Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 621-631 |
| Number of pages | 11 |
| Journal | European heart journal |
| Volume | 40 |
| Issue number | 7 |
| DOIs | |
| Publication status | Published - Feb 14 2019 |
All Science Journal Classification (ASJC) codes
- Cardiology and Cardiovascular Medicine
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In: European heart journal, Vol. 40, No. 7, 14.02.2019, p. 621-631.
Research output: Contribution to journal › Article › peer-review
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TY - JOUR
T1 - Equalization of four cardiovascular risk algorithms after systematic recalibration
T2 - Individual-participant meta-analysis of 86 prospective studies
AU - Pennells, Lisa
AU - Kaptoge, Stephen
AU - Wood, Angela
AU - Sweeting, Mike
AU - Zhao, Xiaohui
AU - White, Ian
AU - Burgess, Stephen
AU - Willeit, Peter
AU - Bolton, Thomas
AU - Moons, Karel G.M.
AU - Van Der Schouw, Yvonne T.
AU - Selmer, Randi
AU - Khaw, Kay Tee
AU - Gudnason, Vilmundur
AU - Assmann, Gerd
AU - Amouyel, Philippe
AU - Salomaa, Veikko
AU - Kivimaki, Mika
AU - Nordestgaard, Børge G.
AU - Blaha, Michael J.
AU - Kuller, Lewis H.
AU - Brenner, Hermann
AU - Gillum, Richard F.
AU - Meisinger, Christa
AU - Ford, Ian
AU - Knuiman, Matthew W.
AU - Rosengren, Annika
AU - Lawlor, Debbie A.
AU - Völzke, Henry
AU - Cooper, Cyrus
AU - Marín Ibañez, Alejandro
AU - Casiglia, Edoardo
AU - Kauhanen, Jussi
AU - Cooper, Jackie A.
AU - Rodriguez, Beatriz
AU - Sundström, Johan
AU - Barrett-Connor, Elizabeth
AU - Dankner, Rachel
AU - Nietert, Paul J.
AU - Davidson, Karina W.
AU - Wallace, Robert B.
AU - Blazer, Dan G.
AU - Björkelund, Cecilia
AU - Donfrancesco, Chiara
AU - Krumholz, Harlan M.
AU - Nissinen, Aulikki
AU - Davis, Barry R.
AU - Coady, Sean
AU - Whincup, Peter H.
AU - Jørgensen, Torben
AU - Ducimetiere, Pierre
AU - Trevisan, Maurizio
AU - Engström, Gunnar
AU - Crespo, Carlos J.
AU - Meade, Tom W.
AU - Visser, Marjolein
AU - Kromhout, Daan
AU - Kiechl, Stefan
AU - Daimon, Makoto
AU - Price, Jackie F.
AU - Gómez De La Cámara, Agustin
AU - Wouter Jukema, J.
AU - Lamarche, Benoît
AU - Onat, Altan
AU - Simons, Leon A.
AU - Kavousi, Maryam
AU - Ben-Shlomo, Yoav
AU - Gallacher, John
AU - Dekker, Jacqueline M.
AU - Arima, Hisatomi
AU - Shara, Nawar
AU - Tipping, Robert W.
AU - Roussel, Ronan
AU - Brunner, Eric J.
AU - Koenig, Wolfgang
AU - Sakurai, Masaru
AU - Pavlovic, Jelena
AU - Gansevoort, Ron T.
AU - Nagel, Dorothea
AU - Goldbourt, Uri
AU - Barr, Elizabeth L.M.
AU - Palmieri, Luigi
AU - Njølstad, Inger
AU - Sato, Shinichi
AU - Monique Verschuren, W. M.
AU - Varghese, Cherian V.
AU - Graham, Ian
AU - Onuma, Oyere
AU - Greenland, Philip
AU - Woodward, Mark
AU - Ezzati, Majid
AU - Psaty, Bruce M.
AU - Sattar, Naveed
AU - Jackson, Rod
AU - Ridker, Paul M.
AU - Cook, Nancy R.
AU - D'Agostino, Ralph B.
AU - Thompson, Simon G.
AU - Danesh, John
AU - Di Angelantonio, Emanuele
AU - Simpson, Lara M.
AU - Pressel, Sara L.
AU - Couper, David J.
AU - Nambi, Vijay
AU - Matsushita, Kunihiro
AU - Folsom, Aaron R.
AU - Shaw, Jonathan E.
AU - Magliano, Dianna J.
AU - Zimmet, Paul Z.
