Aims There is debate about the optimum algorithm for cardiovascular disease (CVD) risk estimation. We conducted head-to-head comparisons of four algorithms recommended by primary prevention guidelines, before and after 'recalibration', a method that adapts risk algorithms to take account of differences in the risk characteristics of the populations being studied. Methods and results Using individual-participant data on 360 737 participants without CVD at baseline in 86 prospective studies from 22 countries, we compared the Framingham risk score (FRS), Systematic COronary Risk Evaluation (SCORE), pooled cohort equations (PCE), and Reynolds risk score (RRS). We calculated measures of risk discrimination and calibration, and modelled clinical implications of initiating statin therapy in people judged to be at 'high' 10 year CVD risk. Original risk algorithms were recalibrated using the risk factor profile and CVD incidence of target populations. The four algorithms had similar risk discrimination. Before recalibration, FRS, SCORE, and PCE over-predicted CVD risk on average by 10%, 52%, and 41%, respectively, whereas RRS under-predicted by 10%. Original versions of algorithms classified 29-39% of individuals aged ≥40 years as high risk. By contrast, recalibration reduced this proportion to 22-24% for every algorithm. We estimated that to prevent one CVD event, it would be necessary to initiate statin therapy in 44-51 such individuals using original algorithms, in contrast to 37-39 individuals with recalibrated algorithms. Conclusion Before recalibration, the clinical performance of four widely used CVD risk algorithms varied substantially. By contrast, simple recalibration nearly equalized their performance and improved modelled targeting of preventive action to clinical need.
Bibliographical noteFunding Information:
from Novartis, Kowa, Pfizer, NHLBI, outside the submitted work; he is listed as a co-inventor on patents held by the Brigham and Women’s Hospital that relate to the use of inflammatory biomarkers in cardiovascular disease and diabetes that have been licensed to AstraZeneka and Seimens; R.R. reports grants, personal fees and non-financial support from Sanofi, MSD, Amgen, Physiogenex, Astra-Zeneca, Novo Nordisk, Janssen, Eli Lilly, Abbott, Medtronic, Servier, outside the submitted work; V.S. reports personal fees from Novo Nordisk outside the submitted work; N.S. reports grants and personal fees from Amgen, AstraZeneca, Boehringer Ingelheim, Eli Lilly, Janssen, Novo Nordisk, Sanofi, outside the submitted work; S.G.T. reports grants from UK Medical Research Council, and British Heart Foundation, during the conduct of the study; P.W. reports personal fees from Novartis Pharmaceuticals, outside the submitted work; M.W. reports personal fees from Amgen, outside the submitted work. The other authors declare no competing interests.
The work of the co-ordinating centre was funded by the UK Medical Research Council (G0800270), British Heart Foundation (SP/09/ 002), British Heart Foundation Cambridge Cardiovascular Centre of Excellence, UK National Institute for Health Research Cambridge Biomedical Research Centre, European Research Council (268834), and European Commission Framework Programme 7 (HEALTH-F2-2012-279233). The Emerging Risk Factor Collaboration’s website https://www.phpc.cam.ac.uk/ceu/erfc/list-of-studies/ has compiled a list provided by investigators of some of the funders of the component studies in this analysis. I.W. was supported by the Medical Research Council Unit Programme MC_UU_12023/21. M.K. is supported by the Netherlands Organization for Scientific Research (NWO) Veni grant (Veni, 91616079). J.P. is supported by Erasmus Mundus Western Balkans (ERAWEB), a project funded by the European Commission.
Conflict of interest: H.A. reports personal fees from Bayer, Daiichi-Sankyo, Fukuda Denshi and Takeda, outside the submitted work; P.A. reports personal fees from Servier, Total, Genoscreen, Takeda, Fondation Alzheimer, outside the submitted work; M.J.B. reports grants and personal fees from National Institute of Health, American Heart Association, FDA, Aetna Foundation, Amgen, Novartis, MedImmune, Sanofi/Regeneron, outside the submitted work; C.C. reports personal fees from Alliance for Better Bone Health, Amgen, Eli Lilly, GSK, Medtronic, Merck, Novartis, Pfizer, Roche, Servier, Takeda and UCB; E.D.A. reports grants from European Commission Framework 7, the European Research Council, the British Heart Foundation, the UK Medical Research Council, National Institute for Health Research, and NHS Blood and Transplant, outside the submitted work; J.D. reports grants from the UK Medical Research Council, the British Heart Foundation, the UK National Institute of Health Research, and the European Commission, during the conduct of the study; personal fees and nonfinancial support from Merck Sharp and Dohme UK Atherosclerosis, personal fees and non-financial support from Novartis Cardiovascular and Metabolic Advisory Board, grants from the British Heart Foundation, European Research Council, Merck, the National Institute of Health Research, NHS Blood and Transplant, Novartis, Pfizer, the UK Medical Research Council, the Wellcome Trust, and AstraZeneca, and personal fees and non-financial support from Pfizer Population Research Advisory Panel, outside the submitted work; M.E. reports grant from Young Health Programme of AstraZeneca, and personal fees from Prudential, Scor, and Third Bridge, all outside the submitted work; M.K. reports grant from the Medical Research Council; H.M.K. reports personal fees from UnitedHealth, Hugo, IBM Watson Health, Element Science, Aetna, Centers for Medicare & Medicaid Services, and grants from Medtronic, and FDA, outside the submitted work; S.Ki reports grants from the Austrian Research Promotion Agency FFG, outside the submitted work; S.Ka reports grants from UK Medical Research Council, and British Heart Foundation, during the conduct of the study; W.K. reports personal fees from AstraZeneca, Novartis, Pfizer, The Medicines Company, DalCor, Sanofi, Berlin-Chemie, Kowa, Amgen, grants and non-financial support from Roche Diagnostics, Beckmann, Singulex, Abbott, outside the submitted work; P.J.N. reports grants from National Institutes of Health, during the conduct of the study; B.M.P. reports that he serves on the DSMB of a clinical trial funded by Zoll LifeCor and on the Steering Committee of the Yale Open Data Access Project funded by Johnson & Johnson; P.M.R. reports grants
© 2018 The Author(s). Published by Oxford University Press on behalf of the European Society of Cardiology.
- Cardiovascular disease
- Risk algorithms
- Risk prediction