# Available Reports

Reports are grouped into functional categories, as listed below:

### Demographics and Visits

Reports examining patient demographics and study visit attendance are described in the table below:.

Report | Choose this report for...
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.
Visit Order | Determines whether visit dates are unusual for subjects when ordering dates according to visit number.
Weekdays and Holidays | Identifying the weekday of study dates and determining whether these dates fall on major holidays.
Perfect Scheduled Attendance | Compares the distributions of study visit days for each center compared to all other centers combined, and identifies unusual differences.
Birthdays and Initials | Identifying subjects that might be identical based on birthdays or initials.
Enrollment Patterns | Generates uniformly weighted moving average plots to determine whether enrollment patterns within each site appear unusual.
Patient Recruitment | Estimates patient recruitment parameters and uses these estimates to predicts future enrollment pattern. If the target time will be missed by a user-defined probability, adaptive adjustment launched by predicting the number of new centers necessary for the target enrollment to be reached by the deadline.

### Interventions

Reports describing interventions are described in the table below:

Report | Choose this report for...
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
Interventions Incidence Screen | Screening interventions by performing a Cochran-Mantel-Haenszel exact test on all 2x2 tables constructed from event incidence and treatment arm

### Events

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

Report | Choose this report for...
Adverse Events Distribution | Comparing Distribution s of adverse events and demographic variables across treatment arms
Adverse Events Narrative | Generating adverse event narratives for clinical study reports
Treatment Emergent Adverse Events Summary | Creating a tabular and graphical overview of treatment emergent adverse events for the safety population by actual treatment arm
Adverse Events Incidence Screen | Screening adverse events by performing a Cochran-Mantel-Haenszel exact test on all 2x2 tables constructed from incidence and treatment arm
Adverse Events Resolution Screen | Screening adverse events by performing a Cochran-Mantel-Haenszel test on all 2x2 tables constructed from event resolution and treatment arm
Adverse Events Severity ANOVA | Screening adverse events by performing a mixed-model analysis of variance, with average ranked severity score as the dependent variable and customizable fixed and random effects
Adverse Events Time to Event | Screening adverse events by performing log-rank and Wilcoxon tests between treatment groups
Mortality Time to Event | Grouping clinical mortality results by treatment arm and generating Kaplan-Meier Survival Curves with associated statistics
Discontinuation Time to Event | Creating Kaplan-Meier Survival Curves for time to study discontinuation and associated statistics, grouped by treatment arm
Events Distribution | Comparing Distribution s of events from a domain and demographic variables across treatment arms Note: This report should be considered as two: DS Distribution and MH Distribution, depending on which domain is specified in the dialog.
Events Incidence Screen | Screening events from a domain by performing a Cochran-Mantel-Haenszel test on all 2x2 tables constructed from event incidence and treatment arm Note: This report should be considered as two: DS Incidence Screen and MH Incidence Screen, depending on which domain is specified in the dialog.
Standardized MedDRA Queries Distribution | Compares distributions of SMQs across treatment arms.
Standardized MedDRA Queries Incidence Screen | Screens SMQ terms by performing a Cochran-Mantel-Haenszel test on all 2 x 2 tables constructed from event incidence and treatment arm.
Adverse Events Bayesian Hierarchical Model | Fitting Bayesian hierarchical models for adverse events, while taking into account a grouping variable

### Findings

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

Report | Choose this report for...
Findings Distribution | Comparing Distribution s of findings and demographic variables across treatment arms
Findings Time Trends | Visualizing findings measurements across the timeline of a study
Findings Box Plots | Displaying Box Plot s 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 Shift Plots | Displaying Shift Plot s 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 Waterfall Plots | Creating waterfall plots to show the distribution of changes in test measurements for a given Findings domain across subjects
Findings Bubble Plot | Tracking a pair of findings measurements over time with an animated Bubble Plot
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
Findings ANOVA | Screening findings measurements for a specified domain one at a time by performing a repeated-measures analysis of variance
Findings Time to Event | Defining events using one or more findings tests to be analyzed in a time-to-event analysis
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
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.
Outliers | Identifies outliers and identifies sites with excessive outliers.
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.
Frequencies | Identifies unusual frequencies by study visit.
Correlated Findings | Calculates pairwise correlations between tests within each findings domain and identifies unusual results at specific study sites.
Summary Statistics | Identifies unusual summary statistics by study visit.
Screening Bias | Identifies within-site mean differences between two selected visits for continuous endpoints to identify regression to the mean in assessing study entry criteria.

### Oncology1 Oncology reports are surfaced only when the current study contains oncology data sets.

Reports are described in the table below:

Report | Choose this report for...
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. Measurements plotted on the spider plot and summarized in the waterfall plot represent change or percent change of tumor burden from baseline in measurable/target lesions.
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.

### SEND2 SEND reports are surfaced only when the current study contains SEND data.

Reports are described in the table below:

Report | Choose this report for...
Animal Profile | This process compares generates a static report (PDF or RTF) summarizing the general information and pathological observations for each animal in the study.
Findings Incidence Report | This process compares distributions of demographic variables across treatment arms via a one-way ANOVA or contingency analysis.
Trial Design | This process visualizes findings measurements for each subject across the time-line of the study.

### Reports

Reports are described in the table below:

Report | Choose this report for...
Study Visit Report | Generating a report of total subject clinic attendance over the course of a study
Standard Safety Reports | Generating standard safety tabular reports
Adverse Events Report | Generating reports of adverse event counts and percentages by treatment arms, sex, and race
Comment Report | Generating a document of study comments obtained from source data pertaining to each subject.

### Cross Domain

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

Report | Choose this report for...
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
Multivariate Inliers and 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.
Cluster Subjects across Study Sites | Constructs a cross domain data set and computes a distance matrix and performs hierarchical clustering of subjects across all of the study centers 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 | Constructs a cross domain data set and computes a distance matrix and performs hierarchical clustering of subjects within each study center 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.
Risk Based Monitoring | Generates a dashboard for risk-based monitoring of clinical trials

### Data Management

Click on a button corresponding to a subject utility. Refer to the table below for guidance..

Report | Choose this report for...
Domain Viewer | Aids in the review of study domains.
Notes Distribution | Enables you to review notes for a selected study.
Required Domain Report | Checks SAS data sets in the SDTM and ADaM folders that have been specified for the selected study, for all variables required for various JMP Clinical reports.
Review Status Distribution | Displaying the distribution of the review status of subjects in a study
Variable Report | Launches the JMP Clinical Study Variable Report.

### Miscellaneous

Reports are described in the table below:.

Report | Choose this report for...
Update Study Risk Data Set | Manually enter site-specific descriptive information as well as risk indicator information
Manage Risk Threshold Data Sets... | Enables you to modify or delete risk threshold data sets.