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Equalization of four cardiovascular risk algorithms after systematic recalibration: individual-participant meta-analysis of 86 prospective studies.

Pennells, L; Kaptoge, S; Wood, A; Sweeting, M; Zhao, X; White, I; Burgess, S; Willeit, P; Bolton, T; Moons, KGM; et al. Pennells, L; Kaptoge, S; Wood, A; Sweeting, M; Zhao, X; White, I; Burgess, S; Willeit, P; Bolton, T; Moons, KGM; van der Schouw, YT; Selmer, R; Khaw, K-T; Gudnason, V; Assmann, G; Amouyel, P; Salomaa, V; Kivimaki, M; Nordestgaard, BG; Blaha, MJ; Kuller, LH; Brenner, H; Gillum, RF; Meisinger, C; Ford, I; Knuiman, MW; Rosengren, A; Lawlor, DA; Völzke, H; Cooper, C; Marín Ibañez, A; Casiglia, E; Kauhanen, J; Cooper, JA; Rodriguez, B; Sundström, J; Barrett-Connor, E; Dankner, R; Nietert, PJ; Davidson, KW; Wallace, RB; Blazer, DG; Björkelund, C; Donfrancesco, C; Krumholz, HM; Nissinen, A; Davis, BR; Coady, S; Whincup, PH; Jørgensen, T; Ducimetiere, P; Trevisan, M; Engström, G; Crespo, CJ; Meade, TW; Visser, M; Kromhout, D; Kiechl, S; Daimon, M; Price, JF; Gómez de la Cámara, A; Wouter Jukema, J; Lamarche, B; Onat, A; Simons, LA; Kavousi, M; Ben-Shlomo, Y; Gallacher, J; Dekker, JM; Arima, H; Shara, N; Tipping, RW; Roussel, R; Brunner, EJ; Koenig, W; Sakurai, M; Pavlovic, J; Gansevoort, RT; Nagel, D; Goldbourt, U; Barr, ELM; Palmieri, L; Njølstad, I; Sato, S; Monique Verschuren, WM; Varghese, CV; Graham, I; Onuma, O; Greenland, P; Woodward, M; Ezzati, M; Psaty, BM; Sattar, N; Jackson, R; Ridker, PM; Cook, NR; D'Agostino, RB; Thompson, SG; Danesh, J; Di Angelantonio, E; Emerging Risk Factors Collaboration, (2019) Equalization of four cardiovascular risk algorithms after systematic recalibration: individual-participant meta-analysis of 86 prospective studies. Eur Heart J, 40 (7). pp. 621-631. ISSN 1522-9645 https://doi.org/10.1093/eurheartj/ehy653
SGUL Authors: Whincup, Peter Hynes

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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.

Item Type: Article
Additional Information: © The Author(s) 2018. Published by Oxford University Press on behalf of the European Society of Cardiology. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
Keywords: 1102 Cardiovascular Medicine And Haematology, Cardiovascular System & Hematology
SGUL Research Institute / Research Centre: Academic Structure > Population Health Research Institute (INPH)
Journal or Publication Title: Eur Heart J
ISSN: 1522-9645
Language: eng
Dates:
DateEvent
14 February 2019Published
22 November 2018Published Online
4 October 2018Accepted
Publisher License: Creative Commons: Attribution-Noncommercial 4.0
Projects:
Project IDFunderFunder ID
G0800270Medical Research Councilhttp://dx.doi.org/10.13039/501100000265
SP/09/002British Heart Foundationhttp://dx.doi.org/10.13039/501100000274
268834European Research Councilhttp://dx.doi.org/10.13039/501100000781
HEALTH-F2-2012-279233Seventh Framework Programmehttp://dx.doi.org/10.13039/501100004963
MC_UU_12023/21Medical Research Councilhttp://dx.doi.org/10.13039/501100000265
91616079Netherlands Organization for Scientific ResearchUNSPECIFIED
PubMed ID: 30476079
Go to PubMed abstract
URI: http://openaccess.sgul.ac.uk/id/eprint/110432
Publisher's version: https://doi.org/10.1093/eurheartj/ehy653

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