Do population-level risk prediction models that use routinely collected health data reliably predict individual risks?
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Title
Do population-level risk prediction models that use routinely collected health data reliably predict individual risks?
Authors
Keywords
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Journal
Scientific Reports
Volume 9, Issue 1, Pages -
Publisher
Springer Science and Business Media LLC
Online
2019-08-02
DOI
10.1038/s41598-019-47712-5
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Related references
Note: Only part of the references are listed.- Random-effects meta-analysis of the clinical utility of tests and prediction models
- (2018) L. Wynants et al. STATISTICS IN MEDICINE
- Development and validation of QRISK3 risk prediction algorithms to estimate future risk of cardiovascular disease: prospective cohort study
- (2017) Julia Hippisley-Cox et al. BMJ-British Medical Journal
- Development and validation of QRISK3 risk prediction algorithms to estimate future risk of cardiovascular disease: prospective cohort study
- (2017) Julia Hippisley-Cox et al. BMJ-British Medical Journal
- 2016 European Guidelines on cardiovascular disease prevention in clinical practice
- (2016) Massimo F. Piepoli et al. EUROPEAN HEART JOURNAL
- Stability metrics for multi-source biomedical data based on simplicial projections from probability distribution distances
- (2016) Carlos Sáez et al. STATISTICAL METHODS IN MEDICAL RESEARCH
- Prediction models for cardiovascular disease risk in the general population: systematic review
- (2016) Johanna A A G Damen et al. BMJ-British Medical Journal
- External validation of clinical prediction models using big datasets from e-health records or IPD meta-analysis: opportunities and challenges
- (2016) Richard D Riley et al. BMJ-British Medical Journal
- Prediction models for cardiovascular disease risk in the general population: systematic review
- (2016) Johanna A A G Damen et al. BMJ-British Medical Journal
- External validation of clinical prediction models using big datasets from e-health records or IPD meta-analysis: opportunities and challenges
- (2016) Richard D Riley et al. BMJ-British Medical Journal
- Data Resource Profile: Clinical Practice Research Datalink (CPRD)
- (2015) Emily Herrett et al. INTERNATIONAL JOURNAL OF EPIDEMIOLOGY
- Prediction of Cardiovascular Risk Using Framingham, ASSIGN and QRISK2: How Well Do They Predict Individual Rather than Population Risk?
- (2014) Tjeerd-Pieter van Staa et al. PLoS One
- The performance of seven QPrediction risk scores in an independent external sample of patients from general practice: a validation study
- (2014) J. Hippisley-Cox et al. BMJ Open
- New perspectives on cardiovascular risk in individuals and in populations
- (2012) Martin O'Flaherty et al. JOURNAL OF EPIDEMIOLOGY AND COMMUNITY HEALTH
- Predicting the 10 year risk of cardiovascular disease in the United Kingdom: independent and external validation of an updated version of QRISK2
- (2012) G. S. Collins et al. BMJ-British Medical Journal
- The Framingham Heart Study's Impact on Global Risk Assessment
- (2010) Asaf Bitton et al. PROGRESS IN CARDIOVASCULAR DISEASES
- Logical analysis of survival data: prognostic survival models by detecting high-degree interactions in right-censored data
- (2008) L.-P. Kronek et al. BIOINFORMATICS
- Rose's Strategy of Preventive Medicine
- (2008) M. Somerville JOURNAL OF PUBLIC HEALTH
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