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Survival analysis 101: an easy start guide to analysing time-to-event data
Quin E Denfeld1,2, Debora Burger1, Christopher S Lee3,4
1School of Nursing, Oregon Health & Science University, Portland, OR, USA.
European Journal of Cardiovascular Nursing
|February 7, 2023
Summary
This guide explains survival analysis, a method for analyzing time-to-event data in health research. It provides a step-by-step approach using heart failure patient data to predict cardiovascular events.
Area of Science:
- Cardiovascular Nursing
- Health-Related Research
- Biostatistics
Background:
- Survival analysis, or time-to-event analysis, is crucial for handling event data in health research.
- Specific methodologies are required to address the unique characteristics of event data.
- Understanding event timing is vital for clinical and research applications.
Purpose of the Study:
- To provide an accessible "easy start guide" to survival analysis methods.
- To demonstrate the application of survival analysis using real-world cardiovascular event data.
- To facilitate the use of survival analysis in nursing and health-related research.
Main Methods:
- A step-by-step instructional approach to survival analysis.
- Application of survival analysis techniques to a 6-month cardiovascular event dataset.
- Utilizing example data from a sample of heart failure patients.
Main Results:
- Demonstration of survival analysis steps applied to cardiovascular event data.
- Illustrative analysis of time-to-event data in heart failure patients.
- Practical insights into describing, explaining, and predicting event occurrence and timing.
Conclusions:
- Survival analysis is a valuable tool for cardiovascular nursing and health research.
- The provided guide simplifies the application of survival analysis for researchers.
- Effective analysis of event data can improve understanding and prediction of cardiovascular outcomes.
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