The uncertainty with using risk prediction models for individual decision making: an exemplar cohort study examining the prediction of cardiovascular disease in English primary care.

ABSTRACT:

Background

Risk prediction models are commonly used in practice to inform decisions on patients' treatment. Uncertainty around risk scores beyond the confidence interval is rarely explored. We conducted an uncertainty analysis of the QRISK prediction tool to evaluate the robustness of individual risk predictions with varying modelling decisions.

Methods

We derived a cohort of patients eligible for cardiovascular risk prediction from the Clinical Practice Research Datalink (CPRD) with linked hospitalisation and mortality records (N = 3,792,474). Risk prediction models were developed using the methods reported for QRISK2 and 3, before adjusting for additional risk factors, a secular trend, geographical variation in risk and the method for imputing missing data when generating

SUBMITTER: Pate A 

PROVIDER: S-EPMC6636064 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature