subpat - Time-to-event on subpopulations and subgroups
Authors: Stefan Eng, Mustapha Larbaoui
Working with Shiny < 1 year
Abstract: Exploratory time-to-event analysis with subgroups and subpopulations via easy to use graphical interface. Supports Kaplan-Meier plots and Cox Ph models.
Full Description: subpat is a collection of package to help with common tasks for people in pharma doing exploratory data analysis using ADaM datasets. The main features include
- Creating and editing subpopulations
- Creating subgroups
- Basic time-to-event analysis with flexible variable mapping
- Includes Kaplan-Meier plots and Cox Ph models
Users such as medical writers can use the subpopulation features (via the PLG app in subpat) to create ad-hoc reports. Developers can easily plug-and-play the modules into their own applications.
One of the novel features of subpat is the use of tidymodules to manage complex nested modules in shiny. Tidymodules provides a new object-oriented programming (OOP) approach for module development, new module interface using input/output ports and a set of tidy operators for handling cross-module communication.
The bulk of this work was developed over the summer during my internship at Novartis in the SCC (Scientific computing and consulting) group.
Category: Healthcare
Keywords: pharma, bs4Dash, tidymodules
Shiny app: https://stefaneng.shinyapps.io/subpat-TTE
Repo: GitHub - Novartis/subpat: {subpat} is a collection of modules to create subpopulations and subgroups from clinical trial data
RStudio Cloud: Posit Cloud
Thumbnail:
Full image:
Subpopulations editing:
Subgroup creation:
KM Plot:
Cox PH:
tidymodule module visualization:
