high, normal, or low for each test, grouped by visit.
Findings Time Trends Enables you to visualize findings measurements across the time line of the study.

Findings Waterfall Plots

Creating waterfall plots to show the distribution of changes in test measurements for a given Findings domain across subjects

Hy’s Law Screening

Visualizing peak values for lab measurements pertaining to Hy’s Law for detecting potential liver toxicity for all subjects across treatment arms

Oncology1

Reports are described in the table below:

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Disease Response Swimmer Plot

This process creates a disease response swimmer plot and tables around either the best or last recorded response rates and calculated objective response rate for solid tumor oncology clinical trials. The results of these assessments are summarized based on selecting either the Best response per subject, based on preferred order: CR, PR, SD, PD for controlled terms, respectively, or Last recorded response. The objective response rate (the sum and percentage of subjects who had CR + PR assessment result) is also calculated and listed in the summary table.

Progression Free Survival

Progression free survival is used to describe how long patients can go without the disease without getting worse. This process uses a modified survival plot and hazard ratio plot to compare the number and percentage of patients who have tumor progression or death, with patients who show no tumor progression or death at the cut-off date.

Tumor Response This process uses the TR, TU (optional), and RS (optional) oncology domains to create spider plots showing tumor results and waterfall plots showing Best or Last recorded responses.

Reports

Reports are described in the table below:

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DSUR/PSUR Report Generating a report for updating regulatory agencies regarding the safety of a clinical trial design and execution for the purpose of securing permission for the continuance of the trial.

Comment Report

Generating a document of study comments obtained from source data pertaining to each subject.

Data Quality

Reports examining patient findings are described in the table below:.

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Birthdays and Initials Attempts to identify subjects, by their birthdays or initials, who register at multiple study sites.
Cluster Subjects Across Study Sites This report is used to identify similar subjects within a demographic subgroup, such as Sex = F and Race = Asian. It does so by constructing a cross domain dataset using as much baseline data as possible (subject to user options). The goal of this exercise is to identify pairs of subjects with a very small distance. This could be an indication that these subjects are in fact the same individual who has enrolled at multiple sites.
Cluster Subjects Within Study Sites This report clusters subjects within study site for the purpose of identifying similar subjects. It constructs a cross domain data set using as much baseline data as possible (subject to user options). The goal of this exercise is to identify pairs of subjects with a very small distance. This could be an indication that these subject are slightly modified copies of one another.

Constant Findings

Identifying tests from findings domains that have the same result for the entire study

Digit Preference

Assesses the use of terminal digits by study sites when reporting their clinical findings to identify those sites that might exhibit biases in rounding issues or other problems with how they report data.

Duplicate Records

Identifying sets of records that have identical values on more than one occasion within a subject or between subjects within a study site

Missing Findings

Determines whether individuals are missing data for all test codes across all Findings domains, based on data available at each visit number and time point number.

Multivariate Outliers

Calculating Mahalanobis distance based on available data to detect subject inliers and outliers in multivariate space, and generating results by site to see which sites are extreme.

Outliers

Identifies outliers and identifies sites with excessive outliers.

 

Patient Recruitment This report estimates the likelihood that recruitment goals are met using enrollment data collected so far. The estimated parameters are then used to predict future enrollment patterns given the existing number of study centers and the number of new centers necessary for the target enrollment to be reached by the deadline.
Perfect Scheduled Attendance This report compares the distribution of study visit days for each center compared to all other centers combined, and identifies unusual differences. For example, a site where all visits occur on the same study day can be flagged for further investigation.
Risk Based Monitoring Risk-based monitoring is a proactive method of clinical trial monitoring to detect patient safety risks and data quality issues at an early stage of a trial.
Visit Order

This report determines whether visit dates are unusual for subjects when ordering dates according to visit number.