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

Lisa Pennells, Stephen Kaptoge, Angela Wood, Mike Sweeting, Xiaohui Zhao, Ian White, Stephen Burgess, Peter Willeit, Thomas Bolton, Karel G. M. Moons, Yvonne T. van der Schouw, Randi Selmer, Kay-Tee Khaw, Vilmundur Gudnason, Gerd Assmann, Philippe Amouyel, Veikko Salomaa, Mika Kivimaki, B. rge G. Nordestgaard, Michael J. Blaha & 36 others Lewis H. Kuller, Hermann Brenner, Richard F. Gillum, Christa Meisinger, Ian Ford, Matthew W. Knuiman, Annika Rosengren, Debbie A. Lawlor, Henry Völzke, Cyrus Cooper, Alejandro Marín Ibañez, Edoardo Casiglia, Jussi Kauhanen, Jackie A. Cooper, Beatriz Rodriguez, Johan Sundström, Elizabeth Barrett-Connor, Rachel Dankner, Paul J. Nietert, Karina W. Davidson, Robert B. Wallace, Dan G. Blazer, Cecilia Björkelund, Chiara Donfrancesco, Harlan M. Krumholz, Aulikki Nissinen, Barry R. Davis, Sean Coady, Marjolein Visser, Jacqueline M. Dekker, Ron T. Gansevoort, Mark Woodward, Simon G. Thompson, John Danesh, Emanuele Angelantonio, Emerging Risk Factors Collaboration

Research output: Contribution to journalArticleAcademicpeer-review

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 languageEnglish
Pages (from-to)621-631
JournalEuropean Heart Journal
Volume40
Issue number7
DOIs
Publication statusPublished - 14 Feb 2019

Cite this

Pennells, L., Kaptoge, S., Wood, A., Sweeting, M., Zhao, X., White, I., ... Emerging Risk Factors Collaboration (2019). Equalization of four cardiovascular risk algorithms after systematic recalibration: individual-participant meta-analysis of 86 prospective studies. European Heart Journal, 40(7), 621-631. https://doi.org/10.1093/eurheartj/ehy653
Pennells, Lisa ; Kaptoge, Stephen ; Wood, Angela ; Sweeting, Mike ; Zhao, Xiaohui ; White, Ian ; Burgess, Stephen ; Willeit, Peter ; Bolton, Thomas ; Moons, Karel G. M. ; van der Schouw, Yvonne T. ; Selmer, Randi ; Khaw, Kay-Tee ; Gudnason, Vilmundur ; Assmann, Gerd ; Amouyel, Philippe ; Salomaa, Veikko ; Kivimaki, Mika ; Nordestgaard, B. rge G. ; Blaha, Michael J. ; Kuller, Lewis H. ; Brenner, Hermann ; Gillum, Richard F. ; Meisinger, Christa ; Ford, Ian ; Knuiman, Matthew W. ; Rosengren, Annika ; Lawlor, Debbie A. ; Völzke, Henry ; Cooper, Cyrus ; Marín Ibañez, Alejandro ; Casiglia, Edoardo ; Kauhanen, Jussi ; Cooper, Jackie A. ; Rodriguez, Beatriz ; Sundström, Johan ; Barrett-Connor, Elizabeth ; Dankner, Rachel ; Nietert, Paul J. ; Davidson, Karina W. ; Wallace, Robert B. ; Blazer, Dan G. ; Björkelund, Cecilia ; Donfrancesco, Chiara ; Krumholz, Harlan M. ; Nissinen, Aulikki ; Davis, Barry R. ; Coady, Sean ; Visser, Marjolein ; Dekker, Jacqueline M. ; Gansevoort, Ron T. ; Woodward, Mark ; Thompson, Simon G. ; Danesh, John ; Angelantonio, Emanuele ; Emerging Risk Factors Collaboration. / Equalization of four cardiovascular risk algorithms after systematic recalibration: individual-participant meta-analysis of 86 prospective studies. In: European Heart Journal. 2019 ; Vol. 40, No. 7. pp. 621-631.
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title = "Equalization of four cardiovascular risk algorithms after systematic recalibration: individual-participant meta-analysis of 86 prospective studies",
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.",
author = "Lisa Pennells and Stephen Kaptoge and Angela Wood and Mike Sweeting and Xiaohui Zhao and Ian White and Stephen Burgess and Peter Willeit and Thomas Bolton and Moons, {Karel G. M.} and {van der Schouw}, {Yvonne T.} and Randi Selmer and Kay-Tee Khaw and Vilmundur Gudnason and Gerd Assmann and Philippe Amouyel and Veikko Salomaa and Mika Kivimaki and Nordestgaard, {B. rge G.} and Blaha, {Michael J.} and Kuller, {Lewis H.} and Hermann Brenner and Gillum, {Richard F.} and Christa Meisinger and Ian Ford and Knuiman, {Matthew W.} and Annika Rosengren and Lawlor, {Debbie A.} and Henry V{\"o}lzke and Cyrus Cooper and {Mar{\'i}n Iba{\~n}ez}, Alejandro and Edoardo Casiglia and Jussi Kauhanen and Cooper, {Jackie A.} and Beatriz Rodriguez and Johan Sundstr{\"o}m and Elizabeth Barrett-Connor and Rachel Dankner and Nietert, {Paul J.} and Davidson, {Karina W.} and Wallace, {Robert B.} and Blazer, {Dan G.} and Cecilia Bj{\"o}rkelund and Chiara Donfrancesco and Krumholz, {Harlan M.} and Aulikki Nissinen and Davis, {Barry R.} and Sean Coady and Marjolein Visser and Dekker, {Jacqueline M.} and Gansevoort, {Ron T.} and Mark Woodward and Thompson, {Simon G.} and John Danesh and Emanuele Angelantonio and {Emerging Risk Factors Collaboration}",
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journal = "European Heart Journal",
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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, BRG, 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, Visser, M, Dekker, JM, Gansevoort, RT, Woodward, M, Thompson, SG, Danesh, J, Angelantonio, E & Emerging Risk Factors Collaboration 2019, 'Equalization of four cardiovascular risk algorithms after systematic recalibration: individual-participant meta-analysis of 86 prospective studies' European Heart Journal, vol. 40, no. 7, pp. 621-631. https://doi.org/10.1093/eurheartj/ehy653

