Summary:
This Shiny app is designed for dynamic visualization of adverse event (AE) data in clinical trials for two groups comparison. We provide a variety of tools for visualizing the AE data based on maximal grade of AEs by toxicity type or toxicity category/system organ classes (SOCs).
Details and Uses:
In the Data Description tab, we provide sample datasets. The user will need to format their dataset accordingly to include the necessary variables in each dataset.
In the Data Upload tab, the user will upload the datasets and specify variable names for each necessary variable.
In the Crosstabs tab, we provide AE table summarized by either maximum toxcitiy type or maximum toxicity category. User can stratify the table by different patient level characteristics.
In the AE Tables tab, we provide AE table that is commonly reported in publications/practices summarized by either maximum toxicity type or maximum toxcitiy category. Different options for sorting, decimal places, minimum percentages of AE to include, whether to combine toxcity degree or not are provided.
In the Toxicity Type Plot tab, we provide different visualization tools for AEs summarized by maximum toxicity type or maximum toxicity category. User can choose toxicity categories to exclude and whether to visualize the counts of AEs or percent of patients with AEs. Different plot options are available when AEs are summarized differently. Different color schemes are also provided.
In the Plot with Tables tab, user can take a closer look at each AE category by having bar plot and AE table side-by-side.
Funding Source:
The development of this project is funded by the Impact Award from the Hope Foundation.
DISCLAIMER:
Users are solely responsible and liable for use of content through the app.
BugReports: wf2213@cumc.columbia.edu
Developed by
Weijia Fan
Please upload two datasets in csv format with the necessary variables shown below. You will need to specify the variables to use in your dataset after uploading them in the Data Upload tab.
ID dataset
This dataset must contain the follwoing two variables:
Patient ID: e.g., PATNO , a distinct number or character for each patient. The number of subjects obtained from here is used as the default when calculating percentages in the tables and graphs.
Treatment assignment: e.g., TRNO , a numeric or character binary variable indicating the treatment assignment for each individual.
The number of patients in this file is assumed to be the total number of patients, which is used as the denominator when calculating percentages.You may also included other patient level variables of interest in the ID dataset.
AE dataset
This dataset must contain the following five variables:
Patient ID: , the variable with the same variable name and matching patient ID as in the ID dataset.
Toxicity category: e.g., CTC_CAT , a character variable indicating category of the adverse event.
Toxicity type: e.g., TOXLABEL , a character variable indicating the type of the adverse event. One toxicity type can only belong to one toxicity category.
Toxicity grade: e.g., TOXDEG , a numeric variable with up to 5 toxicity grades.
Attribution level: e.g., TXATT , a numeric or character variable indicating the attribution of the adverse event.
Template datasets shown on the right can be downloaded.
Loading...
Loading...