When should I use RMST instead of a standard logrank test?

Restricted Mean Survival Time (RMST) is ideal when the proportional hazards assumption is violated or when a more clinically interpretable measure (average survival time up to a specific point) is required.

What is the MaxCombo test used for in clinical trials?

The MaxCombo test combines multiple weighted logrank tests and takes the maximum Z-score. It is used to maintain statistical power when the specific pattern of non-proportional hazards (like delayed effect or crossing hazards) is unknown before the study.

Does this skill support the simtrial R package?

Yes, this skill provides specific implementation patterns for the simtrial R package, including code for Fleming-Harrington weights, Magirr-Burman weights, and milestone analysis.

How do Fleming-Harrington parameters (rho and gamma) affect analysis?

The rho (ρ) and gamma (γ) parameters control which part of the survival curve is emphasized. High rho emphasizes early events, while high gamma emphasizes late events, helping to target specific treatment effect patterns.

Clinical Trial Time-to-Event Analysis

Name: Clinical Trial Time-to-Event Analysis
Author: choxos

bychoxos

0•

Data Science & ML

Provides expert guidance and R implementation patterns for survival analysis methods and non-proportional hazards in clinical trials.

This skill empowers Claude to assist biostatisticians and clinical researchers in selecting, justifying, and implementing advanced survival analysis methods. It covers a comprehensive range of techniques including weighted logrank tests (Fleming-Harrington, Magirr-Burman), MaxCombo tests, Restricted Mean Survival Time (RMST), and milestone analysis. By providing specific simtrial R package implementation patterns and decision algorithms for handling non-proportional hazards (NPH), it ensures robust study design, accurate power simulations, and regulatory-aligned statistical analysis plans.

Key Features

010 GitHub stars

02Power comparison data across various hazard scenarios to optimize study design

03Implementation patterns for Fleming-Harrington and Magirr-Burman weighted logrank tests

04Restricted Mean Survival Time (RMST) and milestone analysis implementations in R

05Selection algorithms for handling diverse non-proportional hazards (NPH) patterns

06Configuration of robust MaxCombo tests for scenarios with uncertain treatment delays

Use Cases

01Designing clinical trial protocols with expected delayed treatment effects or crossing hazards

02Documenting statistical justifications for primary analysis method selection for regulatory submissions

03Implementing complex sensitivity analyses for survival endpoints using the simtrial R package

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add choxos/biostatagent time-to-event-methods

For use in Claude.ai and ChatGPT

Key Features

010 GitHub stars

02Power comparison data across various hazard scenarios to optimize study design

03Implementation patterns for Fleming-Harrington and Magirr-Burman weighted logrank tests

04Restricted Mean Survival Time (RMST) and milestone analysis implementations in R

05Selection algorithms for handling diverse non-proportional hazards (NPH) patterns

06Configuration of robust MaxCombo tests for scenarios with uncertain treatment delays

Use Cases

01Designing clinical trial protocols with expected delayed treatment effects or crossing hazards

02Documenting statistical justifications for primary analysis method selection for regulatory submissions

03Implementing complex sensitivity analyses for survival endpoints using the simtrial R package