The added value of incorporating information from repeated blood pressure and cholesterol measurements to predict cardiovascular disease (CVD) risk has not been rigorously assessed. We used data on 191,445 adults from the Emerging Risk Factors Collaboration (38 cohorts from 17 countries with data encompassing 1962-2014) with more than 1 million measurements of systolic blood pressure, total cholesterol, and high-density lipoprotein cholesterol. Over a median 12 years of follow-up, 21,170 CVD events occurred. Risk prediction models using cumulative mean values of repeated measurements and summary measures from longitudinal modeling of the repeated measurements were compared with models using measurements from a single time point. Risk discrimination (Cindex) and net reclassification were calculated, and changes in C-indices were meta-analyzed across studies. Compared with the single-time-point model, the cumulative means and longitudinal models increased the C-index by 0.0040 (95% confidence interval (CI): 0.0023, 0.0057) and 0.0023 (95% CI: 0.0005, 0.0042), respectively. Reclassification was also improved in both models; compared with the single-time-point model, overall net reclassification improvements were 0.0369 (95% CI: 0.0303, 0.0436) for the cumulative-means model and 0.0177 (95% CI: 0.0110, 0.0243) for the longitudinal model. In conclusion, incorporating repeated measurements of blood pressure and cholesterol into CVD risk prediction models slightly improves risk prediction.
Bibliographical noteFunding Information:
This work was funded by the Medical Research Council (grants MR/L003120/1, MR/K014811/1, and G0902100), the British Heart Foundation (grant RG/13/13/30,194), and the NIHR Cambridge Biomedical Research Centre. The website of the Emerging Risk Factors Collaboration (http:// www.phpc.cam.ac.uk/ceu/erfc/list-of-studies/) contains a list, provided by investigators, of some of the funders of the component studies included in this analysis. B.M.P. serves on the data safety monitoring board of a clinical trial funded by Zoll Lifecor Corporation (Pittsburgh, Pennsylvania) and in the Yale University Open Data Access Project, which is funded by Johnson & Johnson (New Brunswick, New Jersey).
© 2017 The Author(s). Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved.
- Cardiovascular disease
- Longitudinal measurements
- Repeated measurements
- Risk factors
- Risk prediction