CASAS

CASAS performs survival analysis and visualization of time-to-event data, supporting quantile survival analysis, landmark analysis, competing risks analysis, and standard survival analysis for biomedical research.

Key Features:

• Visualization Capabilities: Generates Kaplan-Meier plots and cumulative incidence plots for time-to-event data.
• Quantile Survival Analysis: Analyzes specific quantiles of survival times across datasets.
• Landmark Analysis: Performs analyses at predetermined time points.
• Competing Risks Analysis: Supports analysis of competing risks scenarios where multiple event types can preclude the event of interest.
• Standard Survival Analysis: Implements standard survival analysis methods for time-to-event investigation.
• Univariate and Multivariate Analysis: Enables univariate analysis on one or several user-specified variables with results presented as consolidated tables including log rank p-values and hazard ratios.
• Summary Grids for Multiple Analyses: Constructs single summary grids to compare results across multiple cancer types or datasets.
• Implementation: Implemented in R and integrated with Shiny for analysis and visualization workflows.

Scientific Applications:

• Oncology research: Supports survival studies across various cancer types to investigate patient outcomes.
• Prognostic factor identification: Facilitates identification of variables associated with differences in survival times.
• Treatment efficacy evaluation: Enables assessment of treatment effects on time-to-event outcomes.

Methodology:

Implemented in R and integrated with Shiny; performs quantile survival analysis, landmark analysis, competing risks analysis, and standard survival analyses, generates Kaplan-Meier and cumulative incidence plots, and computes log rank p-values and hazard ratios.