Impact of sample size on the stability of risk scores from clinical prediction models: a case study in cardiovascular disease.

ABSTRACT:

Background

Stability of risk estimates from prediction models may be highly dependent on the sample size of the dataset available for model derivation. In this paper, we evaluate the stability of cardiovascular disease risk scores for individual patients when using different sample sizes for model derivation; such sample sizes include those similar to models recommended in the national guidelines, and those based on recently published sample size formula for prediction models.

Methods

We mimicked the process of sampling N patients from a population to develop a risk prediction model by sampling patients from the Clinical Practice Research Datalink. A cardiovascular disease risk prediction model was developed on this sample and used to generate risk scores for an indep

SUBMITTER: Pate A 

PROVIDER: S-EPMC7487849 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature