Imperial College London


Faculty of MedicineSchool of Public Health

Chair in Global Environmental Health



+44 (0)20 7594 0767majid.ezzati Website




Norfolk PlaceSt Mary's Campus






BibTex format

author = {Pennells, L and Kaptoge, S and Wood, A and Sweeting, M and Zhao, X and White, I and Burgess, S and Willeit, P and Bolton, T and Moons, KGM and van, der Schouw YT and Selmer, R and Khaw, K-T and Gudnason, V and Assmann, G and Amouyel, P and Salomaa, V and Kivimaki, M and Nordestgaard, BG and Blaha, MJ and Kuller, LH and Brenner, H and Gillum, RF and Meisinger, C and Ford, I and Knuiman, MW and Rosengren, A and Lawlor, DA and Völzke, H and Cooper, C and Marín, Ibañez A and Casiglia, E and Kauhanen, J and Cooper, JA and Rodriguez, B and Sundström, J and Barrett-Connor, E and Dankner, R and Nietert, PJ and Davidson, KW and Wallace, RB and Blazer, DG and Björkelund, C and Donfrancesco, C and Krumholz, HM and Nissinen, A and Davis, BR and Coady, S and Whincup, PH and Jørgensen, T and Ducimetiere, P and Trevisan, M and Engström, G and Crespo, CJ and Meade, TW and Visser, M and Kromhout, D and Kiechl, S and Daimon, M and Price, JF and Gómez, de la Cámara A and Wouter, Jukema J and Lamarche, B },
doi = {eurheartj/ehy653},
journal = {European Heart Journal},
pages = {621--631},
title = {Equalization of four cardiovascular risk algorithms after systematic recalibration: individual-participant meta-analysis of 86 prospective studies},
url = {},
volume = {40},
year = {2018}

RIS format (EndNote, RefMan)

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.
AU - Pennells,L
AU - Kaptoge,S
AU - Wood,A
AU - Sweeting,M
AU - Zhao,X
AU - White,I
AU - Burgess,S
AU - Willeit,P
AU - Bolton,T
AU - Moons,KGM
AU - van,der Schouw YT
AU - Selmer,R
AU - Khaw,K-T
AU - Gudnason,V
AU - Assmann,G
AU - Amouyel,P
AU - Salomaa,V
AU - Kivimaki,M
AU - Nordestgaard,BG
AU - Blaha,MJ
AU - Kuller,LH
AU - Brenner,H
AU - Gillum,RF
AU - Meisinger,C
AU - Ford,I
AU - Knuiman,MW
AU - Rosengren,A
AU - Lawlor,DA
AU - Völzke,H
AU - Cooper,C
AU - Marín,Ibañez A
AU - Casiglia,E
AU - Kauhanen,J
AU - Cooper,JA
AU - Rodriguez,B
AU - Sundström,J
AU - Barrett-Connor,E
AU - Dankner,R
AU - Nietert,PJ
AU - Davidson,KW
AU - Wallace,RB
AU - Blazer,DG
AU - Björkelund,C
AU - Donfrancesco,C
AU - Krumholz,HM
AU - Nissinen,A
AU - Davis,BR
AU - Coady,S
AU - Whincup,PH
AU - Jørgensen,T
AU - Ducimetiere,P
AU - Trevisan,M
AU - Engström,G
AU - Crespo,CJ
AU - Meade,TW
AU - Visser,M
AU - Kromhout,D
AU - Kiechl,S
AU - Daimon,M
AU - Price,JF
AU - Gómez,de la Cámara A
AU - Wouter,Jukema J
AU - Lamarche,B
AU - Onat,A
AU - Simons,LA
AU - Kavousi,M
AU - Ben-Shlomo,Y
AU - Gallacher,J
AU - Dekker,JM
AU - Arima,H
AU - Shara,N
AU - Tipping,RW
AU - Roussel,R
AU - Brunner,EJ
AU - Koenig,W
AU - Sakurai,M
AU - Pavlovic,J
AU - Gansevoort,RT
AU - Nagel,D
AU - Goldbourt,U
AU - Barr,ELM
AU - Palmieri,L
AU - Njølstad,I
AU - Sato,S
AU - Monique,Verschuren WM
AU - Varghese,CV
AU - Graham,I
AU - Onuma,O
AU - Greenland,P
AU - Woodward,M
AU - Ezzati,M
AU - Psaty,BM
AU - Sattar,N
AU - Jackson,R
AU - Ridker,PM
AU - Cook,NR
AU - D'Agostino,RB
AU - Thompson,SG
AU - Danesh,J
AU - Di,Angelantonio E
AU - Emerging,Risk Factors Collaboration
DO - eurheartj/ehy653
EP - 631
PY - 2018///
SN - 1522-9645
SP - 621
TI - Equalization of four cardiovascular risk algorithms after systematic recalibration: individual-participant meta-analysis of 86 prospective studies
T2 - European Heart Journal
UR -
UR -
UR -
UR -
VL - 40
ER -