ArticleBMC cardiovascular disorders2023
External validation of the QLifetime cardiovascular risk prediction tool: population cohort study.
Article in BMC cardiovascular disorders, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.
- Discrimination and calibration performances of non-laboratory-based and laboratory-based cardiovascular risk predictions: a systematic review.Open heart · 2025Pooled it
- Prediction of Prevalent Cardiovascular Disease Using Social, Environmental, and Behavioral Factors: A Vital Conditions Framework Approach.Chronic diseases and translational medicine · 2026Article
- Dyslipidaemia and cardiovascular risk - Key considerations in South Asians.Clinical medicine (London, England) · 2026Review
- Risk prediction for individual patients and the pitfalls of selecting an optimal prediction model: do not judge a model by its c-statistic.European journal of epidemiology · 2026Article
- The value of pregnancy-related factors in the prediction of cardiovascular disease: a systematic review.International journal of cardiology. Cardiovascular risk and prevention · 2025Review
- 2025 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association.Circulation · 2025Review
- Assessment of Lifetime Risk for Cardiovascular Disease: Time to Move Forward.Current cardiology reviews · 2024Review
- Article
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundPrediction of lifetime cardiovascular disease (CVD) risk is recommended in many clinical guidelines, but lifetime risk models are rarely externally validated. The aim of this study was to externally validate the QRiskLifetime incident CVD risk prediction tool.
methodsIndependent external validation of QRiskLifetime using Clinical Practice Research Datalink data, examining discrimination and calibration in the whole population and stratified by age, and reclassification compared to QRISK3. Since lifetime CVD risk is unobservable, performance was evaluated at 10-years' follow-up, and lifetime performance inferred in terms of performance for in the different age-groups from which lifetime predictions are derived.
resultsOne million, two hundreds sixty thousand and three hundreds twenty nine women and 1,223,265 men were included in the analysis. Discrimination was excellent in the whole population (Harrell's-C = 0.844 in women, 0.808 in men), but moderate to poor stratified by age-group (Harrell's C in people aged 30-44 0.714 for both men and women, in people aged 75-84 0.578 in women and 0.556 in men). Ten-year CVD risk was under-predicted in the whole population, and in all age-groups except women aged 45-64, with worse under-prediction in older age-groups. Compared to those at highest QRISK3 estimated 10-year risk, those with highest lifetime risk were younger (mean age: women 50.5 vs. 71.3 years; men 46.3 vs. 63.8 years) and had lower systolic blood pressure and prevalence of treated hypertension, but had more family history of premature CVD, and were more commonly minority ethnic. Over 10-years, the estimated number needed to treat (NNT) with a statin to prevent one CVD event in people with QRISK3 ≥ 10% was 34 in women and 37 in men, compared to 99 and 100 for those at highest lifetime risk.
conclusionsQRiskLifetime underpredicts 10-year CVD risk in nearly all age-groups, so is likely to also underpredict lifetime risk. Treatment based on lifetime risk has considerably lower medium-term benefit than treatment based on 10-year risk.
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