- Rod Jackson, professor of epidemiology,
- Roger Marshall, associate professor of biostatistics,
- Andrew Kerr, cardiologist and clinical senior lecturer,
- Tania Riddell, senior research fellow,
- Sue Wells, senior lecturer in clinical epidemiology and quality improvement
- 1School of Population Health, University of Auckland, Private Bag 92019, Auckland, New Zealand
- rt.jackson{at}auckland.ac.nz
In the linked study (doi: 10.1136/bmj.b2584), Collins and Altman assess the performance of the QRISK cardiovascular risk prediction algorithm in a primary care setting in the United Kingdom,1 and compare QRISK2 3 with equivalent Framingham algorithms.4 5
The QRISK algorithm is based on the largest risk prediction study ever undertaken and highlights a potential use of large scale electronic health record systems.2 3 6 In just a few years, a small team has linked electronic health records from several million people to produce a cardiovascular risk prediction algorithm that is more accurate and better validated than previous ones. Although prediction algorithms are available for many conditions, most are based on small numbers, are poorly validated, infrequently updated, and not generalisable. Moreover, most prediction algorithms are weak predictors and are not used regularly.
The first QRISK prediction algorithm was generated by retrospectively extracting data on risk factors and subsequent cardiovascular events for almost two million people from the QRESEARCH primary care database of more than 10 million patients covering about 7% of the …
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