Independent external validation of the QRISK3 cardiovascular disease risk prediction model using UK Biobank
- PMID: 37423742
- PMCID: PMC10646868
- DOI: 10.1136/heartjnl-2022-321231
Independent external validation of the QRISK3 cardiovascular disease risk prediction model using UK Biobank
Abstract
Objective: To externally evaluate the performance of QRISK3 for predicting 10 year risk of cardiovascular disease (CVD) in the UK Biobank cohort.
Methods: We used data from the UK Biobank, a large-scale prospective cohort study of 403 370 participants aged 40-69 years recruited between 2006 and 2010 in the UK. We included participants with no previous history of CVD or statin treatment and defined the outcome to be the first occurrence of coronary heart disease, ischaemic stroke or transient ischaemic attack, derived from linked hospital inpatient records and death registrations.
Results: Our study population included 233 233 women and 170 137 men, with 9295 and 13 028 incident CVD events, respectively. Overall, QRISK3 had moderate discrimination for UK Biobank participants (Harrell's C-statistic 0.722 in women and 0.697 in men) and discrimination declined by age (<0.62 in all participants aged 65 years or older). QRISK3 systematically overpredicted CVD risk in UK Biobank, particularly in older participants, by as much as 20%.
Conclusions: QRISK3 had moderate overall discrimination in UK Biobank, which was best in younger participants. The observed CVD risk for UK Biobank participants was lower than that predicted by QRISK3, particularly for older participants. It may be necessary to recalibrate QRISK3 or use an alternate model in studies that require accurate CVD risk prediction in UK Biobank.
Keywords: Epidemiology; Risk Factors.
© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.
Conflict of interest statement
Competing interests: None declared.
Figures



Similar articles
-
Validation of a deep-learning-based retinal biomarker (Reti-CVD) in the prediction of cardiovascular disease: data from UK Biobank.BMC Med. 2023 Jan 24;21(1):28. doi: 10.1186/s12916-022-02684-8. BMC Med. 2023. PMID: 36691041 Free PMC article.
-
Effect of competing mortality risks on predictive performance of the QRISK3 cardiovascular risk prediction tool in older people and those with comorbidity: external validation population cohort study.Lancet Healthy Longev. 2021 Jun;2(6):e352-e361. doi: 10.1016/S2666-7568(21)00088-X. Lancet Healthy Longev. 2021. PMID: 34100008 Free PMC article.
-
Predictive performance of a competing risk cardiovascular prediction tool CRISK compared to QRISK3 in older people and those with comorbidity: population cohort study.BMC Med. 2022 May 4;20(1):152. doi: 10.1186/s12916-022-02349-6. BMC Med. 2022. PMID: 35505353 Free PMC article.
-
United Kingdom Biobank (UK Biobank): JACC Focus Seminar 6/8.J Am Coll Cardiol. 2021 Jul 6;78(1):56-65. doi: 10.1016/j.jacc.2021.03.342. J Am Coll Cardiol. 2021. PMID: 34210415 Review.
-
Trends in the epidemiology of cardiovascular disease in the UK.Heart. 2016 Dec 15;102(24):1945-1952. doi: 10.1136/heartjnl-2016-309573. Epub 2016 Aug 22. Heart. 2016. PMID: 27550425 Free PMC article. Review.
Cited by
-
Comparative Effects of Time-Restricted Eating and the Ketogenic Diet on QRISK3-Assessed Cardiovascular Risk in Individuals with Obesity: A Longitudinal Analysis of Metabolic, Anthropometric, and Lifestyle Factors.Nutrients. 2025 Jun 9;17(12):1963. doi: 10.3390/nu17121963. Nutrients. 2025. PMID: 40573074 Free PMC article.
-
Comprehensive interaction modeling with machine learning improves prediction of disease risk in the UK Biobank.Nat Commun. 2025 Jul 18;16(1):6620. doi: 10.1038/s41467-025-61891-y. Nat Commun. 2025. PMID: 40681488 Free PMC article.
-
Review and Comparative Evaluation of Mobile Apps for Cardiovascular Risk Estimation: Usability Evaluation Using mHealth App Usability Questionnaire.JMIR Mhealth Uhealth. 2025 May 8;13:e56466. doi: 10.2196/56466. JMIR Mhealth Uhealth. 2025. PMID: 40341099 Free PMC article. Review.
-
Performance of PREVENT and pooled cohort equations for predicting 10-Year ASCVD risk in the UK Biobank.Am J Prev Cardiol. 2025 May 18;22:101009. doi: 10.1016/j.ajpc.2025.101009. eCollection 2025 Jun. Am J Prev Cardiol. 2025. PMID: 40510258 Free PMC article.
-
Genomic and Precision Medicine Approaches in Atherosclerotic Cardiovascular Disease: From Risk Prediction to Therapy-A Review.Biomedicines. 2025 Jul 14;13(7):1723. doi: 10.3390/biomedicines13071723. Biomedicines. 2025. PMID: 40722793 Free PMC article. Review.
References
-
- World Health Organization (WHO) . WHO reveals leading causes of death and disability worldwide: 2000-2019. World Health Organization (WHO), 2020.
Publication types
MeSH terms
Grants and funding
LinkOut - more resources
Full Text Sources
Medical