AU - Wannamethee, S. Goya
AU - Willeit, Johann
AU - Santer, Peter
AU - Egger, Georg
AU - Casas, Juan Pablo
AU - Amuzu, Antointtte
AU - Tikhonoff, Valérie
AU - Sutherland, Susan E.
AU - Cushman, Mary
AU - Søgaard, Anne Johanne
AU - Håheim, Lise Lund
AU - Ariansen, Inger
AU - Tybjærg-Hansen, Anne
AU - Jensen, Gorm B.
AU - Schnohr, Peter
AU - Giampaoli, Simona
AU - Vanuzzo, Diego
AU - Panico, Salvatore
AU - Balkau, Beverley
AU - Bonnet, Fabrice
AU - Marre, Michel
AU - De La Cámara, Agustin Gómez
AU - Rubio Herrera, Miguel Angel
AU - Friedlander, Yechiel
AU - McCallum, John
AU - McLachlan, Stela
AU - Guralnik, Jack
AU - Phillips, Caroline L.
AU - Wareham, Nick
AU - Schöttker, Ben
AU - Saum, Kai Uwe
AU - Holleczek, Bernd
AU - Tolonen, Hanna
AU - Vartiainen, Erkki
AU - Jousilahti, Pekka
AU - Harald, Kennet
AU - Massaro, Joseph M.
AU - Pencina, Michael
AU - Vasan, Ramachandran
AU - Kayama, Takamasa
AU - Kato, Takeo
AU - Oizumi, Toshihide
AU - Jespersen, Jørgen
AU - Møller, Lars
AU - Bladbjerg, Else Marie
AU - Chetrit, A.
AU - Wilhelmsen, Lars
AU - Lissner, Lauren
AU - Dennison, Elaine
AU - Kiyohara, Yutaka
AU - Ninomiya, Toshiharu
AU - Doi, Yasufumi
AU - Nijpels, Giel
AU - Stehouwer, Coen D.A.
AU - Kazumasa, Yamagishi
AU - Iso, Hiroyasu
AU - Kurl, Sudhir
AU - Tuomainen, Tomi Pekka
AU - Salonen, Jukka T.
AU - Deeg, Dorly J.H.
AU - Nilsson, Peter M.
AU - Bo, Hedblad
AU - Melander, Olle
AU - De Boer, Ian H.
AU - DeFilippis, Andrew Paul
AU - Verschuren, W. M.Monique
AU - Watt, Graham
AU - Verschuren, W. M.Monique
AU - Tverdal, Aage
AU - Kirkland, Susan
AU - Shimbo, Daichi
AU - Shaffer, Jonathan
AU - Bakker, Stephan J.L.
AU - Van Der Harst, Pim
AU - Hillege, Hans L.
AU - Dallongeville, Jean
AU - Schulte, Helmut
AU - Trompet, Stella
AU - Smit, Roelof A.J.
AU - Stott, David J.
AU - Després, Jean Pierre
AU - Cantin, Bernard
AU - Dagenais, Gilles R.
AU - Laughlin, Gail
AU - Wingard, Deborah
AU - Aspelund, Thor
AU - Eiriksdottir, Gudny
AU - Gudmundsson, Elias Freyr
AU - Ikram, Arfan
AU - Van Rooij, Frank J.A.
AU - Franco, Oscar H.
AU - Rueda-Ochoa, Oscar L.
AU - Muka, Taulant
AU - Glisic, Marija
AU - Tunstall-Pedoe, Hugh
AU - Howard, Barbara V.
AU - Ying, Zhang
AU - Jolly, Stacey
AU - Davey-Smith, George
AU - Can, Günay
AU - Yüksel, Hüsniye
AU - Nakagawa, Hideaki
AU - Morikawa, Yuko
AU - Miura, Katsuyuki
AU - Ingelsson, Martin
AU - Giedraitis, Vilmantas
AU - Gaziano, J. Michael
AU - Shipley, Martin
AU - Arndt, Volker
AU - Ibañez, Alejandro Marín
AU - Geleijnse, Johanna M.
N1 - Funding 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. Funding Information: 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. Funding Information: 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 Publisher Copyright: © 2018 The Author(s). Published by Oxford University Press on behalf of the European Society of Cardiology.
PY - 2019/2/14
Y1 - 2019/2/14
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85061592905&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85061592905&partnerID=8YFLogxK
U2 - 10.1093/eurheartj/ehy653
DO - 10.1093/eurheartj/ehy653
M3 - Article
C2 - 30476079
AN - SCOPUS:85061592905
SN - 0195-668X
VL - 40
SP - 621
EP - 631
JO - European Heart Journal
JF - European Heart Journal
IS - 7
ER -