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PERSUADE

ParamEtRic SUrvivAl moDel sElection

A standardized R tool to support the selection, comparison, andcommunication of parametric survival models, and their implementation indecision-analytic models.

Overview

PERSUADE guides analysts through a reproducible workflow for survivalanalysis and model selection. It provides:

• Kaplan-Meier visualizations and diagnostics
• Assessment of proportional hazards (PH) assumption
• Observed and predicted hazard function plots
• Fit comparisons of standard, spline-based, and cure models
• Goodness-of-fit statistics (AIC/BIC)
• Explore model extrapolation beyond observed data
• Automated PDF reports for communication
• Export the parametric survival model parameters for use indecision-analytic models

The framework is designed for transparency and consistency whensurvival analysis feeds into decision-analytic models.

Prerequisites

• R (version compatible with survival and other dependencies)
• Recommended: RStudio for better environment handling
• Install PERSUADE package usinginstall.packages("PERSUADE")
• Alternatively: to install the development version of PERSUADE:devtools::install_github("Bram-R/PERSUADE", quiet = TRUE, upgrade = "never")
• Load PERSUADE package:library(PERSUADE)

Quick start

The easiest way to get started is by running the example workflowscript:PERSUADE_example_workflow.R using:file.edit(system.file("example_workflow", "PERSUADE_example_workflow.R", package = "PERSUADE"))

This script:

• Loads example survival data.
• Runs the main PERSUADE analysis (f_PERSUADE()).
• Summarizes results withprint(),summary(), andplot().
• Generates a ready-to-share PDF report viaf_generate_report().
• Exports fitted model parameters to .csv.

Step-by-step workflow

1. Load PERSUADE package

library(PERSUADE)

2. Run example analysis

PERSUADE<-f_PERSUADE(name ="BC_OS",years = flexsurv::bc$recyrs,# time-to-eventstatus = flexsurv::bc$censrec,# event indicatorgroup = flexsurv::bc$group,# grouping variablestrata =TRUE,spline_mod =TRUE,cure_mod =TRUE,time_unit =1/12,# months in yearstime_horizon =40,time_pred_surv_table =c(0,1,2,5,10,20,30,40))

3. Inspect the object

print(PERSUADE)

4. Summarize results

# Kaplan-Meier estimatessummary(PERSUADE,type ="km")# Survival probabilities at time pointssummary(PERSUADE,type ="surv_probs")# Goodness-of-fit for standard parametric modelssummary(PERSUADE,type ="gof")# Goodness-of-fit for spline-based modelssummary(PERSUADE,type ="gof_spline")# Goodness-of-fit for cure modelssummary(PERSUADE,type ="gof_cure")

5. Visualize results

# Set colour palette for Figurespalette(rainbow(n =9,s =1,v =1,start =0,end =max(1,9-1)/9,alpha =1))# Kaplan-Meier curvesplot(PERSUADE,type ="km")# Proportional hazards diagnosticsplot(PERSUADE,type ="ph")# Observed smoothed hazardplot(PERSUADE,type ="hr")# Standard parametric modelsplot(PERSUADE,type ="param_models")# Spline-based modelsplot(PERSUADE,type ="spline_models")# Cure modelsplot(PERSUADE,type ="cure_models")# Set colour palette to defaultpalette("default")

6. Generate the report

f_generate_report(PERSUADE)

7. Export model parameters

# Copy to clipboard (for copying in PERSUADE Excel template.xltx)write.table(PERSUADE$surv_model_excel,"clipboard-128",sep ="\t",col.names =FALSE)# Export to CSV (change `tempdir()` into `getwd()` for copying to working directory)write.csv(PERSUADE$surv_model_excel,file.path(tempdir(),paste0(name,"_output"),"PERSUADE_Time-to-event_models_parameters_comma.csv"))write.csv2(PERSUADE$surv_model_excel,file.path(tempdir(),paste0(name,"_output"),"PERSUADE_Time-to-event_models_parameters_semicolon.csv"))

f_get_excel_template()