Pennells, L.* ; Kaptoge, S.* ; Wood, A.* ; Sweeting, M.* ; Zhao, X.* ; White, I.* ; Burgess, S.* ; Willeit, P.* ; Bolton, T.* ; Moons, K.G.M.* ; van der Schouw, Y.T.* ; Selmer, R.* ; Khaw, K.T.* ; Gudnason, V.* ; Assmann, G.* ; Amouyel, P.* ; Salomaa, V.* ; Kivimaki, M.* ; Nørdestgaard, B.G.* ; Blaha, M.J.* ; Kuller, L.H.* ; Brenner, H.* ; Gillum, R.F.* ; Meisinger, C. ; Ford, I.* ; Knuiman, M.W.* ; Rosengren, A.* ; Lawlor, D.A.* ; Völzke, H.* ; Cooper, C.* ; Marín Ibañez, A.* ; Casiglia, E.* ; Kauhanen, J.* ; Cooper, J.A.* ; Rodriguez, B.* ; Sundström, J.* ; Barrett-Connor, E.* ; Dankner, R.* ; Nietert, P.J.* ; Davidson, K.W.* ; Wallace, R.B.* ; Blazer, D.G.* ; Björkelund, C.* ; Donfrancesco, C.* ; Krumholz, H.M.* ; Nissinen, A.* ; Davis, B.R.* ; Coady, S.* ; Whincup, P.H.* ; Jørgensen, T.* ; Ducimetiere, P.* ; Trevisan, M.* ; Engström, G.* ; Crespo, C.J.* ; Meade, T.W.* ; Visser, M.* ; Kromhout, D.* ; Kiechl, S.* ; Daimon, M.* ; Price, J.F.* ; Gómez de la Cámara, A.* ; Wouter Jukema, J.* ; Lamarche, B.* ; Onat, A.* ; Simons, L.A.* ; Kavousi, M.* ; Ben-Shlomo, Y.* ; Gallacher, J.* ; Dekker, J.M.* ; Arima, H.* ; Shara, N.* ; Tipping, R.W.* ; Roussel, R.* ; Brunner, E.J.* ; Koenig, W.* ; Sakurai, M.* ; Pavlovic, J.* ; Gansevoort, R.T.* ; Nagel, D.* ; Goldbourt, U.* ; Barr, E.L.M.* ; Palmieri, L.* ; Njølstad, I.* ; Sato, S.* ; Monique Verschuren, W.M.* ; Varghese, C.V.* ; Graham, I.* ; Onuma, O.* ; Greenland, P.* ; Woodward, M.* ; Ezzati, M.* ; Psaty, B.M.* ; Sattar, N.* ; Jackson, R.* ; Ridker, P.M.* ; Cook, N.R.* ; D'Agostino, R.B.* ; Thompson, S.G.* ; Danesh, J.* ; di Angelantonio, E.*
Equalization of four cardiovascular risk algorithms after systematic recalibration: Individual-participant meta-analysis of 86 prospective studies.
Eur. Heart J. 40, 621-631 (2019)
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.
Impact Factor
Scopus SNIP
Web of Science
Times Cited
Scopus
Cited By
Altmetric
Publikationstyp
Artikel: Journalartikel
Dokumenttyp
Wissenschaftlicher Artikel
Typ der Hochschulschrift
Herausgeber
Schlagwörter
Cardiovascular Disease ; Risk Prediction ; Risk Algorithms ; Calibration ; Discrimination; Primary Prevention; Disease Prevention; Task-force; Statin Use; Guidelines; Validation; Prediction; Framingham; Scores; Calibration
Keywords plus
Sprache
englisch
Veröffentlichungsjahr
2019
Prepublished im Jahr
2018
HGF-Berichtsjahr
2018
ISSN (print) / ISBN
0195-668X
e-ISSN
1522-9645
ISBN
Bandtitel
Konferenztitel
Konferzenzdatum
Konferenzort
Konferenzband
Quellenangaben
Band: 40,
Heft: 7,
Seiten: 621-631
Artikelnummer: ,
Supplement: ,
Reihe
Verlag
Oxford University Press
Verlagsort
Great Clarendon St, Oxford Ox2 6dp, England
Tag d. mündl. Prüfung
0000-00-00
Betreuer
Gutachter
Prüfer
Topic
Hochschule
Hochschulort
Fakultät
Veröffentlichungsdatum
0000-00-00
Anmeldedatum
0000-00-00
Anmelder/Inhaber
weitere Inhaber
Anmeldeland
Priorität
Begutachtungsstatus
Peer reviewed
POF Topic(s)
30202 - Environmental Health
Forschungsfeld(er)
Genetics and Epidemiology
PSP-Element(e)
G-502900-001
G-504000-006
G-504090-001
Förderungen
Copyright
Erfassungsdatum
2018-12-20