Reports | Findings Waterfall Plots

Findings Waterfall Plots
This report creates waterfall plots to show the distribution of changes in test measurements for a given Findings domain across subjects (ordered by their magnitude of change). The Findings measurements are summarized based on a specified summary statistic and a waterfall plot is created for each Findings test.
Note: JMP Clinical uses a special protocol for data including non-unique Findings test names. Refer to How does JMP Clinical handle non-unique Findings test names? for more information.
Report Results Description
Running Findings Waterfall Plots with the Nicardipine sample setting and LB findings domain generates the report shown below.
Waterfall Plots
There is one Waterfall Plot for each quantitative findings test (for example, laboratory tests) in the Findings data set that was analyzed. Output data set is a stacked data set of findings measurements at subject level; subject level drill downs available.
There are a series of plots. Each plot shows a summary of the findings test measurements on the Y axis for each subject (on X axis) ordered by that measurement. Caption boxes in the upper right corner of each graph (optional) display a summary statistic across all subjects (in a treatment or BY variable group) to aid in understanding the differences in the center/spread of the group distributions.
Data Filter
This enables you to subset subjects based on demographic characteristics and other factors. Refer to Data Filter for more information.
Action Buttons
Action buttons, provide you with an easy way to drill down into your data. The following action buttons are generated by this report:
Profile Subjects: Select subjects and click to generate the patient profiles. See Profile Subjects for additional information.
Show Subjects: Select subjects and click to open the ADSL (or DM if ADSL is unavailable) of selected subjects.
Cluster Subjects: Select subjects and click to cluster them using data from available covariates. See Cluster Subjects for additional information.
Demographic Counts: Select subjects and click to create a data set of USUBJIDs, which subsets all subsequently run reports to those selected subjects. The currently available filter data set can be applied by selecting Demographic Counts in any report dialog.
Click to generate a standardized pdf- or rtf-formatted report containing the plots and charts of selected sections.
Click to read user-generated notes. Refer to View Notes for more information.
Click the Options arrow to reopen the completed report dialog used to generate this output.
Click the gray border to the left of the Options tab to open a dynamic report navigator that lists all of the reports in the review. Refer to Report Navigator for more information.
Report Options
Findings Domain Tests
Use the Findings Domain to Analyze option to specify whether to plot the distribution of measurements from either the Electrocardiogram (EG), Laboratory (LB), or Vital Signs (VS) findings domains. LB is selected by default.
You can use the Findings Domain Tests for Analysis option to plot the distributions of one or more selected findings tests. Leaving the field blank (the default selection) plots the distributions for all available findings tests.
Treatment or Comparison Variable:
The primary goal of clinical trials is to distinguish treatment effects when reporting and analyzing trial results. Treatments are defined by specific values in the treatment or comparison variables of the CDISC models. These variables are specified in this report using the Treatment or Comparison Variable to Use andTreatment or Comparison Variable options.
Distributions of the specified treatment or comparison variables are shown in the output.
Available variables include Planned, which is selected when the treatments patients received exactly match what was planned and Actual, which is selected when treatment deviates from what was planned.
You can also specify a variable other than the ARM or TRTxxP (planned treatment) or ACTARM or TRTxxA (actual treatment) from the CDISC models as a surrogate variable to serve as a comparator. Finally, you can select None to plot the data without segregating it by a treatment variable.
See Treatment or Comparison Variable to Use, Treatment or Comparison Variable for more information.
Lab Measurements
Use the Plot findings measurements as: option to specify how you want to display the findings results in the plots.
Use the Summary Statistic for Trial Data option to specify whether to display the mean, median, maximum, minimum, or last values to summarize the results of the trial period.
By default, JMP Clinical reports unaltered laboratory measurement values. In any cases, simply examining the raw numbers can make interpretation somewhat confusing. Normalization of Lab Measurements to accepted values can often ease these difficulties. JMP Clinical offers three options for normalizing your data.
Selecting LLN normalizes the data to the lower limit of the expected normal range and is best used when you expect the values to fall below the normal. Normalized values less than one are considered to be lower than normal.
Selecting ULN normalizes the data to the upper limit of the expected normal range and is best used when you expect the values to exceed the normal range. Normalized values greater than one are considered to be higher than normal.
Selecting Geometric normalizes the data such that the lower limit of the expected normal range is set to -1 and the upper limit of the expected normal range is set to +1. This method is best used when there is no expectations of where the values might fall. Normalized values less than -1 are considered to be lower than normal while values greater that +1 are higher than normal.
Note: These options are available only when LB is the specified domain.
Unscheduled Visits
You might or might not want to include unscheduled visits when you are analyzing findings by visit. Check the Remove unscheduled visits to exclude unscheduled visits.
Filtering the Data:
Filters enable you to restrict the analysis to a specific subset of subjects and/or findings records, based on values within variables. You can also filter based on population flags (Safety is selected by default) within the study data.
If there is a supplemental domain (SUPPXX) associated with your study, you can opt to merge the non-standard data contained therein into your data.
See Select the analysis population, Select saved subject Filter1, Merge supplemental domain, Include the following findings records:, Additional Filter to Include Findings Records, and Additional Filter to Include Subjects2 or more information.
By default, time is measured by visits. However, you can change the Time Scale to measure time in either weeks or days. This option is useful for assessing report graphics for exceptionally long studies.
To establish a baseline measurement for each finding, you must specify the time period (usually prior to day one of the study) and whether to use on or more than one measurement. Use the Baseline Time Window option to specify the time period during which baseline measurements are taken and the Calculate baseline as: option to use the last pre-dose measurement or the mean of all the measurements taken during the baseline time window as the baseline measurement.
Use these options to specify how you want the plots to appear.
By default, subject identifiers are not included on the waterfall plots. Click the Display Subject Identifiers on Waterfall Plot x-Axis box to display the subject identifiers on the x-axes of the plots.
The results for the treatment and control arms for each test are overlaid on the waterfall plots by default (top plot, shown below). Results for each arm are shown in different colors.
For times when you want to view treatment and control arms separately (bottom plots, shown above), deselect the Overlay treatment groups in plots
Use the Overall Summary Statistic to Display in Plots option to select the summary statistic to display in the waterfall plots. Median is selected by default.
You can also subdivide the subjects and run analyses for distinct groups by specifying one or more By Variables.

Subject-specific filters must be created using the Create Subject Filter report prior to your analysis.

For more information about how to specify a filter using this option, see The SAS WHERE Expression.