ArticleStatistics in medicine2017
The use of repeated blood pressure measures for cardiovascular risk prediction: a comparison of statistical models in the ARIC study.
Article in Statistics in medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 2 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
31 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Informative presence and observation in routine health data: A review of methodology for clinical risk prediction.Journal of the American Medical Informatics Association : JAMIA · 2021Pooled it
- Use of Repeated Blood Pressure and Cholesterol Measurements to Improve Cardiovascular Disease Risk Prediction: An Individual-Participant-Data Meta-Analysis.American journal of epidemiology · 2017Pooled it
- The use of blood test trends in cancer detection: a scoping review.Diagnostic and prognostic research · 2026Review
- Review
- Automated assessment of breast arterial calcification: a new frontier in cardiovascular risk prediction.Frontiers in cardiovascular medicine · 2026Review
- Delayed kernels for longitudinal survival analysis and dynamic prediction.Statistical methods in medical research · 2024Article
- Young Infants Clinical Signs Study 8-sign Algorithm for Identification of Sick Infants Adapted for Routine Home Visits: A Systematic Review and Critical Appraisal of its Measurement Properties.Global pediatric health · 2024Review
- Dynamic Risk Prediction of Treatment Discontinuation Using Patient-Reported Outcomes Data in the Phase III NSABP B-35 Trial.Cancer prevention research (Philadelphia, Pa.) · 2023Article
- Using Polygenic Risk Scores for Prioritizing Individuals at Greatest Need of a Cardiovascular Disease Risk Assessment.Journal of the American Heart Association · 2023Article
- DYNAMIC RISK PREDICTION TRIGGERED BY INTERMEDIATE EVENTS USING SURVIVAL TREE ENSEMBLES.The annals of applied statistics · 2023Article
- Multivariate longitudinal data for survival analysis of cardiovascular event prediction in young adults: insights from a comparative explainable study.BMC medical research methodology · 2023Observational
- Incremental value of risk factor variability for cardiovascular risk prediction in individuals with type 2 diabetes: results from UK primary care electronic health records.International journal of epidemiology · 2022Article
- Comparing statistical methods in assessing the prognostic effect of biomarker variability on time-to-event clinical outcomes.BMC medical research methodology · 2022Article
- Individual dynamic prediction of clinical endpoint from large dimensional longitudinal biomarker history: a landmark approach.BMC medical research methodology · 2022Article
- Landmarking 2.0: Bridging the gap between joint models and landmarking.Statistics in medicine · 2022Article
- Associations of longitudinal D-Dimer and Factor II on early trauma survival risk.BMC bioinformatics · 2021Article
- Optimal blood pressure for patients with chronic kidney disease: a nationwide population-based cohort study.Scientific reports · 2021Article
- Age-Specific Associations Between Systolic Blood Pressure and Cardiovascular Disease: A 10-Year Diabetes Mellitus Cohort Study.Journal of the American Heart Association · 2020Article
- Harnessing repeated measurements of predictor variables for clinical risk prediction: a review of existing methods.Diagnostic and prognostic research · 2020Review
- Association of Blood Pressure and Risk of Cardiovascular and Chronic Kidney Disease in Hong Kong Hypertensive Patients.Hypertension (Dallas, Tex. : 1979) · 2019Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Many prediction models have been developed for the risk assessment and the prevention of cardiovascular disease in primary care. Recent efforts have focused on improving the accuracy of these prediction models by adding novel biomarkers to a common set of baseline risk predictors. Few have considered incorporating repeated measures of the common risk predictors. Through application to the Atherosclerosis Risk in Communities study and simulations, we compare models that use simple summary measures of the repeat information on systolic blood pressure, such as (i) baseline only; (ii) last observation carried forward; and (iii) cumulative mean, against more complex methods that model the repeat information using (iv) ordinary regression calibration; (v) risk-set regression calibration; and (vi) joint longitudinal and survival models. In comparison with the baseline-only model, we observed modest improvements in discrimination and calibration using the cumulative mean of systolic blood pressure, but little further improvement from any of the complex methods. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.