Equalization of four cardiovascular risk algorithms after systematic recalibration: individual-participant meta-analysis of 86 prospective studies. / Pennells, Lisa; Kaptoge, Stephen; Wood, Angela; Sweeting, Mike; Zhao, Xiaohui; White, Ian; Burgess, Stephen; Willeit, Peter; Bolton, Thomas; Moons, Karel G. M.; van der Schouw, Yvonne T.; Selmer, Randi; Khaw, Kay-Tee; Gudnason, Vilmundur; Assmann, Gerd; Amouyel, Philippe; Salomaa, Veikko; Kivimaki, Mika; Nordestgaard, B. rge G.; Blaha, Michael J.; Kuller, Lewis H.; Brenner, Hermann; Gillum, Richard F.; Meisinger, Christa; Ford, Ian; Knuiman, Matthew W.; Rosengren, Annika; Lawlor, Debbie A.; Völzke, Henry; Cooper, Cyrus; Marín Ibañez, Alejandro; Casiglia, Edoardo; Kauhanen, Jussi; Cooper, Jackie A.; Rodriguez, Beatriz; Sundström, Johan; Barrett-Connor, Elizabeth; Dankner, Rachel; Nietert, Paul J.; Davidson, Karina W.; Wallace, Robert B.; Blazer, Dan G.; Björkelund, Cecilia; Donfrancesco, Chiara; Krumholz, Harlan M.; Nissinen, Aulikki; Davis, Barry R.; Coady, Sean; Visser, Marjolein; Dekker, Jacqueline M.; Gansevoort, Ron T.; Woodward, Mark; Thompson, Simon G.; Danesh, John; Angelantonio, Emanuele; Emerging Risk Factors Collaboration.

In: European Heart Journal, Vol. 40, No. 7, 14.02.2019, p. 621-631.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - Equalization of four cardiovascular risk algorithms after systematic recalibration: 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, B. rge 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 - Visser, Marjolein

AU - Dekker, Jacqueline M.

AU - Gansevoort, Ron T.

AU - Woodward, Mark

AU - Thompson, Simon G.

AU - Danesh, John

AU - Angelantonio, Emanuele

AU - Emerging Risk Factors Collaboration

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 - https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85061592905&origin=inward

UR - https://www.ncbi.nlm.nih.gov/pubmed/30476079

U2 - 10.1093/eurheartj/ehy653

DO - 10.1093/eurheartj/ehy653

M3 - Article

VL - 40

SP - 621

EP - 631

JO - European Heart Journal

JF - European Heart Journal

SN - 0195-668X

IS - 7

ER -