This report screens all adverse events by performing a
Cochran-Mantel-Haenszel exact test (CMH exact test) on all 2 x 2 tables constructed from event resolution and treatment
arm. Resolution is computed directly from the end time of an adverse event and the end time of the trial, or from a resolution time that you specify.
Refer to the AE Incidence Screen report description, keeping in mind the following important report differences in contrast with the example:
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Dot Plot: Click to create a dot plot for selected terms or for all terms that fall under selected groups, with rates of adverse events by treatment, the relative risk, the risk difference, and the odds ratio presented.
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Relative Risk Plot: Click to create a relative risk plot and table for selected terms or for all terms that fall under selected groups, with rates of adverse events by treatment, the log 2(relative risk) and unadjusted 95% confidence intervals ( Multiple Testing Method is not applied) presented.
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Odds Ratio Plot: Click to create a plot that shows the ratio of the odds for exhibiting a selected event/intervention to the odds for those who do not exhibit the event/intervention and it can be used to estimate the relative risk when the probability of positive response is small.
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Contingency Analysis: Click to create the typical treatment by event contingency table for selected terms or for all terms that fall under selected groups.
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Venn Diagram: Click to create a Venn diagram for up to five selected terms or for terms that fall under selected groups, to show the co-occurrence of adverse events within study subject.
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Tabulate: Click to create a table for selected terms or for all terms that fall under selected groups, showing the co-occurrence of adverse events within study subject. You can further modify the tables to show additional summary statistics.
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Click the Options arrow to reopen the completed report dialog used to generate this output.
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Note: For information about how treatment emergent adverse events (TEAEs) are defined in JMP Clinical, please refer to
How does JMP Clinical determine whether an Event Is a Treatment Emergent Adverse Event?.
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.
Analysis can consider all events or only those that emerge at specific times before, during, or after the trial period. For example, selecting On treatment events as the
Event Type includes only those events that occur on or after the first dose of study drug and at or before the last dose of drug (+ the offset for end of dosing).
If you choose to Ignore available treatment emergent flags, the analysis includes all adverse events that occur on or after day 1 of the study.
By default, post-treatment monitoring begins after the patient receives the last treatment. However, you might want to specify an Offset for End of Dosing, increasing the time between the end of dosing and post-treatment monitoring for treatments having an extended half-life.
Check the Treatment end date is equivalent to the start date if the treatment end date (
EXTENDTC) is missing from the data. In this case, it is assumed that all treatments were given on the same day and that the treatment start date can be used instead.
You must specify how to determine whether an adverse event is resolved or not resolved using the Determine Resolved / Not Resolved Status using: option. You can specify either an outcome (resolved or not) or a time. A
Reference Value or Day must be specified if you select one of the available time options, which include either duration of the event, or the date on which it ended.
If there is a supplemental domain (SUPPAE) 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,
Additional Filter to include Adverse Events, and
Additional Filter to Include Subjects for more information.
The Treatment Control Level is specified as either
“Placebo” or
“Pbo”, depending on the value found in your data, by default. However, if your control is defined differently you can use the text box to specify the control level is identified in your study.
You can opt to assess interventions across the entire study (specified by default). Alternatively, you can use the Time Windows for Start of AE option to limit it to selected time points or intervals. By default, time is measured in days. However, you can change the
Time Scale to measure time in weeks. This option is useful for assessing report graphics for exceptionally long studies.
Stratification Variables segment the data into meaningful clusters and statistical tests such as the CMH exact test account for them. Such stratification is usually recommended when strata exist in your study, for example, by site.
You can opt to Perform Double FDR Adjustment on your data. By default, this adjustment is not performed. The Double False Discovery Rate method
2 is used here to compare the incidence of interventions among treatments, leveraging the grouping of related events (typically defined by the MedDRA system organ class). The method considers whether related terms within a group show differences between the treatments and upweights or downweights the significance of an individual term within the group accordingly.
The False Discovery Rate test is selected by default. You can use the Multiple Testing Method option to select alternative test protocols.
The Alpha option is used to specify the significance level by which to judge the validity of the summary statistics generated by this report. The meaning of
alpha depends on the adjustment method that you select.
Alpha can be set to any number between 0 and 1, but is most typically set at 0.001, 0.01, 0.05, or 0.10. The higher the
alpha, the higher the error rate but also higher the power for detecting significant differences. You will need to decide on the best trade-off for your experiment.
Note that instead of performing multiple testing adjustments of the p-values, you can opt to simply specify a cutoff value for
-log10(
p-values) in order to select significant hypothesis tests. Using unadjusted
p-values with a cutoff has the benefit of more expansive volcano plots, whereas adjusted
p-values tend to squish points along the
y-axis.Refer to
-log10(p-Value) Cutoff for more information.
Note: This option is available only when no multiple testing method is specified.
Use the X-Axis for Volcano Plot option to specify the parameter to be plotted on the x-axis of your volcano plots. The
Color Theme option enables you to specify the color scheme of the report graphics.