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Published on: September 16, 2022
Assessing the value of risk predictions by using risk stratification tables
Holly Janes1, Margaret S Pepe, Wen Gu
1Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, USA. hjanes@scharp.org
Annals of Internal Medicine
|November 20, 2008
Summary
Risk stratification tables offer a novel method for evaluating new risk markers in disease prediction models. This approach improves upon traditional measures by assessing calibration, stratification capacity, and classification accuracy for better clinical decision-making.
Area of Science:
- Epidemiology
- Biostatistics
- Clinical Prediction Modeling
Background:
- Numerous studies assess statistical models for predicting disease and adverse events.
- Evaluating the added benefit of new risk markers to existing prediction models is crucial.
Purpose of the Study:
- To introduce and demonstrate the utility of risk stratification tables.
- To compare the performance of risk prediction models with and without new risk markers.
Main Methods:
- Cross-tabulating risk predictions from models with and without the new marker.
- Evaluating calibration, stratification capacity, and classification accuracy.
Main Results:
- Risk stratification tables provide a comprehensive comparison of model performance.
- This method offers significant improvements over traditional measures like c-statistics and Hosmer-Lemeshow tests.
Conclusions:
- Risk stratification tables offer superior insights into the clinical utility of risk prediction models.
- This approach enhances the ability to guide medical decisions effectively.
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