External validation of clinical prediction models using big datasets from e-health records or IPD meta-analysis: opportunities and challenges

Access to big datasets from e-health records and individual participant data (IPD) meta-analysis is signalling a new advent of external validation studies for clinical prediction models. In this article, the authors illustrate novel opportunities for external validation in big, combined datasets, while drawing attention to methodological challenges and reporting issues. #### Summary points A popular type of clinical research is the development of statistical models that predict disease presence and outcome occurrence in individuals,123 thereby informing clinical diagnosis and prognosis. Such models are referred to here as diagnostic and prognostic prediction models, but they have many other names including risk models, risk scores, and clinical prediction rules. They are typically developed by use of a multivariable regression framework, which provides an equation to estimate an individual’s risk based on values of multiple predictors (such as age and smoking, or biomarkers and genetic information). …