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Updated: Jun 22, 2026
04:57
Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Hazard ratio funnel plots for survival comparisons.
1Trent Cancer Registry, and NIHR Research Design Service for East Midlands, Nottingham, UK. paul.silcocks@nhs.net
Journal of Epidemiology and Community Health
|June 23, 2009
Summary
Funnel plots using hazard ratios offer a clearer view of institutional performance than traditional survival plots. This method enhances data interpretation for healthcare quality monitoring.
Area of Science:
- Biostatistics
- Health Services Research
- Survival Analysis
Background:
- Funnel plots are control charts visualizing institutional performance at a specific time.
- Existing methods for survival analysis visualization have limitations.
Purpose of the Study:
- To describe the construction of funnel plots for survival analyses using hazard ratios.
- To provide a method for adjusting for covariates and overdispersion in Cox regression models.
Main Methods:
- Utilized Cox regression to obtain adjusted hazard ratio estimates.
- Incorporated methods to account for overdispersion using model or log-rank chi-squared statistics.
- Applied the methodology to both simulated and real survival data.
Main Results:
- Demonstrated the process of generating centered hazard ratio estimates.
- Presented detailed programming instructions for Stata implementation.
- Showcased results from simulated data and a practical healthcare example.
Conclusions:
- Hazard ratio-based funnel plots are more interpretable and less prone to bias than survival-based plots.
- Meta-analysis techniques can further improve the interpretation of these plots.
- This approach offers valuable comparative insights for healthcare organizations like Cancer Registries and Primary Care Trusts.
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