The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Derivation, validation, and evaluation of a new QRISK model to estimate lifetime risk of cardiovascular disease: cohort study using QResearch database
Open accessAbstract
OBJECTIVE: To develop, validate, and evaluate a new QRISK model to estimate lifetime risk of cardiovascular disease. DESIGN: Prospective cohort study with routinely collected data from general practice. Cox proportional hazards models in the derivation cohort to derive risk equations accounting for competing risks. Measures of calibration and discrimination in the validation cohort. SETTING: 563 general practices in England and Wales contributing to the QResearch database. SUBJECTS: Patients aged 30-84 years who were free of cardiovascular disease and not taking statins between 1 January 1994 and 30 April 2010: 2 343 759 in the derivation dataset, and 1 267 159 in the validation dataset. Main outcomes measures Individualised estimate of lifetime risk of cardiovascular disease accounting for smoking status, ethnic group, systolic blood pressure, ratio of total cholesterol:high density lipoprotein cholesterol, body mass index, family history of coronary heart disease in first degree relative aged <60 years, Townsend deprivation score, treated hypertension, rheumatoid arthritis, chronic renal disease, type 2 diabetes, and atrial fibrillation. Age-sex centile values for lifetime cardiovascular risk compared with 10 year risk estimated using QRISK2 (2010). RESULTS: Across all the 1 267 159 patients in the validation dataset, the 50th, 75th, 90th, and 95th centile values for lifetime risk were 31%, 39%, 50%, and 57% respectively. Of the 10% of patients in the validation cohort classified at highest risk with either the lifetime risk model or the 10 year risk model, only 18 385(14.5%) were at high risk on both measures. Patients identified as high risk with the lifetime risk approach were more likely to be younger, male, from ethnic minority groups, and have a positive family history of premature coronary heart disease than those identified with the 10 year QRISK2 score. The lifetime risk calculator is available at www.qrisk.org/lifetime/. CONCLUSIONS: Compared with using a 10 year QRISK2 score, a lifetime risk score will tend to identify patients for intervention at a younger age. Although lifestyle interventions at an earlier age could be advantageous, there would be small gains under the age of 65, and medical interventions carry risks as soon as they are initiated. Research is needed to examine closely the cost effectiveness and acceptability of such an approach.
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Cites
Statins and risk of incident diabetes: A collaborative meta-analysis of randomised statin trials
Sattar, N., Preiss, D., Murray, H. M., Welsh, P., Buckley, B. M., de Craen, A. J., Seshasai, S. R. K., McMurray, J. J., Freeman, D. J., Jukema, J. W., et al. (2010) · The Lancet · doi:10.1016/s0140-6736(09)61965-6 · Cited by 2,436
Multiple Imputation of Missing Values
Royston, P. (2004) · The Stata Journal: Promoting communications on statistics and Stata · doi:10.1177/1536867x0400400301 · Cited by 2,340 · cited 1×
“We used multiple imputation to replace missing values for systolic blood pressure, total cholesterol:HDL cholesterol ratio, smoking status, and body mass index. We used the ICE procedure in STATA for imputation and included all the predictor variables listed above plus the survival outcome variables for cardiovascular…”
MethodPredicting cardiovascular risk in England and Wales: prospective derivation and validation of QRISK2
Hippisley-Cox, J., Coupland, C., Vinogradova, Y., Robson, J., Minhas, R., Sheikh, A., & Brindle, P. (2008) · BMJ · doi:10.1136/bmj.39609.449676.25 · Cited by 1,459
Self-citationPrediction of lifetime risk for cardiovascular disease by risk factor burden at 50 years of age
Lloyd-Jones, D. M., Leip, E. P., Larson, M. G., D’Agostino, R. B., Beiser, A., Wilson, P. W. F., Wolf, P. A., & Levy, D. (2006) · Circulation · doi:10.1161/circulationaha.105.548206 · Cited by 1,298
A new measure of prognostic separation in survival data
Royston, P., & Sauerbrei, W. (2004) · Statistics in Medicine · doi:10.1002/sim.1621 · Cited by 450
Ray, K. K. (2010) · Archives of Internal Medicine · doi:10.1001/archinternmed.2010.182 · Cited by 446
Screening for cardiovascular risk in asymptomatic patients
Berger, J. S., Jordan, C. O., Lloyd-Jones, D., & Blumenthal, R. S. (2010) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2009.09.066 · Cited by 238
Cooney, M. T., Dudina, A., D'Agostino, R., & Graham, I. M. (2010) · Circulation · doi:10.1161/circulationaha.109.852756 · Cited by 222
Cited by
Rapsomaniki, E., Timmis, A., George, J., Pujades-Rodriguez, M., Shah, A. D., Denaxas, S., White, I. R., Caulfield, M. J., Deanfield, J. E., Smeeth, L., et al. (2014) · The Lancet · doi:10.1016/s0140-6736(14)60685-1 · Cited by 1,643
Agca, R., Heslinga, S. C., Rollefstad, S., Heslinga, M., McInnes, I. B., Peters, M. J. L., Kvien, T. K., Dougados, M., Radner, H., Atzeni, F., et al. (2017) · Annals of the Rheumatic Diseases · doi:10.1136/annrheumdis-2016-209775 · Cited by 1,380
Goldstein, B. A., Navar, A. M., Pencina, M. J., & Ioannidis, J. P. A. (2017) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocw042 · Cited by 936
Prediction models for cardiovascular disease risk in the general population: systematic review
Damen, J. A. A. G., Hooft, L., Schuit, E., Debray, T. P. A., Collins, G. S., Tzoulaki, I., Lassale, C. M., Siontis, G. C. M., Chiocchia, V., Roberts, C., et al. (2016) · BMJ · doi:10.1136/bmj.i2416 · Cited by 935
JBS3 Board (2014) · Heart · doi:10.1136/heartjnl-2014-305693 · Cited by 608
Metadata
- Authors
- Hippisley-Cox, J., Coupland, C., Robson, J., & Brindle, P.
- Venue
- BMJ
- Publisher
- BMJ
- Published
- 2010-12-09
- Volume
- 341
- Issue
- dec09 1
- Pages
- c6624-c6624
- ISSN
- 0007-1447 (ISSN-L)
- 0959-8138
- 1468-5833
- OpenAlex
- W2089996629
- Cited by
- 364
- References
- 9
- FWCI
- 17.00
- Type
- journal article
- Language
- en
- Open access
- hybrid
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