FREE WEBINAR
Exploring Survival Analysis Designs for Clinical Trials
Survival analysis is one of the most common statistical approaches used in clinical trials, especially in clinical areas such as oncology. In this tutorial, Paul Murphy, research statistician at nQuery, has delved into survival analysis within the context of clinical trials and scrutinised various challenges researchers may encounter.
Learning objective of this webinar:
This tutorial covers how to perform power calculations for survival analysis, identify and address challenges in survival power calculations, and apply various statistical procedures, including the Log-Rank Test, Linear-Rank Tests (Fleming-Harrington & Modestly Weighted Tests), and the MaxCombo procedure.
Key Areas Covered:
1. Power Calculations for Survival Analysis
- Understanding the importance of power calculations in survival analysis.
- Determining the necessary sample size to achieve desired statistical power.
2. Inputs Required for Survival Power Calculations
- Identifying essential parameters such as effect size, hazard ratio, and event rate.
- Assessing variability and distribution of survival times.
3. Issues & Challenges for Survival Power Calculations
- Addressing challenges like varying accrual rates, dropout patterns, and unequal follow-up durations.
- Managing non-proportional hazards and their impact on analysis.
4. Demonstration of Survival Analysis Procedures
- Applying the Log-Rank Test for comparing survival distributions between groups.
- Utilizing Linear-Rank Tests, including Fleming-Harrington and Modestly Weighted Tests.
- Implementing the MaxCombo Procedure for combining multiple tests to enhance power.
About nQuery
nQuery helps make your clinical trials faster, less costly and more successful.
It is an end-to-end platform covering Frequentist, Bayesian, and Adaptive designs with 1000+ sample size procedures.
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